JAMS - journals.squ.edu.om

JAMSJournal of Agricultural and Marine Sciences

• AReviewonSolarDryingofFish

• GISandremotesensingtechniquesinControlledEnvironmentAgriculture:Areview

• AreviewonthenoveldiscoveriesofBegomovirusesinOman

• CharacterizationofGeneticDiversityinDhofariWildGazelles

• PhysicalandChemicalFruitQualityAttributesofTwoPomegranateCultivarsGrownatVaryingAltitudesofAl-HajarMountainsinOman

• SeroprevalenceofTrypanosomaevansiinfectionsamongdromedarycamels(Camelusdrome-daries)inNorthAsh-SharqiyaGovernorate,SultanateofOman

• Anti-diabeticPotentialPropertiesofTwoEdibleOmaniWildPlants(PteropyrumscopariumandOxaliscorniculata)

• GrowthModelandForecastingPricesofSomeAgriculturalProductsinBangladesh

HistopathologyofthePancreatTissuesofRatTreatedwithHealthFunctionalOmaniPlant

Sultan Qaboos University - Sultanate of Oman

Volume 26, Issue 2, 2021

www.squ.edu.om/agr/JAMS

Contents

A Sultan Qaboos University Research Journal

Journal of Agricultural and Marine Sciences (JAMS(JAMS is an international peer-reviewed journal that publishes original fundamental and applied research articles in a wide variety of disciplines of the agricultural and marine sciences. The journal provides a forum for specialists and practitioners and brings together quality papers dealing with agricultural economics, natural resource economics, animal and veterinary sciences, bio-resources, biotechnologies, soil sciences, water management, agricultural engineering, fisheries, marine sciences, food science, human nutrition, plant production, plant protection, rural environment, coastal zone management and oceanography. All issues of the Journal of Agricultural and Marine Sciences are freely available online and do not carry any publication charges.

Sultan Qaboos University Academic Publication Board

JAMS Editorial Board

Prof. Shafiur Rahman (Editor-in-Chief )Dr. Muhammad Farooq (Editor)

Dr. Ali Al-Maktoomi Dr. Haytham Alieldin Ali Dr. Waleed Al-MarzooqiDr. Daniel Blackburn Dr. Lokman Zaibet Dr. Hemanatha P W JayasuriyaDr. Zaher Al-Attabi Dr. Velazhahan Rethinasamy Dr. Rhonda JankeDr. Michel R. Claereboudt Prof. Anvar Kacimov Dr. Mohamed Essa MusthafaDr. Wenresti Glino Gallardo

International Advisory BoardProf. James W. Oltjen, University of California, USAProf. Paul Moughan, Massey University, New ZealandProf. Donald C. Slack, University of Arizona, USAProf. R. Paul Singh, University of California, USAProf. Stephan Kasapis, RMIT University, AustraliaProf. Christopher D. Lu, University of Hawaii, USAProf. Mattheus Goosen, Alfaisal University, Saudi ArabiaProf. Ewen McLean, Virginia Polytechnic, USAProf. Ching Yuan Hu, University of Hawaii, USA

Technical Assistant: Alia Ali Al-Rutani

The Journal of Agricultural and Marine Sciences (JAMS) is published by Sultan Qaboos University, P.O. Box 50, Al-Khod 123, Muscat, Sultanate of Oman.Year of issue: 2021

The content of the journal is licenced under the Creative Common (CC BY ND) licensing schemes the details of which can be found at creativecommons.org/licenses/by-nd/4.0/legalcode. The Journal of Agricultural and Marine Sciences is not responsible for opinions printed in its publications; they represent the views of the individuals to whom they are credited and are not binding to the Journal.

Manuscript submission is made through an online management system at journals.squ.edu.om/index.php/jams Alternatively, if internet access is difficult, manuscripts can be emailed to [email protected] see Guidelines for Authors at journals.squ.edu.om/index.php/jams/about/submissions#authorGuidelines

Dr. Amer Al-HinaiChair, Academic Publication BoardProf. Yahya Al-WahaibiMr. Jamal Al-Ghailani

Prof. Said AldhafriProf. Shafiur RahmanProf. Mohammad S. Khan

Prof. Samir Al-AdawiProf. Ibrahim MetwallyDr. Mohammed Al-Saqri

Associate Editors

Contents

Review ARticle

ReseARch ARticle

A Review on Solar Drying of Fish 01Nasreen S. Al-Mahruqi, Abdulrahim M. Al-Ismaili

GIS and remote sensing techniques in Controlled Environment Agriculture: A review 10 Asma M. Al-Maimani, Abdulrahim M. Al-Ismaili, Yassine Charabi

A review on the novel discoveries of Begomoviruses in Oman 24 M. S. Shahid, A. M. Al-Sadi

Characterization of Genetic Diversity in Dhofari Wild Gazelles 35 Ahmed Jashool, Alya Al Ansari, Waleed Al Marzooqi, Othman Alqaisi, Mansour Al Gahdhami, Mohammed A Al-Abri

Physical and Chemical Fruit Quality Attributes of Two Pomegranate Cultivars Grown at Varying Altitudes of Al-Hajar Mountains in Oman 42 Basim S. AL-Kalbani, Rashid A. Al-Yahyai, Abdullah M. Al-Sadi, Al-Ghaliya H. Al-Mamari

Seroprevalence of Trypanosoma evansi infections among dromedary camels (Camelus dromedaries) in North Ash-Sharqiya Governorate, Sultanate of Oman 51 A. H. Al-Kharusi, Elshafie I. Elshafie, K. E. M. Ali, R. Al-Sinadi, N. Baniuraba, F. Al-Saifi and Y. Al-Mawali

Anti-diabetic Potential Properties of Two Edible Omani Wild Plants (Pteropyrum scoparium and Oxalis corniculata) 56 Iman R. S. Al-Qalhati, Mostafa I. Waly, Lyutha Al-Subhi, Zaher Al-Attabi

Growth Model and Forecasting Prices of Some Agricultural Products in Bangladesh

64 Mohammad Abdullah Al Mamun, Mohammad Zakir Hossain, Sheikh Mohammad Sayem, Khondaker Md. Mostafizur Rahman

JAMS: Guidelines for authors 72

Review ARticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 1–9DOI: 10.24200/jams.vol26iss2pp1-9Received 25 Oct 2020Accepted 22 March 2021

A Review on Solar Drying of Fish

Nasreen S. Al-Mahruqi and Abdulrahim M. Al-Ismaili*

Abdulrahim M. Al-Ismaili*( ) [email protected]; [email protected], Department of Soils, Water and Agricultural Engineering, Sultan Qaboos University, Oman

Introduction

Oman is considered one of the largest fish pro-ducers and consumers in the Gulf Cooperation Council (FAO, 2015). Fish is a very popular food

due to its high protein and nutrients content. Howev-

er, the due to the high moisture content in fish (Tiwari et al., 2009), spoilage is a critical issue facing fish pro-ducers. Because of the high spoilage rate of fish (Jain and Pathare, 2007), Ghaly et al. (2010) found that 30% of fish is lost every year. Therefore, several techniques have been practiced to preserve fish in order to increase their shelf life and to maintain their texture, flavour and nutritional value (Ghaly et al., 2010). Smoking, drying, chilling, brining and freezing are among the common-

مراجعة على التجفيف الشمسي للأسماكنسرين س. المحروقية ، عبدالرحيم م. الإسماعيلي *

Abstract. Oman is one of the major fish producers in this region. Fish is highly perishable, therefore different pres-ervation techniques, such as smoking, drying, chilling, brining and freezing are being used. Solar drying is one of the most popular technique due to its simplicity and low cost as compared to other techniques. This study aimed to review the different types of solar drying techniques and highlighted the quality measures of solar dried fish. Solar drying tech-niques can be divided into three types: open-sun drying, direct and indirect solar drying. The open-sun drying is the most adoptable method because it is the cheapest preservation technique. However, this technique has several draw-backs, such as the uncertainty of weather, large implementation area, required time, poor drying rate, high labor costs, possible attack by insects, microorganism and birds, and contaminated with dust and foreign materials. Solar dryers, on the other hand, overcome the most of drawbacks associated with open-sun drying. They have shorter drying time and higher drying rate, and at the same time these enhance the physical properties of dried fish. For better understanding of the drying processes many regression models were used and the exponential model was found to be the best fitted mod-el describing the drying behavior. Fish possesses good nutritional value due to higher amount of proteins, lipids and ash contents. For higher shelf life, fish has to meet certain characteristics with respect to pH, water activity, microbial load, total volatile base nitrogen (TVB-N), trimethylamine nitrogen (TMA-N) and enzymatic autolysis. For a very good qual-ity, the pH must be ranged from 6.0-6.9 and the water activity must be lower than 0.6. The TVB-N and TMA-N are the indicators of spoilage and their upper acceptable limits are 10-15 mg/100g and 35-40 mg/100g, respectively. Total plate count (TPC) and total fungal count (TFC) are two attributes used to assess the microbiological quality of fish products. The autolysis changes in the fish lead to spoilage as a result of the production of biogenic amines and microbial growth. Studying the health aspect of dried fish is very important for the human body to obtain a greater proportion of proteins and important substances away from the harmful chemicals that may appear in traditional draying technique.

Keywords: Solar drying techniques, fish, quality

الملخص:عمــان هــي واحــدة مــن أكــر منتجــي الأسمــاك في هــذه المنطقــة، ولأن الأسمــاك قابلــة للتلــف بدرجــة كبــرة فإنــه يتــم اســتخدام تقنيــات مختلفــة لحفظهــا؛ مثــل التدخــن والتجفيــف والتريــد والتخمــر والتجميــد، ويعــد التجفيــف الشمســي مــن أكثــر التقنيــات شــيوعا نظــرا لبســاطته وتكلفتــه المنخفضــة مقارنــة بالتقنيــات الأخــرى. ولقــد هدفــت هــذه الدراســة إلى مراجعــة الأنــواع المختلفــة لتقنيــات التجفيــف الشمســي وإبــراز مقاييــس الجــودة للأسمــاك المجففــة شمســيا. ويمكــن تقســيم تقنيــات التجفيــف الشمســي إلى ثلاثــة أنــواع: التجفيــف الشمســي المفتــوح، والتجفيــف الشمســي المباشــر وغــر المباشــر داخــل المجففــات الشمســية، ويعتــر التجفيــف تحــت أشــعة الشــمس المفتوحــة هــو الأســلوب الأكثــر اســتخداما لأنــه أرخــص تقنيــة للحفــظ، ولكــن هــذه التقنيــة لهــا العديــد مــن العيــوب؛ مثــل تقلبــات الطقــس، والمســاحة الكبــرة الــي تحتاجهــا، وطــول الوقــت المطلــوب للتجفيــف، وبــطء معــدل التجفيــف، وتكاليــف العمالــة المرتفعــة، وتعرضهــا للحشــرات والكائنــات الحيــة الدقيقــة والطيــور، واحتماليــة التلــوث بالغبــار والمــواد الخارجيــة. ولقــد وجــد أن المجففــات الشمســية تتغلــب علــى معظــم العوائــق المرتبطــة بالتجفيــف تحــت أشــعة الشــمس المفتوحــة وذلــك لأن المجففــات الشمســية تحتــاج لوقــت تجفيــف أقصــر ولهــا معــدل تجفيــف أعلــى، وفي نفــس الوقــت فإنهــا تحســن مــن الخصائــص الفيزيائيــة للأسمــاك المجففــة، ولفهــم عمليــات التجفيــف بشــكل أفضــل قــام الباحثــون باســتخدام العديــد مــن نمــاذج الانحــدار، ووجــد أن النمــوذج الأســي هــو أفضــل نمــوذج ملائــم يصــف ســلوك التجفيــف. ومــن ناحيــة أخــرى؛ فــإن الأسمــاك تمتلــك قيمــة غذائيــة جيــدة بســبب احتوائهــا علــى كميــات كبــرة مــن الروتينــات والدهــون ومحتــويات الرمــاد، وللحصــول علــى عمــر تخزيــي أعلــى فإنــه يجــب أن تفــي الأسمــاك بخصائــص معينــة فيمــا يتعلــق بدرجــة الحموضــة والنشــاط المائــي والحمــل الميكــروبي وإجمــالي النيتروجــن الأساســي المتطايــر )TVB-N(، والنيتروجــن ثلاثــي ميثيــل الأمــن )TMA-N( والانحــلال الــذاتي الأنزيمــي، وللحصــول علــى جــودة جيــدة جــدا يجــب أن يــتراوح الرقــم الهيدروجيــي بــن 6.0-6.9 وأن يكــون نشــاط المــاء أقــل مــن 0.6. ويعــد TVB-N و TMA-N همــا مؤشــرا التلــف وحدودهمــا القصــوى المقبولــة هــي 10-15 مجــم/100 جــم و 35-40 مجــم/100 جــم علــى التــوالي، وأمــا عــن إجمــالي عــدد الصفائــح )TPC( وإجمــالي عــدد الفطــريات )TFC( فهمــا سمتــان تســتخدمان لتقييــم الجــودة الميكروبيولوجيــة لمنتجــات الأسماك. وتؤدي تغرات التحلل الذاتي في الأسماك إلى تلفها نتيجة إنتاج الأمينات الحيوية والنمو الميكروبي. وتعتر دراسة الجانب الصحي للأسماك المجففة أمرا مهما جــدا لصحــة الإنســان مــن أجــل الحصــول علــى نســبة كبــرة مــن الروتينــات والمــواد المهمــة بعيــدا عــن المــواد الكيميائيــة الضــارة الــي قــد تظهــر في تقنيــة التجفيــف التقليديــة.

الكلمات المفتاحية: طرق التجفيف التقليدية، الأسماك، الجودة.

2 SQU Journal of Agricultural and Marine Sciences, 2021, Volume 26, Issue 2


ly-practiced techniques for fish preservation (Ghaly et al., 2010). However, fish drying is the most popular technique (Jain and Pathare, 2007; Sahu et al., 2016), which is achieved using different approaches such as solar, electrical, spray and mechanical drying meth-ods (Prakash and Kumar, 2014; Singh et al., 2017). Due to the increase in the prices of fossil fuels, solar dry-ing became the most widely-used drying method as it uses a renewable source of energy and does not rely on fossil fuel (Bala and Janjai, 2009; Prakash and Ku-mar, 2014). The objectives of this article were to re-view the different types of solar drying techniques and to highlight the quality measures of solar dried fish.

Solar Drying TechniquesSolar energy is the most abundant source of energy on the earth and consequently, it is used in many pro-cesses. Solar drying is a traditional drying process that harnesses solar energy to speed up the drying process. There are three types of solar drying techniques, which are open-sun drying, direct and indirect solar drying (Sahu et al., 2016). The most popular technique is drying by the direct exposure to sun which is considered the cheapest technique as it does not demand a significant infrastructure and operational costs (Jain and Pathare, 2007) (Figure 1). When the product is exposed to sun, its temperature increases due to heat absorption, which in turn leads to moisture reduction, i.e. drying.

In the direct solar drying technique, the product is placed inside a structure that is covered with a trans-parent material, such as plastic and glass (Figure 2). This kind of structure traps the solar heat (greenhouse effect) as it allows shortwave radiation to pass and cap-tures the longwave radiation (Singh et al., 2017), i.e. causing higher air temperatures and thus, faster drying (Sahu et al., 2016). In this technique, drying rate can be additionally increased by the use of fans to bring dry-er air over the products and this technique is known as

“forced convective” direct drying (Singh et al., 2017).In the indirect drying techniques (Figure 3), products

are not exposed to direct sun light but instead, ambient air is heated by solar radiation via a solar collector and then the hot air flows over the products. The air is circu-lated in this technique either by natural convection (i.e. indirect dryer under passive mode) or by the use of ex-haust fans. In the former, ambient air enters to the solar collector through a lower vent and then the hot air leaves to the drying chamber through a higher vent, i.e. ther-mosyphic effect (Prakash and Kumar, 2014). In the latter, exhaust fans located at the outlet vent are used to move the air stream and this technique is known as forced convection indirect solar drying (Sahu et al., 2016). The forced convection dryer is more suitable for products with high moisture content while natural convection is suitable for low moisture products (Sahu et al., 2016; Singh et al., 2017). Prakash and Kumar (2014) found that the convective mass transfer coefficient in the forced convection mode was double than that in the natural convection mode. As illustrated in Figures 2 and 3, the structure of direct and indirect solar dryers is similar to the structure of greenhouses, which may explain the rea-son why these dryers are also called “greenhouse dryers”.

The efficiency of solar dryers is enhanced by the in-tegration with photovoltaic (PV) systems. The use of PV-integrated solar dryers is very practical if forced con-vection is to be implemented in the areas where electric-ity is not available or not affordable (Sahu et al., 2016). In terms of solar drying performance, the greenhouse dry-er is considered the best alternative to sun drying. Bala and Janjai (2009) reported that PV-integrated green-house solar dryers can reduce the drying time by almost 50%. The shape of the greenhouse is another factor af-fecting the drying process. It was reported by Charters et al. (2017) that the dome shape (hemispherical) can offer the maximum utilization of solar radiation and the even-span shape is utilized for proper air mixing.

Figure 1. Solar drying by direct sun exposure for (a) Red chili pepper (Walters and Jha, 2016), and (b) Fish (Ochieng et al., 2015).

3Review Article

Al-Mahruqi and Al-Ismaili

Advantages and Disadvantages of Solar Drying Solar radiation is an abundant, eco-friendly and inex-haustible source of energy (Ghaly et al., 2010). Hence, it represents the cheapest way to preserve food (Jain and Pathare, 2007). Nevertheless, there are many dis-advantage related to open-sun drying method, such as the uncertainties of weather, requirement of large im-plementation area, time-consuming, poor drying rate, high labour costs, attacking by insects, microorganism and birds, and mixing with dust and foreign materials (Jain and Pathare, 2007; Al Rawahi et al., 2013; Martunis, 2013; Sontakke and Salve, 2015). Mansur et al. (2013) found that, during open-sun drying, some fish samples contained a large amount of debris from the poor quality underlying material and the dried samples have under-gone surplus drying or inappropriate drying and han-dling. However, some of these limitations, e.g. time-con-suming, insect attacks and dust contamination, can be

eliminated by the use of greenhouse dryers (Charters et al., 2017; Sontakke and Salve, 2015).

Solar Fish DryingIn many coastal areas, fish is considered a main source of food and income (Belwal et al. 2015). However, fish products are highly perishable and thus, have a short shelf life (Bala and Mondol, 2001). Drying is the most widely-used preservation technique used to overcome the spoilage problem. Because of their high market value and availability, several fish species such as ribbon fish, golden anchovies, croker, prawns, paplet and surmai are dried using solar drying techniques (Sengar et al., 2009).

In Oman, due to the high fish production and con-sumption, traditional sun drying techniques are widely practiced to dry a variety of fish types such as sardine, anchovy and jake mackerel (Al Bulushi et al., 2013; Al Rawahi et al., 2013). Sardine fish alone represents 80% of the total Oman small fish catching and the annual amount of dried sardine is 23000 tons, which is mainly used as a livestock feed (Al-Jufaili and Al-Jahwari, 2011; Basunia et al., 2011). Open-sun drying of fish is an old method used worldwide to dry a variety of fish types. In Oman, as an example, sardine fish (Figure 4) are tra-ditionally dried by dispersing the fish on sandy beaches for 7 days in low ambient temperatures and 4-5 days in high temperatures (Basunia et al., 2011). This method, although widely-accepted, is associated with a substan-tial loss of almost 30-40% of the total dried amount due to a variety of reasons that include rain, wind, dust and contamination and consumption by animals, birds and rats (Al Rawahi et al., 2013).

Other solar drying techniques such as greenhouse dryers are implemented to overcome the drawbacks of open-sun drying. For instance, Sengar et al. (2009) used a low cost passive (natural convection) multi-shelf greenhouse solar dryer (Figure 5) to dry prawns. The fish dried inside the solar dryer were found better than the fish dried in open-sun in terms of drying time, texture and color. In a similar study, silver jewfish was dried by a natural convection solar tunnel drier in Bangladesh (Bala and Janjai, 2009). The solar dried products had better quality with a significant reduction in drying time as compared with open-sun drying. In another study, a low cost passive solar tunnel dryer (Figure 6) was de-veloped in Oman to dry sardine, skater bream and jake mackerel (Al Rawahi et al., 2013). On the other hand, an active (forced convection) greenhouse solar dryer was used in Indonesia for drying anchovy fish (Figure 7) (Martunis, 2013). In a similar study, jewfish was dried in a hybrid solar drying system and it was found that the drying time took only 8 h to reduce the moisture content from 64 to 10% (Singh et al., 2017). All of the abovemen-tioned dryers managed to reduce the drying time with increased water loss.

Several studies focused on the calculation of drying time, drying rate and the final moisture content of the

Figure 2. Direct solar dryer (Singh et al., 2017).

Figure 3. Indirect forced convection solar dryer; 1: Vent , 2: Exhaust fan , 3: Heating chamber, 4: Drying chamber and 5: Glass cover with fibre (Singh et al., 2017).



dried fish products. For example, the drying time to reduce the initial moisture content of prawns from 75 to 16.4% in open-sun drying and to 16.5% in a low-cost passive solar dryer was 11 and 8 h, respectively (Sengar et al., 2009). Similarly, Abraha et al. (2017) found that open-sun drying of anchovy took 5 days and inside a solar tent drier, it took only 3 days. Using a natural con-vective solar drier, it was found that the drier was able to reduce the initial moisture content of bayad fish flakes from 78.67% to a final moisture content of 11.41% (Ba-biker et al., 2014). Mustapha et al. (2014) studied five dif-ferent solar driers and found that black stone-inserted glass drier showed the fastest drying rate in comparison to the plastic drier, mosquito net drier, glass drier and aluminum drier for drying African catfish and Nile tila-pia. Martunis (2013) reported that the drying rate of fish using a force convection greenhouse was 3.29% per hour in a total drying time of 11 h while the same amount of

fish took 2 days to dry in the sun. Using a parabolic-dish solar collector (Figure 8), Solomon et al. (2016) found that salted prawn and unsalted prawn required 8 h and 15 h to dry, respectively which highlights the effect of salting on the drying time. In all drying processes, the drying time increased with increasing humidity in the ambient air (Bala and Janjai, 2009). In general, the drying rate starts high at the beginning of the drying process and decreases with the reduction in moisture content (Jain and Pathare, 2007).

The solar drying technique has a great effect on the physical properties of dried fish. Under open-sun drying, (Mansur et al., 2013) compared three physical character-istics, namely, color, odor and texture, of three types of fish; labeo, channa and wallago attu. The results showed that labeo and channa fish had better quality than walla-go fish which developed bitter taste, rancid odor and soft and fibrous texture. However, all three fish had brown color as compared to the fresh fish which have cream color. In a similar study the channa fish showed good physical quality as compared with wallago and glosso-gobius fish (Majumdar et al., 2017). Islam et al. (2012) reported differences in the physical properties of dried mola fish in a solar tunnel. The final color of the dried fish was ranging from white to light brown and the tex-ture was firm and flexible with good odor. The overall quality of the dried mola fish was excellent as compared with the traditionally dried mola fish, where the color was brown and the texture was soft with off-odor. In general, Mustapha et al. (2014) found that the physical parameters of open-sun dried fish was the least accept-able among the fish dried in five other solar driers.

Abraha et al. (2017) reported that the physical prop-erties, such as color, flavor, appearance, texture and odor was superior for fish dried in a solar tent drier to fish dried in open-sun. For instance, anchovy fish dried in a greenhouse dryer undergone no color change during the drying process (Martunis, 2013). Sengar et al. (2009)

Figure 4. Traditional open-sun drying of sardine, (a) Sar-dine fish dispersed on a sandy beach and (b) Animals eating from the dried sardine (Al-Jufaili and Al-Jahwari, 2011).

Figure 5. Low cost passive solar dryer (Sengar et al., 2009).

5Review Article


found that the color and texture of salted fish inside a low cost dryer were better as compared with unsalted fish, but the dried fish in open-sun was the least accepted one. In a similar study, the addition of salts in the dried fish affected positively the physical (organoleptic) prop-erties, such as aroma, taste, texture and general accept-ability. Solomon et al. (2016) observed good taste and total acceptability of salted fish were superior to those of unsalted fish when both were dried in a solar drier. Therefore, direct and indirect solar drying techniques provide better quality fish than open-sun drying and salt-ed fish gave better physical properties than unsalted fish.

For better understanding of the behavior of drying processes, regression models were extensively used. To optimize the drying process, accurate simulation-mod-els can be to predict the performance of the product to be dried (Belessiotis and Delyannis, 2011). Non-linear regression models were used to best-fit experimental drying curves with the closest matching models. The

drying rate could be either constant (fixed) or falling (de-creasing), however the falling rate prevails (Toujani et al., 2013) because in most biological products, the constant rate does not exist (Bellagha et al., 2002). In the drying process, the moisture is removed rapidly at the beginning then it decreases slowly as the drying progresses. This is because at the beginning moisture evaporates from the surface of the fish and then moisture moves by diffu-sion inside the fish material toward the surface (Toujani et al., 2013). This behavior is described using different regression models such as exponential, logarithmic, diffusion-approximate, two-term and many others.

Hubackova et al. (2014) found that the appropriate models describing the natural convection solar drying kinetics of five species of fish were as follows; loga-rithmic model for climbing perch and Nile tilapia fish; diffusion-approximate model for swamp eel and walk-ing catfish; and two-term model for channa fish. In an-other study, the drying kinetics of sardine muscle were well-fitted using two models, namely, exponential and page (Djendoub et al., 2009). Figure 9 illustrates the ex-ponential drying curve of tilapia fish (Kituu et al., 2010). On the other hand, a logarithmic regression model was used to describe the drying rate of prawn and chelwa fish under open-sun drying (Jain and Pathare, 2007). In electric oven-drying, the most appropriate mod-el for all fish species is the Modified Page1 because of the uniform drying conditions except for channa fish where the exponential model showed the best-fit. All mentioned models can help in predicting the dry-ing kinetics of fish using different drying techniques.

Health aspects of solar-dried fishThe quality of dried fish has to meet certain character-istics with respect to protein, lipid and ash content. Re-cent studied proved that dried fish with high amount of protein, ash and fat content have very good nutritional value (Siddique et al., 2012). Proteins control the metab-olism in the nerves and bones and control blood sugar level by producing peptides (Jónsson et al., 2007). The protein content in dried fish is higher compared to fresh fish, which is a desirable characteristic. The protein is an important factor that helps in the quality assessment of dried fish (Hazarika et al., 2016). Lipids and ash are two important sources of energy for the body. It was found that the amount of lipids is affected by the dry-ing technique where it was reported that lipid content of open sun dried fish is less than that in fish dried with other drying methods (Anh et al., 2015). Commonly, ash content of dried fish is higher than that of fresh fish. However, it could be less in the dried fish because the ash content comes from inorganic matter, i.e. a residue that remains after drying, where water content and or-ganic matter are reduced (Oladipo and Bankole, 2013). When the values of protein, lipids and ash content were analyzed for 10 fish species dried under open sun, they ranged 28.63-53.84, 4.42-16.52 and 8.96-30.30 g/100 g,

Figure 6. Fish drier diagram (Al Rawahi et al., 2013).

Figure 7. Force convection greenhouse solar dryer (Mar-tunis, 2013).



respectively (Hazarika et al., 2016). In a similar study, Islam et al. (2013) reported that the protein, lipids and ash content for 4 fish types, namely, Amblypharyngodon mola (Mola), Puntius spp. (Punti), Channa punctata (Taki) and Glossogobius giuris (Bele), dried under open-sun amounted to 32.02-41.38 g/100 g (Channa puncta-tus had the highest value), 3.21-14.03 g/100 g (Channa punctatus had the lowest value) and 20.14-24.40 g/100 g.

Sultana et al. (2008) compared the protein, lipids and ash content of fresh silver jew fish, Bombay and duck ribbon fish with the dried samples in a solar tunnel dry-er. The protein content of fresh fish ranged from 65.90-71.60 g/100 g, lipids ranged from 13.42 to 21.30 g/100 g and ash content from 11.27 to 12.44 g/100 g where-as after drying they ranged 71.9-80.52, 8.05-19.18 and 9.47-10.24 g/100 g, respectively. Similarly, Babiker et al. (2014) found that the protein, fat and ash content of dried bayad fish flakes using a natural convective solar drier were 69.19, 0.23 and 30.68 g/100g of product, re-spectively while, the fresh fish contained 92.51, 0.22 and 7.27 g/100 g of product, respectively.

Across the developing countries, dried fish is con-sidered a widespread delicacy. Therefore, extending the shelf life of dried fish is necessary for long time storage. To achieve this, dried fish has to meet certain charac-teristics such as pH, water activity, microbial load, total volatile base nitrogen (TVB-N), trimethylamine nitro-gen (TMA-N) and enzymatic autolysis which differ due to the fluctuations in processing conditions (Al Bulushi et al., 2013). Lower pH values of dried products offer more enhancement in microbial inhibition and conse-quently, increase the shelf life of dried fish by preventing endogenous proteases activities (Majumdar et al., 2017). Dried fish under a pH range of 6.0-6.9 are considered to be of very good quality (Kakati, 2017). This implies that the loss of fish quality can result from the increase in pH. In literature, Puntius sophore, Setipinna phasa, Amblypharyngodon mola, Pseudeutropius atherinoi-des, Pseudambassis ranga and Corica soborna fish were dried under open-sun drying where the pH was 6.2-6.6

(Kakati.B, 2017). In another study, Noemacheilus beav-ani, Chanda ranga, Barilius tileo, Amphipnous cuchia, Anabas testudineus, Amblypharyngodon mola, Channa punctatus, Tor putitora, Puntius chola and Conta elon-gate fish were also dried under open-sun drying where most of these fish types were within the good-quality pH range and only four of them, viz. Amblypharyngodon mola, Channa punctatus, Tor putitora and Conta elon-gate, were outside the range (Hazarika et al., 2016).

The second characteristic is the water activity, which is the ratio of vapor pressure of water in the fish product to the vapor pressure of pure water at the same tempera-ture (Labuza, 1980). The water activity is considered as a criterion and a measure of microorganism develop-ment and toxin release of enzymatic and non-enzymatic browning development. It was found that water activ-ity greatly affects fresh fish endogenous microflora (Al Bulushi et al., 2013). There is a water activity limit for each food product below which the microorganism stop growing (Belessiotis and Delyannis, 2011). Most molds maintains their growth at a minimum water activity of 0.7 (Oparaku et al., 2017) and many bacteria sustains the growth at 0.9, while some biogenic amines, such as E. cloacae, need water activity of 0.48 (Al Bulushi et al., 2013). Majumdar et al. (2017) found that when moisture content of dried fish is less than 15%, no microbe can grow. This is because with the increase in water absorp-tion from the surronding, the water activity increases, causing an increase in microbial growth and reduction of shelf life of dried products. Further reduction in the water activity limits the spoilage and microbial growth.

The microbial quality of fish products is affected by the drying method and the proper handling anox-ic conditions (hygienic conditions) (Al Bulushi et al., 2013; Oparaku et al., 2017). Developing countries pro-duce low microbiological quality products which could be loaded with Staphylococcus aureus, Clostridium spp. and fecal Streptococcus spp. pathogens (Al Bu-lushi et al., 2013). To assess the microbiological qual-ity of fish products, Total Plate Count (TPC), which uses plate count agar, and Total Fungal Count (TFC),

Figure 8. Parabolic-dish solar collector (Solomon et al., 2016).

Figure 9. Exponential drying curve of tilapia fish (Kituu et al., 2010).

7Review Article


which uses potato dextrose agar by APHA, are used as microbial parameters. Immaculate et al. (2012) ob-served that TPC and TFC were high in open-sun dried sardine but absent in the sardine dried in a solar drier. They also reported the presence of E. coli pathogens in open-sun samples, however other pathogens such as Salmonella and vibrio were absent in both methods.

Total volatile base nitrogen (TVB-N) and trime-thylamine nitrogen (TMA-N) are signs (indicators) of spoilage which are correlatated strongly with the bacte-rial activity, endogenous enzymes and thus, the rate of spoilage (Kakati, 2017). They can be determined from trichloroacetic acid removal by micro diffusion from the sea product (fish). The recommended acceptability upper limit of these indicators for human consumption is 10-15 mg/100g for TMA-N and 35-40 mg/100g of TVB-N in dried fish (Immaculate et al., 2013). The qual-ity of dried fish with respect to TVB-N can be classified into very high quality at TVB-N value of 25 mg/100g or less, good quality at 26-30 mg/100g, limit of acceptabili-ty at 30-35 mg/100g and spoilt quality above 35 mg/100g (Jinadasa, 2014). However, in previous studies, the ac-ceptablity limit for TVB-N was considered to be 100 mg/100g (Connell, 1980), which is much higher than the recent classifications. Accordingly, Hossain et al. (2017) found that TMA-N and TVB-N values of open-sun dried Silver Pomfret and open-sun dried Perch fish were within the human acceptablity levels. The TMA-N and TVB-N values for Perch dried-fish were 8.21±0.12 and 46.97±1.00 mg/100g, respectively and for Silver Pom-fret, the values were 9.41±0.37 and 85.68±1.60 mg/100g, respectively. In another study, the TVB-N value were found to be acceptable for human consumption for mola fish dried in a solar tunnel dryer (15.68 mg/100g) and in open-sun (20.36 mg/100g) (Islam et al., 2012). Similarly, Sultana et al. (2008) repoted that in a solar tunnel dryer, the TVB-N values of dried ribbon fish, silver jew fish and Bombay duck were ranging from 15.46 to 19.21 mg/100g.

The last cause of fish spoilage is the autolytic chang-es (Oparaku et al., 2017) which denotes the biological and chemical changes occurring because of quali-ty losses at early stage of fresh fish (Ghaly et al., 2010; Oparaku et al., 2017). Major fish molecules undergo en-zymatic breakdown and as a result of autolysis of fish muscle proteins peptides and free amino acids can be produced which cause fish meat spoilage as a result of production of biogenic amines and microbial growth (Ghaly et al., 2010). For instance, open sun dried an-chovy fish was reported to contain biogenic amines that can cause scombroid-poisoning (Al Bulushi et al., 2013). The scombroid poisoning can also be caused by the increase in the level of histamine in the fish prod-uct so it is also called histamine fish poisoning (Hun-gerford, 2010). Bulushi et al. (2009) found that biogenic amines could be involved in the formation of nitrosa-mines at a high significant level when biogenic amines are present at a high concentration in fish products. It

was reported, in the same study, that impure salts en-hance the formation of nitrosamine whereas, pure salts (sodium chloride) inhibit nitrosamine formation.

ConclusionA review on solar drying of fish was done, several points can be concluded from this the study: (i) Open-sun draying is the most popular preservation technique of food products, (ii) The drawbacks of open-sun drying can be overcome by implementing other solar drying techniques such as greenhouse tunnel dryers, (iii) Solar dryers have shorter drying time and higher drying rate, and the physical properties of dried fish are enhanced, (iv) Many regression models were used for better under-standing of the drying processes, (v) Fish have very good nutritional value due to their high amount of proteins, lipids and ash contents, and (vi) Some characteristic, such as pH, water activity, microbial load, total vola-tile base nitrogen (TVB-N), trimethylamine nitrogen (TMA-N) and enzymatic autolysis analyzes, are used to assess the quality of dried fish to achieve longer shelf life.

ReferencesAbraha B, Samuel M, Mohammud A, Habte-Tsion HM,

Admassu H, Al-Hajj, NQM. (2017). A comparative study on quality of dried Anchovy (Stelophorus het-erolobus) using open sun rack and solar tent drying methods. Turkish Journal of Fisheries and Aquatic Sciences 17(6): 1107-1115. C-5:

Al-Jufaili S, Al-Jahwari OS. (2011). The Omani coastal traditional sardine fishery 1994-2007: A review. Jour-nal of Agricultural and Marine Sciences 16: 1-12.

Al Bulushi IM, Guizani N, Dykes GA. (2013). Effect of ambient storage on the microbial characteristics of traditional dried anchovies (Encrasicholina puncti-fer). African Journal of Microbiology Research 7(28): 3575-3581.

Al Rawahi ZNA, Munusami A, Kaithari DK. (2013). Per-formance analysis of solar drying system for marine product of Oman. International Journal of Students’ Research in Technology & Management 1(6): 610-613.

Anh NTN, Nhi NT, Van Hoa N. (2015). Effect of differ-ent drying methods on total lipid and fatty acid pro-files of dried Artemia francis-cana biomass. Can Tho University Journal of Science 1: 1-9.

Babiker AMO, Ismail IA, Osman OE, Salih ZA. (2014). Effect of solar drying using a natural convective so-lar drier on bacterial load and chemical composition of bayad (Bagrus bayad) fish flakes. International Journal of Multidisciplinary and Current research 2: 2321-3124.

Bala B, Janjai S. (2009). Solar drying of fruits, vegetables, spices, medicinal plants and fish: Developments and Potentials. International Solar Food Processing Con-



ference, Indore, India, January 14-16.Bala B, Mondol M. (2001). Experimental investigation

on solar drying of fish using solar tunnel dryer. Dry-ing Technology 19(2): 427-436.

Basunia MA, Al-Handali HH, Al-Balushi MI, Rahman MS, Mahgoub O. (2011). Drying of fish sardines in Oman using solar tunnel dryers. Journal of Agricul-tural Science and Technology B 1: 108-114.

Belessiotis V, Delyannis E. (2011). Solar drying. Solar Energy 85(8): 1665-1691.

Bellagha S, Amami E, Farhat A, Kechaou N. (2002). Dry-ing kinetics and characteristic drying curve of lightly salted sardine (Sardinella aurita). Drying Technology 20(7): 1527-1538.

Belwal R, Belwal S, Al Jabri O. (2015). The fisheries of Oman: A situation analysis. Marine Policy 61: 237-248.

Bulushi IA, Poole S, Deeth HC, Dykes GA. (2009). Bio-genic amines in fish: roles in intoxication, spoilage, and nitrosamine formation—a review. Critical Re-views in Food Science and Nutrition 49(4): 369-377.

Charters W, Macdonald R, Kaye D, Xiaoren S. (2017). Passive greenhouse type solar dryers and their devel-opment. International Energy Journal 11(2): 51-60.

Connell JJ. (1980). Control of fish quality II, Vol. 12, Fish-ing News Books Ltd.: 7-129.

Djendoubi N, Boudhrioua N, Bonazzi C, Kechaou N. (2009). Drying of sardine muscles: Experimental and mathematical investigations. Food and Bioproducts Processing 87(2): 115-123.

FAO. (2015). Fishery and Aquaculture Country Profiles. Oman. http://www.fao.org (accessed 7 March 2018).

Ghaly AE, Dave D, Budge S, Brooks M. (2010). Fish spoilage mechanisms and preservation techniques. American Journal of Applied Sciences 7(7): 859.

Hazarika P, Ullah N, Handique PJ. (2016). Assessment of biochemical quality of ten selected dried fish prod-ucts of North East India. Assessment 3(3): 183-186.

Hossain M, Jamil M, Mia M, Uddin M, Mansur M. (2017). Studies on the proximate composition, qual-ity and heavy metal concentration of two sun-dried marine fish (sun-dried Silver Pomfret and sun-dried Perch) of Cox’s Bazar District of Bangladesh. Jour-nal of Environmental Science and Natural Resources 10(1): 25-32.

Hubackova A, Kucerova I, Chrun R, Chaloupkova P, Ba-nout J. (2014). Development of solar drying model for selected Cambodian fish species. The Scientific World Journal 2014. vol. 2014.10.1155

Hungerford JM. (2010). Scombroid poisoning: a review. Toxicon 56(2): 231-243.

Immaculate J, Sinduja P, Jamila P. (2012). Biochemical and microbial qualities of Sardinella fimbriata sun dried in different methods. International Food Re-search Journal 19(4): 1699-1703.

Immaculate K, Sinduja P, Velammal A, Patterson J. (2013). Quality and shelf life status of salted and sun dried fishes of Tuticorin fishing villages in different seasons. International Food Research Journal 20(4): 1855-1863.

Islam M, Hossain M, Mian S. (2012). Nutritive value of dried and heat processed mola fish (Amblypharyn-godon mola) products. International Journal of Nat-ural Sciences 2(2): 43-48.

Islam MT, Ahmed S, Sultana MA, Tumpa A, Flowra FA. (2013). Nutritional and food quality assessment of dried fishes in Singra upazila under Natore district of Ban-gladesh. Trends in Fisheries Research 2(1): 2319-4758.

Jain D, Pathare PB. (2007). Study the drying kinetics of open sun drying of fish. Journal of Food Engineering 78(4): 1315-1319.

Jinadasa B. (2014). Determination of quality of ma-rine fishes based on total volatile base nitrogen test (TVB-N). Nature and Science 12(5): 106-111.

Jónsson Á, Finnbogadóttir GA, Þorkelsson G, Mag-nússon H, Reykdal Ó, Arason S. (2007). Dried fish as health food. Matis-Food Research. Innovation & Safety Report 5: 1-22.

Kakati BK, Sharma P, Goswami UC. (2017). Quality evaluation of dried fish products commerce in As-sam, india. International Journal of Advanced Bio-logical Research 7(3): 465-469.

Kituu GM, Shitanda D, Kanali C, Mailutha J, Njoroge C, Wainaina J, Silayo V. (2010). Thin layer drying model for simulating the drying of Tilapia fish (Oreochro-mis niloticus) in a solar tunnel dryer. Journal of Food Engineering 98(3): 325-331.

Labuza TP. (1980). The effect of water activity on reac-tion kinetics of food deterioration. Food Technology 34(4): 36-41.

Majumdar BC, Afrin F, Rasul M, Khan M, Shah A. (2017). Comparative study of physical, chemical, mi-crobiological and sensory aspects of some sun dried fishes in Bangladesh. Brazilian Journal of Biological Sciences 4(8): 323-331.

Mansur MA, Rahman S, Khan MNA, Reza MS, Uga S. (2013). Study on the quality and safety aspect of three sun-dried fish. African Journal of Agricultural Re-search 8(41): 5149-5155.

Martunis M. (2013). Performance of a forced-convec-tion greenhouse dryer for fish drying. Rona Teknik Pertanian 6(1): 426-430.

9Review Article


Mustapha MK, Ajibola TB, Salako AF, Ademola SK. (2014). Solar drying and organoleptic characteristics of two tropical African fish species using improved low-cost solar driers. Food Science & Nutrition 2(3): 244-250.

Ochieng OB, Oduor OPM, Nyale MM. (2015). Biochem-ical and nutritional quality of dried sardines using raised open solar rack dryers off Kenyan coast. Jour-nal of Food Resource Science 4(2): 33-42.

Oladipo I, Bankole S. (2013). Nutritional and microbial quality of fresh and dried Clarias gariepinus and Oreo-chromis niloticus. International Journal of Applied Microbiology and Biotechnology Research 1: 1-6.

Oparaku NF, Mgbenka BO, Eyo JE. (2017). Proximate and organoleptic characteristics of sun and solar dried fish. Animal Research International 7(2): 1169-1175.

Prakash O, Kumar A. (2014). Solar greenhouse drying: A review. Renewable and Sustainable Energy Reviews 29: 905-910.

Sahu TK, Jaiswal V, Singh AK. (2016). A review on solar drying techniques and solar greenhouse dryer. IOSR Journal of Mechanical and Civil Engineering 13: 31-37.

Sengar S, Khandetod Y, Mohod A. (2009). Low cost solar dryer for fish. African Journal of Environmental Sci-ence and Technology 3(9).

Siddique M, Mojumder P, Zamal H. (2012). Proximate composition of three commercially available marine dry fishes (Harpodon nehereus, Johnius dussumieri and Lepturacanthus savala). American Journal of Food Technology 7(7): 429-436.

Singh P, Shrivastava V, Kumar A. (2017). Recent develop-ments in greenhouse solar drying: A review. Renew-able and Sustainable Energy Reviews 82: 3250-3262.

Solomon S, Okomoda V, Egwumah A. (2016). Design and performance of a pioneering solar collector us-ing parabolic dish for fish processing. Jordan Journal of Agricultural Sciences 12(2): 581-590.

Sontakke MS, Salve SP. (2015). Solar drying technolo-gies: A review. International Journal of Engineering Science 4: 29-35.

Sultana S, Hossain M, Shikha F, Islam M, Kamal M. (2008). Quality assessment of rotating and solar tun-nel dried marine fish product. Bangladesh Journal of Fisheries Research 12(1): 121-128.

Tiwari G, Das T, Chen C, Barnwal P. (2009). Energy and exergy analyses of greenhouse fish drying. Interna-tional journal of exergy 6(5): 620-636.

Toujani M, Hassini L, Azzouz S, Belghith A. (2013). Ex-perimental study and mathematical modeling of sil-verside fish convective drying. Journal of Food Pro-cessing and Preservation 37(5): 930-938.

Walters SA, Jha AK. (2016). Sustaining chili pepper production in Afghanistan through better irrigation practices and management. Agriculture 6(4): 62-71.

Review ARticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 10–23DOI: 10.24200/jams.vol26iss2pp10-23Received 19 Dec 2020Accepted 21 Jan 2021

GIS and remote sensing techniques in Controlled Environment Agriculture: A review

Asma M. Al-Maimani 1, Abdulrahim M. Al-Ismaili 2,*, Yassine Charabi 2,3

Abdulrahim M. Al-Ismaili 2,*( ) [email protected]; [email protected], 1Department of Soils, Water and Agricultural En-gineering, Sultan Qaboos University, Sultanate of Oman, 2Department of Geography, Sultan Qaboos University, Sultanate of Oman, Email: [email protected], 3 Center for Environmental Studies and Research, Sultan Qaboos University, Sultanate of Oman

Introduction

In arid and semi-arid regions, high temperatures and water scarcity are the two major constraints for ag-riculture development and sustainability (Al-Ismai-

li and Jayasuriya, 2016). Greenhouses are considered a sustainable option for crop production in harsh climat-ic conditions (Helmy et al., 2013; Kumar et al., 2009) through providing favourable microclimate for plants, extending the cropping season and achieving year-round production. Controlled Environment Agriculture (CEA) term refers to a group of agricultural systems including screenhouses, greenhouses, shade-houses and aquapon-ics (Al-Ismaili et al., 2017). The total area under plastic greenhouse covers has rapidly grown to reach more than 500,000 ha around the world (Agüera and Liu, 2009).

تطبيقات نظم المعلومات الجغرافية و الإستشعار عن بعد في الزراعة المحمية: مراجعةأسماء م. الميمني1، عبدالرحيم م. الإسماعيلي 2،*، ياسين شرعبي 2،3

Abstract. Geographic Information System (GIS) and Remote Sensing (RS) are useful tools in environmental mon-itoring, evaluation and analysis for various sectors including agriculture. This paper reviews the applications of GIS, RS and the integration of both techniques in the agricultural field, in general, and Controlled Environment Agriculture (CEA), in particular. More emphasis is given to their applications in arid areas and Oman is taken as a case study. GIS techniques have been used in the mapping of soil and water quality, spatial assessment for water quantity stress, land suitability, pest and disease distribution of crops as well as delineating and generating database management systems (DBMS) for protected cultivations. In Oman, GIS was only employed to analyse the spatio-temporal dynamics of land use changes as affected by external factors and greenhouses as an example in northern part. RS was also utilised to map the changes in land cover and their uses, detect and map soil salinity, and monitor agricultural droughts. In CEA, RS was utilised for mapping, detection and classification of greenhouses through aerial images and satellites. In Oman, negligible study was documented on the use of RS techniques in the CEA field. The integration of both techniques has proven its capability in mapping, evaluating and managing natural resources and greenhouse distribution and generat-ing database management system in agriculture and CEA fields. Sophisticated geostatistical analysis models based on Multi-criteria analysis using Fuzzy-logic and Analytic Hierarchy Process could be a good platform for trade-off analysis for land suitability analysis and optimal location of CEA in challenging agriculture like Oman.

Keywords: GIS; Remote sensing; greenhouse; database management system

الملخص: تعد تقنيات نظم المعلومات الجغرافية )GIS( والإستشعار عن بعد )RS( من الأدوات المفيدة في المراقبة البيئية والتقييم والتحليل لمختلف القطاعــات بمــا في ذلــك الزراعــة. تســتعرض هــذه الورقــة تطبيقــات نظــم المعلومــات الجغرافيــة و الإستشــعار عــن بعــد ودمــج كلتــا التقنيتــين في المجــال الزراعــي بشــكل عام والزراعة المحمية )CEA( على وجه الخصوص. تم التركيز بشــكل أكبر على تطبيقاتهم في المناطق القاحلة ويتم أخذ عمان كدراســة حالة. تم اســتخدام نظــم المعلومــات الجغرافيــة في رســم خرائــط التربــة وجــودة الميــاه ، والتقييــم المــكاني لإجهــاد كميــة الميــاه ، وملاءمــة الأراضــي ، وتوزيــع الآفــات والأمــراض للمحاصيــل وكذلــك تحديــد وإنشــاء نظــام إدارة قواعــد البيــانات )DBMS( للزراعــة المحميــة. في عمــان، تم اســتخدام نظــم المعلومــات الجغرافيــة فقــط لتحليــل الديناميكيــات المكانيــة والزمانيــة لتغــرات اســتخدام الأراضــي والبيــوت المحميــة كمثــال في الجــزء الشــمالي. كمــا تم اســتخدام الإستشــعار عــن بعــد لرســم خريطــة التغــرات في الغطــاء الأرضــي واســتخداماته ، واكتشــاف ملوحــة التربــة ورســم خرائــط لهــا ، ورصــد حــالات الجفــاف الزراعــي. في الزراعــة المحميــة، تم اســتخدام الإستشــعار عــن بعــد لرســم خرائــط واكتشــاف وتصنيــف الزراعــة المحميــة مــن خــلال الصــور الجويــة والأقمــار الصناعيــة. في عمــان ، لم يتــم توثيــق أي دراســة واحــدة حــول اســتخدام تقنيــات الاستشــعارعن بعــد في مجــال الزراعــة المحميــة . أثبــت تكامــل كلتــا التقنيتــين قدرتــه علــى رســم خرائــط وتقييــم وإدارة المــوارد الطبيعيــة وتوزيــع الزراعــة المحميــة وإنشــاء نظــام إدارة قواعــد البيــانات في مجــالات الزراعــة والزراعــة المحميــة. يمكــن أن تكــون نمــاذج التحليــل الإحصائــي المتطــورة القائمــة علــى التحليــل متعــدد المعايــر باســتخدام عمليــة التسلســل الهرمــي التحليلــي والمنطــق الضبــابي منصــة جيــدة لتحليــل

المقايضــة لتحليــل ملاءمــة الأرض والموقــع الأمثــل للزراعــة المحميــة في مــكان تتواجــد بــه التحــديات الزراعيــة مثــل عمــان.الكلمات المفتاحية: نظم المعلومات الجغرافية، الإستشعار عن بعد، البيت المحمي، نظام ادارة قواعد البيانات.

11Review Article

Al-Maimani, Al-Ismaili and Charabi

However, this rapid growth of CEA should be monitored and mapped for better understanding and planning for the development and management of natural resources, which could be achieved using Geographic Information System (GIS) and RS (Remote Sensing) techniques.

GIS is a professional computer system that manipu-lates spatial and non-spatial data to present them in a simple illustrative manner on the map (Soomro, 2015). It links the tabular (database) information with their re-spective locational (Spatial) coordinates for better visu-alization. In addition, it has a unique capacity with spatial data in terms of collection, storage, management, con-version, analysis, modelling and display as it performs these functions in a very organised way (Davis, 1996). GIS tools and techniques are very helpful and beneficial in several fields including geography, computer science, environmental science, agriculture, forest, food, enter-tainment, banking, health services and manufacturing (Soomro, 2015).

RS is an art of acquiring information about an object or event on earth’s surface, ocean or atmosphere using remote sensors (e.g. special cameras, radars and digital scanners) (Bhatta, 2011; Wang and Weng, 2013). Build-ings, soils, water and vegetation are examples of sens-ing/observing objects at distant (remote) places which are investigated by scientists (Campbell and Wynne, 2011). RS has several distinguished advantages, such as observation of a broad area at one time (spatial) as well as observing the areas for long periods (temporal). Another advantage is the possibility to collect data from places that are geographically or politically inaccessible without any distortions (Bhatta, 2011; Wang and Weng, 2013). The user can benefit from the results of RS in a variety of applications such as ecosystems, natural land-scapes, hydrology, urban planning and agriculture.

Usery et al. (1995) mentioned that advanced technol-ogies such as GIS and RS are used to collect and han-dle spatially referenced data, perform spatial analysis and decision-making for factors related to geography in order to solve problems in planning and management (Parthasarathy, 2010; Soomro, 2015). Using interrela-tionships between geography, location and people in GIS makes it possible to take decisions aiming to im-prove the living on earth (Soomro, 2015). RS and GIS are very beneficial techniques to store, operate and quanti-tatively evaluate the soil sustainability and capability for various practices (Saleh et al., 2015).

Applications of GIS in AgricultureIn agricultural field, GIS can be used for a small scale ar-eas like a single farm to a large scale areas like the globe (Wilson, 1999). The basic of success and profitability of any farm is to balance between inputs and outputs (Parthasarathy, 2010). GIS tools are beneficial to own-ers of agricultural farms by visualising the environmen-tal parameters and workflows within their farms. These tools enable them to handle the agricultural spatial data,

which are collected through mobile devices, in investi-gating their farm conditions and evaluating their effects on the wellbeing of their farms (Soomro, 2015).

Jayasuriya et al. (2014) presented the use of GIS in mapping the levels of soil compaction by heavy-load ve-hicles and the moisture content distribution of Rhodes grass to reach the best tillage and irrigation management. Results showed an inverse relationship between Rhodes grass growth and soil compaction levels. Sadat-Noori et al. (2014) worked on GIS and Water Quality Index (WQI) to assess and examine the spatial distribution of ground-water quality of Saveh-Nobaran aquifer in Iran. The major cations and anions (Ca, Mg, Na, HCO3, SO4, Cl, and TDS), EC, pH and hardness of ground-wa-ter samples were analysed and documented. Using GIS, maps of the aforementioned parameters were created using Kriging method. Figure 1 shows the WQI map of the selected aquifer. For the WQI assessment, they re-ported that 65% of samples were under three categories of drinking water qualities; very poor, poor and unsuit-able. The amalgamation of GIS and WQI method was very effective and can help for better decision making. In another study, knowledge-base model was built in GIS environment to assess the supplementary irrigation in rain-fed agricultural watersheds in India (Reshmidevi et al., 2010). The model used the empirical information of land suitability for crops, irrigation practices and the hy-drological models to improve the supplementary irriga-tion in the watershed. It was found that this model could be implemented to estimate the irrigation requirements based on rainfall conditions.

Land suitability analysis is necessary for agricultural planning and sustainability. GIS can also aid farmers to determine the preference areas for crop cultivation as well as to manage pests and increase the profit during harvesting (Soomro, 2015). Bhagat et al. (2009) used GIS to analyse land suitability for cereal production in Himachal Pradesh, India. The geo-referenced data (cli-mate, elevation, soil and land cover) with potential pro-duction were fed to GIS. The resulted maps delineated suitable lands for growing cereals in the study area. For agricultural sustainability, GIS showed that small ag-ricultural lands can be merged efficiently together. In Turkey, a study of land suitability for fruit growing us-ing GIS was done by Yarilgac (2012). Similarly, Chiranjit and Kishore (2016) reviewed GIS applications on land suitability evaluation for agricultural crop selection us-ing different approaches such as Fuzzy logic, Multi-Cri-teria Evaluation (MCE) and Analytic Hierarchy Process (AHP) within GIS environment. The MCE approach is one of the land assessment tools used for selecting the proper factors from a large number of factors and thus, giving the best solutions and finding alternatives for de-cision making (Gastli and Charabi, 2010; Hedia and Elk-awy, 2016; Olaniyi et al., 2015). The combination of MCE within GIS environment gives a strong support for de-cision makers and researches. Hedia and Elkawy (2016)



studied the assessment of land suitability for agricultural uses in Egypt by means of MCE within GIS. (Chivasa et al., 2019) evaluated the land suitability for maize pro-duction (Zea mays L.) with aid of GIS, AHP and MCE in Zimbabwe. Different thematic maps such as rainfall, soil type and slope were ovleraid in GIS environment. Re-sults found that there was a significant posituve correla-tion between maize yield and classes of land suitability (R2= 0.63-0.85). This method was effective and recom-mended to use it as a tool for decision making for maize placement in the country. Many researches have used the integration of AHP with GIS to assess land suitabili-ty (Mishra et al., 2015; Romano et al., 2015; Uyan, 2013)

Manyong et al. (2008) described the benefits of GIS techniques in disease and pest control particularly in predicting, monitoring and managing the spread of Xan-thomonas wilt (BXW) in banana (Musa spp.). Similarly, a study on the spatial analysis of Lettuce Downy Mildew were conducted in USA (Wu et al., 2001). In another application, GIS was employed to map the agricultural plastic waste in Greece (Hiskakis et al., 2007).

In Oman, the use of GIS in agricultural-related ap-plications was recently introduced. To date, several studies were conducted to measure the soil and wa-ter qualities using GIS. Jamrah et al. (2008) evaluated ground-water vulnerability using DRASTIC method in ArcGIS. DRASTIC stands for seven parameters; D: depth to groundwater, R: net recharge, A: aquifer media, C: hydraulic conductivity of the aquifer, S: soil media, I: impact of vadose zone and T: topography or slope. This study covered the period between 1994 and 2004 for Barka, North Al-Batinah Governorate. A number of seven DRASTIC layers were generated and the result-ed maps revealed that the northern and central parts of Baraka were highly affected by contaminants compared to the southern part (Fig. 2).

Al-Barwani and Helmi (2006) studied seawater intru-sion for the coastal aquifers between As’ Seeb and As’ Suwaiq cities for the years 1984-2005 (Figure 3). Using GIS, geographical locations of wells and their water salinity (EC) values were created on the map. The EC data were recorded from regular field measurements undertaken by the Ministry of Regional Municipalities and Water Resources. The salinity zones were delineat-ed for all areas between the two cities. Results showed a 7% decrease in land with suitable water for agricultural purposes between 2000 and 2005. Also, they reported that seawater intrusion in Barka city has moved 12 km inland over the same period. GIS techniques have been used also for spatial assessment of water quantity stress across the Sultanate of Oman (Al-Awadhi and Mansour, 2015). Results presented significant variations in water quantity stress across the governorates. Also, seasonal variations in water supply and drought severity were the most important predicators for water quantity risk. In another study, Behrendt et al. (2015) investigated the distribution and diversity of banana (Musa spp.) in Wadi Tiwi, Oman. The spatial distribution of different banana cultivars is depicted in Figure 4.

Al-Habsi (2015) studied GIS-linked Computer Simu-lation Model for Wheat seed emergence predication in Oman. The study showed the best locations for wheat production in Oman through linking Simulation Model with Numerical Weather Predication Model (NWPM) in GIS environment. The model was used to predict time of emergence based on soil temperature, water potential and planting depth (Figure 5). In renewable energy sector, a study was done to investigate the best locations to build large Photovoltaic system (PV) using MCA (Multi-cri-teria analysis) in GIS environment in Al-Batinah farms, Oman (Gastli and Charabi, 2010). This will be benefi-cial to exploit the solar energy in Oman and implement large PV plants. It can be source of energy inside farms.

Figure 1. The spatial distribution of Water Quality Index (WQI) in Saveh-Nobaran aquifer in Iran (Sadat-Noori et al. 2014).

13Review Article


Applications of GIS in CEA Very few studies were reported on the applications of GIS in the field of Controlled Environment Agriculture (CEA). Matsuoka et al. (2015) studied the use of GIS and developed Monte Carlo method to simulate the collec-tion of catch crops (e.g. dent corn) from greenhouses to collection stations in Kochi Prefecture in Japan. The study also estimated the yield production and carbon emissions from the transportation of catch crops. Using the results from the above investigations, potential ways to reduce groundwater contamination and conserve agricultural resources were explored. Results revealed that the total collected fresh weight of catch crops was 67,900 tons and 70% of production came from central plains of the study area where the cluster of greenhouses was more. GIS maps clearly illustrated that eggplant was the dominant crop in the eastern part and cucumber was the dominant crop in the western part (Figure 6).

The combination of the developed method and GIS were easy and multilateral in solving collection and transpor-tation problems. Crifasi et al. (2002) reported the use of GIS as a Data Base Management System (DBMS) for protected cultivations in Marsala town, western Sicily, Italy. The study covered an area of about 3,588 ha having 2,607 greenhouses (Figure 7). The distribution of green-houses and their floor area were recorded. The study emphasised the capability of GIS to precisely determine greenhouse sizes and to handle, organise and administer large amounts of data in a quick and simple manner.

In Oman, there was only one study on the use of GIS in CEA. Deadman et al. (2016) studied the spatio-tem-poral dynamics of land use changes affected by external pressures and considered greenhouses as an example in northern Oman. This study considered GPS coordinates of greenhouses for five years; 2001, 2002, 2003, 2004 and 2009. Results revealed that greenhouse density was

Figure 2. DRASTIC values for Barka in 2004 (Jamrah et al.. 2008).

Figure 3. Salinity Zones in As’ Seeb (Al-Barwani and Helmi 2006).

Figure 4. Geographical Locations of Musa spp. in the study area (Behrendt et al., 2015).



increasing with increasing distance from the coastline (i.e. decreasing groundwater salinity). Barka city was the most affected by the increase in groundwater salinity and so, 57.8% of all abandoned farms in Al-Batinah gov-ernorates were in Barka (Figure 8). New and large farms were developed away from high levels of groundwater sa-linity and away from urbanised areas. Because this study did not cover the whole country, a more comprehensive study is necessary to investigate the factors affecting the spatio-temporal distribution of greenhouses in Oman.

Applications of RS in agricultureRemote sensing (RS) is progressively used in a variety of agricultural applications such as soil salinity which is a severe environmental problem particularly in arid and

semi-arid regions (Sahoo et al., 2015). RS techniques are professional, more informative and faster than tradi-tional methods used in detecting soil salinity (Al-Mulla, 2010; Allbed and Kumar, 2013). Additionally, they have a capability in delineation, mapping and assessment of this problem. Alavipanah and Goossens (2001) studied the relationship between soil salinity and data obtained from Landsat TM and MSS. In another study, Allbed et al. (2014) described the use of IKONOS satellite imager-ies to assess the soil salinity using vegetation and soil sa-linity indices in a region dominated with date palm trees in Al-Hassa Oasis, Saudi Arabia. Three sites were select-ed within the study area and field measurements were under taken. Remotely sensed data were used to extract the Soil-Adjusted Vegetation Index (SAVI) and 12 soil

Figure 5. A raster map shows the time (days) of emer-gence at 25 mm planting depth (Al-Habsi, 2015).

Figure 6. The cultivated area in proportions with four produced catch crops (Matsuoka et al., 2015).

Figure 7. Distribution of greenhouses by area (m2) (Cri-fasi et al., 2002).

Figure 8. : Barka map displays levels of groundwater salinity related to active, abandonment ground cover and urban area (Deadman et al., 2016).

15Review Article


salinity broadband indices. Results showed that soils of Al-Hassa Oasis were highly saline (EC >16 dS/m). This salinity level was indicated with a higher spectral re-sponse in the visible and NIR range compared to the oth-er salinity levels (Figure 9). However, other levels of soil salinity differed within the three sites due to human-in-duced or environmental factors such as: poor quality of irrigation water, unbalanced agricultural practices and poor drainage. The most beneficial indices for assessing

soil salinity in areas dominated by date palm were SAVI, NDSI and SI-T that were extracted from the IKONOS.

A similar study was done using IKONOS satellite images and Landsat Multi Spectral Scanner (MSS) to detect crop reflectance, soil salinity levels and salinity impact on crop yield (Elhaddad and Garcia 2006). In another study, Alhammadi and Glenn (2008) studied SAVI to detect the health of date palms and greenness change of vegetation in the eastern part of United Arab Emaciates. SAVI was examined from Landsat Themat-ic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images for three different sites: Fujairah, Hatta and Kalba in 1987 and 2000. Additionally, field measure-ments were taken for ground-truthing. Results revealed that in Hatta, there was a reduction in vegetation green-ness and healthy conditions yet the overall agricultur-al land area increased (Fig. 10). Salt-affected soils were identified using the SAVI values which decease with the rise in soil salinity. The study confirmed that a special attention should be given in monitoring and managing soil salinity problem to keep date palm trees produc-tive. RS is also used to detect vegetative covers in for-est vegetation using Vegetation Indices, VI (Jinguo and Wei, 2004). Dawbin and Evans (1988) reported some RS techniques for digital crop classification using Landsat data for Australian environment. For arid and humid re-gions, Rhee et al. (2010) proposed a new drought index called Scaled Drought Condition Index (SDCI) which is

based on temperature data for land surface, Normalized Difference Vegetation index (NDVI) and precipitation data from selected satellites for monitoring agricultur-al drought. On the other hand, Tenkorang and Lowen-berg-DeBoer (2008) reviewed the potential of using RS to improve farm profits such as optimizing the use of fertilizers and pesticides.

In Oman, Al-Mulla (2010) highlighted the use of RS in mapping soil salinity. He mentioned that salinity is a dy-

namic process which affected large areas in Oman. The vegetation abundance in the vicinity of Sultan Qaboos University in Muscat was studied using RS by Rajendran et al. (2016). On the other hand, Harris (2003) evaluat-ed agricultural land changes using Landsat MSS in 1978 and Landsat Enhanced Thematic Mapper (ETM) data in 2001 (Fig. 11). The study was conducted in Khaburah and Sohar cities on the coastal line of Al-Batinah. Field work was done to support earth observation data for 1979 and 2001. The change in agricultural lands was es-timated from environmental change maps that were de-rived from supervised and unsupervised classifications. The study concluded that the change in agricultural ar-eas was clear and considerable in the study period due to the growing income since 1970, i.e. fast urbanization.

Applications of RS in the CEAIn recent years, rapid growth of plastic greenhouses took place and the total land area under plastic greenhouses reached more than 500,000 ha worldwide (Agüera and Liu, 2009). Mapping and detection of greenhouses by means of RS could be a challenging task (Aguilar et al., 2014; Aguilar et al., 2015; Tarantino and Figorito, 2012). Aguilar et al. (2014) studied the classification of green-houses in Cuevas del Almanzora of Almeria, Spain, us-ing Object-Based Image Analysis (OBIA) for two high resolution stereo images of GeoEye-1 (GE1) and World-View-2 (WV2), (Figure 12). In the eastern part of Alme-

Figure 9. Soil spectral reflectance of Al-Hassa Oasis (Allbed et al., 2014).



ria, Spain, another mapping of plastic greenhouses was produced using texture analysis to improve per-pixel classification from other high resolution satellite im-ages which were QuickBird and IKONOS (Figure 13), (Agüera et al., 2008). Similarly, mapping of plastic cov-ered vineyard using true colour aerial data (Very High Spatial Resolution) was examined in the Apulia Region (Italy) (Tarantino and Figorito, 2012). The object-based classification method from aforementioned data were developed for testing eight locations in the study area. The overall accuracy of the method used for mapping areas was about 90%. In another study, Yang et al. (2017)

developed a new spectral index for mapping plastic greenhouses through medium spatial resolution satel-lite images in China. RS approaches were also utilized to study the spatial and temporal patterns of greenhouses and the factors driving these changes between 2000 and 2015 in Shouguang City, China (Yu et al., 2017).

Arcidiacono and Porto (2010a) investigated the clas-sification of crop-shelter using RGB aerial images. Sim-ilar study was done for the classification of crop shelter through processing of digital images in Italy (Arcidiacono and Porto, 2007). Aguilar et al. (2015) identified, for the first time, the horticultural crops that were grown under

Figure 10. False colour composite images (red, layer 4; green, layer 3; and blue, layer 2) for Hatta area for 1987 (top) and 2000 (bottom). Red colour represents vegetation (Alhammadi and Glenn, 2008).

Figure 11. Supervised Classifications in Sohar, (a) Landsat MSS in 1978 (b) Landsat ETM in 2000 (Harris, 2003).

17Review Article


plastic greenhouses of Almeria in Spain. Eight images were acquired between May and November 2013 from Landsat 8 Operational Land Imager (OLI) where OBIA and decision tree (DT) classifier applied to these images. In addition, a single WV-2 multi-temporal satellite im-agery was applied as a data source. Both types of images were utilized to derive spectral information, vegetation indices (VI) and textural features which were already be-

ing segmented to detect the most popular crops culti-vated in greenhouses of the study area (pepper, tomato, aubergine and cucumber). The overall classification ac-curacy was 81.3% for the whole series of Landsat 8 OLI

imageries. In another study, the accuracy of RS reached 95.9% in mapping greenhouses with Landsat TM im-agery in Qingzhou, China (Geng-Xing et al., 2004).

In Oman, the number of greenhouses increased by almost 40% annually between 2001 and 2005 (Al-Ki-yumi, 2009; Al-Sadi et al., 2007). However, no studies have been done in utilizing RS techniques for identify-ing and mapping greenhouses or studying the temporal distribution of CEA and the external factors affecting such distribution such as groundwater salinity in the Sultanate. Therefore, a need for such a study is essen-tial to update the status of CEA and all relevant aspects.

Applications of GIS and RS in agricultureRS and GIS data are widely utilized in mapping and managing natural resources and building environmen-tal models (Sajjad et al., 2015). For instance, Saleh et al. (2015) evaluated land resources (e.g. soil quality and wa-ter availability) for potential agricultural practices using RS and GIS techinques in El-Galaba basin, Eygpt. Simi-larly, another study used RS and GIS in the assessment of land cover and soil quality (Obade and Lal, 2013). Shalaby and Tateishi (2007) investigated land cover and land use changes in Egypt. RS and GIS were also used to detect changes of forest cover in Tehsil Barawal, Pakistan for 2000 and 2012 (Figure 14) (Sajjad et al., 2015). In an-other study, Jha et al. (2007) conducted a review for using RS and GIS tools for the development and management

of groundwater. Jiménez-Bello et al. (2012) used RS and GIS tools for irrigation management of citrus trees in Southwest Europe. Another study presented the use of Landsat method (which combines GIS and RS) to esti-

Figure 12. Nine classes assigned for all objects based on aerial PNOA (Spanish Programme of Aerial Ortho-pho-tography) ortho-image (Aguilar et al., 2014).

Figure 13. Study area from two different Satellites: QuickBird (top) and IKONOS (bottom) (Agüera et al., 2008).



mate the exposure of agricultural pesticides on human health in USA (VoPham et al., 2015; Ward et al., 2000).

In Oman, GIS and RS techniques have been used to map the temporal changes of soil salinity for 1991 and 2005 in Al-Rumais area, Barka (Al-Mulla and Al-Adawi, 2009). In this study, two satellite imageries were re-pro-jected and geo-referenced and thus, soils affected with salinity were identified and classified. Results showed a high potential of utilizing GIS and RS techniques due to their accuracy, labour saving and cost effectiveness. Al-Rawas and Valeo (2011) investigated quality of ground-water and pollution sources in As’ Seeb area by means of RS, GIS techniques and spatial data analysis. In this

study, 335 water samples were collected from the study area. Levels of Nitrate (NO3), acidity (pH) and Electrical Conductivity (EC) were analysed and compared to the Omani Standards (MOCI, 2006) and WHO standards for drinking water. Results revealed that all water wells were unsuitable for drinking (beyond Omani standards) because EC values were greater than 4000 MS/cm in farms close to sea because of over pumping (Figure 15) yet, pH values were within Standards (6.5 – 8). The percentage of samples that exceeded the allowable con-centration levels of NO3 (>50 mg/L) was 23.28%. These levels were originated from populated areas and near to the drainage system which is affected by landfill loca-tion of As’ Seeb area. The presence of septic tanks and proximity to the landfill were the two major reasons for the increase of NO3. The study is beneficial in providing an overview of the spatial assessment of groundwater quality in As’ Seeb city. In another study, GIS and RS techniques were utilized to identify the vegetative cover using satellite imageries in Dhofar, Oman (Al-Awadhi et al., 2011). Three approaches were studied: NDVI, su-pervised classification and unsupervised classification. Results reaveled that large variations in calcuating the total areas of vegeation among the three approaches. Yet, NDVI was the best approach compared to other approaches since it was closer to visual comparsions.

Applications of GIS and RS in CEARS satellites have the capability of recording environ-mental information at a fast rate and economical scale for various purposes. GIS can combine these data with other spatial data (e.g. maps) and non-spatial data (e.g. text or tables) to simplify new forms of analyses (Ehlers,

Figure 14. Classified images for the two years: 2000 (above) and 2012 (below) (Sajjad et al., 2015).

Figure 15. Map of interpolated EC values (MS/cm) (Al-Rawas and Valeo, 2012).

19Review Article


1996). The integration of GIS and RS becomes very help-ful (Merchant and Narumalani, 2009). Sönmez and Mus-tafa (2006) conducted a study to generate a new database system for greenhouses using GIS and RS techniques of Antalya, Turkey, as an effort to determine and reg-ister the agricultural resources for the European Union Common Agricultural Policy (EUCAP). Pan-Sharpened IKONOS satellite image was used to determine the type of greenhouses (e.g. glass or plastic greenhouses). With-in GIS environment, the Database Management system (DBMS) was created for each greenhouse in the region including position, number, area and type of green-houses, information about owner, production input and amount of production (Figure 16). Results concluded that the accuracy of using GIS and RS technologies was high (97% for plastic greenhouses and 96.1% for glass greenhouses). Also, DBMS provided a reliable source for statistical data. Both technologies were capable in creat-ing databases which were reliable with European Union and other international standards.

In another study, GIS and RS techniques were utilized to determine the negative environmental effects on air, water cycle and agricultural soil under plastic protected cultivation and also to determine the aesthetic distortion in rural areas along the coast of Jonian Sea, Southern It-aly (Picuno et al., 2011), (Figure 17). The analysis was carried on multi-temporal Landsat TM images with su-pervised classification, image processing, GIS tools and

vectorialization. Results revealed a method of auto-de-tection for the plastic covers used in CEA. Furthermore, a concept of “threshold” limit of the quantity of plastic covers was suggested. The possible adjustment of colour and texture of the cladding material was also evaluated. Similar study was done for the environmental effects of crop-shelter by utilizing landscape indicators, RS imag-eries and GIS analysis (Arcidiacono and Porto, 2010c). Moreover, Arcidiacono and Porto (2010b) built a model

Figure 16. An example of DBMS for a greenhouse, (Sönmez and Mustafa, 2006).

Figure 17. A view of plastic film that covered the agricul-tural land (Picuno et al., 2011).



for managing the spatial development of crop-shelter using RS imageries, GIS and spatial indicators in Italy.

In Oman, the Agricultural Census is taking place ev-ery 10 years to provide updated statistical data on the ag-ricultural sector components (MAF, 2013). Although the number of greenhouses keeps on growing at rapid rates, there has been no single study that integrated the use of GIS and RS in CEA. So, there is a need for similar stud-ies integrating the use of RS and GIS in order to acquire a consistent statistical data about CEA and all relevant aspects. Consequently, such information may help to in-crease the income of farmers and food security of Oman.

ConclusionIn this review, an attempt has been done to highlight the previous inventory work done by scientists and research-ers. GIS is one of the powerful techniques in capturing, storing, retrieval, displaying and analysing spatial data. It has a capability of mapping, solving problems, planning, managing, and taking decisions and predications. GIS was utilized in many studies within agricultural fields. In Oman, it has been used only to study the greenhouse distribution and the spatio-temporal dynamics of land use changes affected by external pressures in northern Oman. RS is another useful technique utilized progres-sively in a variety of agricultural applications around the world. Regarding the CEA in Oman, no studies have been done in utilizing RS techniques for identifying and mapping greenhouses or studying the temporal distribu-tion of CEA and the external factors affecting such distri-bution such as groundwater salinity. The integration of GIS and RS is very helpful and their data are widely uti-lised in mapping, managing natural resources and build-ing environmental models. In CEA, satellite imageries and GIS tools were used for generating DBMS, map-ping and identifying greenhouses. In Oman, there has been no single study that applied the integration of both techniques. So, a need for a similar study is necessary to acquire a consistent statistical data about CEA and all relevant aspects. This could probably help increas-ing the income of farmers and food security of Oman. Multi-criteria Evaluation in GIS environment could pro-vide a trade-off analysis for CEA land planning with high ecosystem service value. This platform of trade-off anal-ysis for land suitability analysis could generate differ-ent scenarios using spatial and economic information. This approach could be a robust tool for government to achieve agricultural sustainability and adopting effective pathways for better management for natural resources.

Acknowledgementsincere thanks to The Research Council, Oman for fund-ing this work through an open grant research fund (proj-ect code: RC/AGR/SWAE/15/01).

FundingThis work received a research fund from The Research Council, Oman through project number RC/AGR/SWAE/15/01.

ReferencesAgüera F, Aguilar FJ, Aguilar MA. (2008). Using texture

analysis to improve per-pixel classification of very high resolution images for mapping plastic green-houses. ISPRS Journal of Photogrammetry and Re-mote Sensing 63(6): 635-646.

Agüera F, Liu JG. (2009). Automatic greenhouse delinea-tion from quickbird and ikonos satellite images. Com-puters and Electronics in Agriculture 66(2): 191-200.

Aguilar MA, Bianconi F, Aguilar FJ, Fernández I. (2014). Object-based greenhouse classification from geo-eye-1 and worldview-2 stereo imagery. Remote Sens-ing 6(5): 3554-3582.

Aguilar MA, Vallario A, Aguilar FJ, Lorca AG, Parente C. (2015). Object-based greenhouse horticultural crop identification from multi-temporal satellite im-agery: A case study in almeria, spain. Remote Sensing 7(6):7378-7401.

Al-Awadhi T, Al-Shukili A, Al-Amri Q. (2011). The use of remote sensing and geographical information systems to identify vegetation: The case of dhofar governorate (oman). http://www.isprs org/proceed-ings/2011 (accessed on September 10, 2011)

Al-Awadhi T, Mansour S. (2015). Spatial assessment of water quantity stress in sultanate of oman provinc-es: A gis based analysis of water resources variabili-ty. Journal of Geographic Information System 7(06): 565-579.

Al-Barwani A, Helmi T. 2006. Seawater intrusion in a coastal aquifer: A case study for the area between seeb and suwaiq in the sultanate of oman. Agricul-tural and Mar Sciences 11: 55-69.

Al-Habsi R. (2015). Gis-linked computer stimulation model for wheat seed emergence prediction in oman. [Sultanate of Oman]: Sultan Qaboos University, Oman.

Al-Ismaili AM, Al-Mezeini NK, Jayasuriya PH. (2017). Controlled environment agriculture in oman: Facts and mechanization potentials. Agricultural Mechani-zation in Asia. Africa and Latin America 48(2): 45-51.

Al-Ismaili AM, Jayasuriya H. (2016). Seawater green-house in oman: A sustainable technique for fresh-water conservation and production. Renewable and Sustainable Energy Reviews 54: 653-664.

Al-Kiyumi KSM. (2009). Greenhouse cucumber pro-duction systems in oman: A study on the effects of cultivation practices on crop diseases and crop yields. University of Reading Publication, UK.

21Review Article


Al-Mulla Y. (2010). Salinity mapping in oman using re-mote sensing tools: Status and trends. Published in the Monograph on Management of Salt-Affected Soils and Water for Sustainable Agriculture. Mush-taque A, Al-Rawahi SA, Hussain N. eds. Sultan Qa-boos University, Oman, p. 17-24.

Al-Mulla Y, Al-Adawi S. (2009). Mapping temporal changes of soil salinity in al-rumais region of oman using geographic information system and remote sensing techniques. Paper presented at: ASABE An-nual International Meeting. At Reno, NV, US.

Al-Rawas GA, Valeo C. (2011). Spatial assessment of wa-ter quality data in a’seeb area, oman using gis. Mag-azine Geotunis Org, https://www.geosp.net/wp-con-tent/uploads/2012/11 (accessed 17/11/12).

Al-Sadi A, Drenth A, Deadman M, De Cock A, Aitken E. (2007). Molecular characterization and pathogenic-ity of pythium species associated with damping‐off in greenhouse cucumber (cucumis sativus) in oman. Plant Pathology 56(1): 140-149.

Alavipanah SK, Goossens R. (2001). Relationship be-tween the landsat tm, mss data and soil salinity. Journal of Agricultural Science and Technology 3(2): 101-111.

Alhammadi MS, Glenn EP. (2008). Detecting date palm trees health and vegetation greenness change on the eastern coast of the united arab emirates using savi. Inter-national Journal of Remote Sensing 29(6): 1745-1765.

Allbed A, Kumar L. (2013). Soil salinity mapping and monitoring in arid and semi-arid regions using re-mote sensing technology: A review. Advances in Re-mote Sensing: 2(4): 373-385.

Allbed A, Kumar L, Aldakheel YY. (2014). Assessing soil salinity using soil salinity and vegetation indices de-rived from ikonos high-spatial resolution imageries: Applications in a date palm dominated region. Geo-derma 230: 1-8.

Arcidiacono C, Porto SM. (2010a). Classification of crop-shelter coverage by rgb aerial images: A com-pendium of experiences and findings. Journal of Ag-ricultural Engineering 41(3): 1-11.

Arcidiacono C, Porto SMC. (2010b). A model to manage crop-shelter spatial development by multi-temporal coverage analysis and spatial indicators. Biosystems Engineering 107(2): 107-122.

Arcidiacono C, Porto SMC. (2010c). A set of landscape indicators to describe environmental impacts of crop-shelter coverage. Paper presented at: XXVIII International Horticultural Congress on Science and Horticulture for People (IHC2010): International Symposium on on Advances in Ornamentals, Land-scape and Urban Horticulture, Lisbon, Portugal.

Arcidiacono C, Porto SMC. (2007). Image processing for the classification of crop shelters. Paper presented at: International Symposium on High Technology for

Greenhouse System Management: Greensys 2007, Naples, Italy.

Behrendt S, zum Felde A, De Langhe E, Al Khanjari S, Brinkmann K, Buerkert A. (2015). Distribution and diversity of banana (musa spp.) in wadi tiwi, northern oman. Genetic Resources and Crop Evolution 62(8): 1135-1145.

Bhagat R, Singh S, Sood C, Rana R, Kalia V, Pradhan S, Immerzeel W, Shrestha B. (2009). Land suitability analysis for cereal production in himachal pradesh (india) using geographical information system. Jour-nal of the Indian Society of Remote Sensing 37(2): 233-240.

Bhatta B. (2011). Remote sensing and gis. Oxford Uni-versity Press, USA.

Campbell JB, Wynne RH. (2011). Introduction to remote sensing. Guilford Press.

Chiranjit S, Kishore CS. (2016). Land suitability evalua-tion criteria for agricultural crop selection: A review. Agricultural Reviews 37(2): 125-132.

Chivasa W, Mutanga O, Biradar C. (2019). Mapping land suitability for maize (zea mays l.) production using gis and ahp technique in zimbabwe. South African Journal of Geomatics 8(2): 265-281.

Crifasi G, Grassa F, Scrofani M. (2002). Validity of geo-graphic information systems (gis) applied to protect-ed cultivations. In vi international symposium on protected cultivation in mild winter climate: Product and Process Innovation 614 (pp. 41-46)..

Davis BE. (1996). Gis: A Visual Approch. Onword Press, USA.

Dawbin KW, Evans JC. (1988). Large area crop classi-fication in new south wales, australia, using landsat data. International Journal of Remote Sensing 9(2): 295-301.

Deadman ML, Al-Sadi AM, Al-Wardi MM, Al-Kiyumi KS, Deadman W, Al Said FA. (2016). Spatio-temporal dynamics of land use changes in response to external pressures in oman: Greenhouse cropping as an exam-ple. Journal of Agricultural and Marine Sciences 21: 33-46.

Ehlers M. (1996). Remote sensing and geographic infor-mation systems: Advanced technologies for environ-mental monitoring and management. Remote sens-ing and gis for site characterization: Applications and Standards. ASTM International, Pennsylvania, USA.

Elhaddad A, Garcia L. (2006). Detecting soil salinity lev-els in agricultural lands using satellite imagery. In pro-ceedings of the american society for photogrammetry and remote sensing annual conference, Reno, Nevada,

Gastli A, Charabi Y. (2010). Siting of large pv farms in al-batinah region of oman. In 2010 IEEE Internation-al Energy Vonference, 18-22 December 2010, Mana-ma, Bahrain.



Geng-Xing Z, Jing L, Tao L, Yu-De Y, Warner T. (2004). Utilizing landsat tm imagery to map greenhouses in qingzhou, shandong province, china. Pedosphere 14(3): 363-369.

Harris R. (2003). Remote sensing of agriculture change in oman. International Journal of Remote Sensing 24(23): 4835-4852.

Hedia RM, Elkawy ORA. (2016). Assessment of land suitability for agriculture in the southeastern sector of siwa oasis. Alexandria Science Exchange Journal 37(4): 771-780.

Helmy MA, Eltawil MA, Abo-shieshaa RR, El-Zan NM. (2013). Enhancing the evaporative cooling perfor-mance of fan-pad system using alternative pad ma-terials and water film over the greenhouse roof. Ag-ricultural Engineering International: CIGR Journal 15(2): 173-187.

Hiskakis M, Briassoulis D, Babou E, Liantzas K. (2007). Ag-ricultural plastic waste mapping in greece. In interna-tional symposium on high technology for greenhouse system management: Greensys 2007 801, Naples, Italy.

Jamrah A, Al-Futaisi A, Rajmohan N, Al-Yaroubi S. (2008). Assessment of groundwater vulnerability in the coastal region of oman using drastic index meth-od in gis environment. Environmental Monitoring and Assessment. 147(1-3): 125-138.

Jayasuriya H, Al-Wardy M, Al-Adawi S, Al-Hinai K. (2014). Gis mapping of soil compaction and mois-ture distribution for precision tillage and irrigation managementer title. Paper presented at: The 12th In-ternational Conference on Precision Agriculture. At Sacramento, California, USA.

Jha MK, Chowdhury A, Chowdary VM, Peiffer S. (2007). Groundwater management and development by in-tegrated remote sensing and geographic information systems: Prospects and constraints. Water Resources Management 21(2): 427-467.

Jiménez-Bello M, Ruiz L, Hermosilla T, Recio J, Intrigli-olo D. (2012). Use of remote sensing and geographic information tools for irrigation management of cit-rus trees. The Use of Remote Sensing and Geograph-ic Information Systems for Irrigation Management in Southwest Europe CIHEAM.147-159.

Jinguo Y, Wei W. (2004). Identification of forest vegeta-tion using vegetation indices. Chinese Journal of Pop-ulation Resources and Environment 2(4): 12-16.

Kumar KS, Tiwari KN, Jha MK. (2009). Design and technology for greenhouse cooling in tropical and subtropical regions: A review. Energy and Buildings. 41(12): 1269-1275.

MAF. (2013). Agricultural census report 2012/2013 Muscat, Oman: Ministry of Agricultural and Fisher-ies, Oman.

Manyong VM, Legg C, Mwangi M, Nakato V, Coyne D, Sonder K, Abele S. (2008). The potential benefits of gis techniques in disease and pest control: An exam-ple based on a regional project in central africa. In: iv international symposium on banana: International conference on banana and plantain in africa: Har-nessing international 879, Mombasa, Kenya.

Matsuoka M, Nagare H, Fujiwara T. (2015). Simulation of the collection of catch crops for the recovery of ag-ricultural resources using geographic and statistical data. Transactions in GIS, Transactions in GIS. 20(2): 221-239.

Merchant JW, Narumalani S. (2009). Integrating remote sensing and geographic information systems. SAGE Publications Ltd: London, UK.

Mishra AK, Deep S, Choudhary A. (2015). Identification of suitable sites for organic farming using ahp & gis. The Egyptian Journal of Remote Sensing and Space Science 18(2): 181-193.

MOCI. (2006). Omani standard no. 8/2006 for unbot-tled drinking water, Ministry of Commerce, Oman.

Muscat, Oman: Ministry of Commerce and Industry, General Directorate of Specifications and Measure-ments, Oman.

Obade VP, Lal R. (2013). Assessing land cover and soil quality by remote sensing and geographical informa-tion systems (gis). CATENA 104: 77-92.

Olaniyi AO, Ajiboye AJ, Abdullah AM, Ramli MF, Sood AM. (2015). Agricultural land use suitability assess-ment in malaysia. Bulgarian Journal of Agricultural Science 21(3): 560-572.

Parthasarathy U. (2010). Importance of gis in agricul-ture. Financing Agriculture Publisher, Bombay, India.

Picuno P, Tortora A, Capobianco RL. (2011). Analysis of plasticulture landscapes in southern italy through re-mote sensing and solid modelling techniques. Land-scape and Urban Planning 100(1–2): 45-56.

Rajendran S, Al-Sayigh AR, Al-Awadhi T. (2016). Veg-etation analysis study in and around sultan qaboos university, oman, using geoeye-1 satellite data. The Egyptian Journal of Remote Sensing and Space Sci-ence 19(2): 297-311.

Reshmidevi TV, Eldho TI, Jana R. (2010). Knowl-edge-based model for supplementary irrigation as-sessment in agricultural watersheds. Journal of Irri-gation & Drainage Engineering 136(6): 376-382.

Rhee J, Im J, Carbone GJ. (2010). Monitoring agricultural drought for arid and humid regions using multi-sen-sor remote sensing data. Remote Sensing of Environ-ment 114(12): 2875-2887.

Romano G, Dal Sasso P, Liuzzi GT, Gentile F. (2015). Multi-criteria decision analysis for land suitability mapping in a rural area of southern italy. Land Use Policy 48: 131-143.

23Review Article


Sadat-Noori S, Ebrahimi K, Liaghat A. (2014). Ground-water quality assessment using the water quality in-dex and gis in saveh-nobaran aquifer, iran. Environ-mental Earth Sciences 71(9): 3827-3843.

Sahoo R, Ray S, Manjunath K. (2015). Hyperspectral re-mote sensing of agriculture. Current Science 108(5): 848-859.

Sajjad A, Hussain A, Wahab U, Adnan S, Ali S, Ahmad Z, Ali A. (2015). Application of remote sensing and gis in forest cover change in tehsil barawal, district dir, pakistan. American Journal of Plant Sciences 6(9): 1501-1508.

Saleh AM, Belal AB, Mohamed ES. (2015). Land resourc-es assessment of el-galaba basin, south egypt for the potentiality of agriculture expansion using remote sensing and gis techniques. The Egyptian Journal of Remote Sensing and Space Science 18(1, Supplement 1): S19-S30.

Shalaby A, Tateishi R. (2007). Remote sensing and gis for mapping and monitoring land cover and land-use changes in the northwestern coastal zone of egypt. Applied Geography 27(1): 28-41.

Sönmez NK, Mustafa S. 2006. Use of remote sensing and geographic information system technologies for developing greenhouse databases. Turkish Journal of Agriculture and Forestry 30(6): 413-420.

Soomro TR. (2015). Gis enabling smart agriculture. In: Rehman A-u, editor. Smart Agriculture: An Approach towards Better Agriculture Management. Foster City, USA: OMICS Group eBooks. p. 61-66.

Tarantino E, Figorito B. (2012). Mapping rural areas with widespread plastic covered vineyards using true color aerial data. Remote Sensing 4(7): 1913-1928.

Tenkorang F, Lowenberg-DeBoer J. (2008). On-farm profitability of remote sensing in agriculture. Journal of Terrestrial Observation 1(1):50-59.

Usery EL, Pocknee S, Boydell B. (1995). Precision farm-ing data management using geographic information systems. Photogrammetric Engineering and Remote Sensing. 61(11): 1383-1391.

Uyan M. (2013). Gis-based solar farms site selection using analytic hierarchy process (ahp) in karapinar region, konya/turkey. Renewable and Sustainable En-ergy Reviews 28: 11-17.

VoPham T, Wilson JP, Ruddell D, Rashed T, Brooks MM, Yuan J-M, Talbott EO, Chang C-CH, Weissfeld JL. (2015). Linking pesticides and human health: A geo-graphic information system (gis) and landsat remote sensing method to estimate agricultural pesticide ex-posure. Applied Geography 62: 171-181.

Wang G, Weng Q. (2013). Remote sensing of natural re-sources. CRC Press, Boca Raton, FL.

Ward MH, Nuckols JR, Weigel SJ, Maxwell SK, Cantor KP, Miller RS. (2000). Identifying populations poten-tially exposed to agricultural pesticides using remote sensing and a geographic information system. Envi-ronmental Health Perspectives 108(1): 5-12.

Wilson JP. (1999). Local, national, and global applica-tions of gis in agriculture. Geographical Information Systems: Principles, Techniques, Management, and Applications, Publisher, Ciry, 981-998.

Wu BM, van Bruggen AHC, Subbarao KV, Pennings GGH. 2001. Spatial analysis of lettuce downy mildew using geostatistics and geographic information sys-tems. Phytopathology. 91(2):134-142.

Yang D, Chen J, Zhou Y, Chen X, Chen X, Cao X. (2017). Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spec-tral index. ISPRS Journal of Photogrammetry and Re-mote Sensing 128: 47-60.

Yarilgac T. (2012). The use of geographic information systems (gis) in fruit growing. Journal of Science and Technology 2(1): 71-80.

Yu B, Song W, Lang Y. (2017). Spatial patterns and driv-ing forces of greenhouse land change in shouguang city, china. Sustainability 9(3): 359-374.

Review ARticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 24–34DOI: 10.24200/jams.vol26iss2pp24-34Reveived 16 July 2020Accepted 24 Nov 2020

A review on the novel discoveries of Begomoviruses in Oman

M. S. Shahid* and A. M. Al-Sadi

M. S. Shahid ( ) [email protected], Department of Plant Sci-ences, College of Agricultural and Marine Sciences, Sultan Qaboos University, Al-Khod 123, Oman, ORCID: M. S. Shahid : https://orcid.org/0000-0002-3550-0000

Introduction

Geminiviridae is a family of plant pathogens char-acterized by geminate (twin) icosahedral parti-cles containing a circular single stranded DNA

(ssDNA) genome. Based on variability in their genome organization, insect vectors and host range, they are divided into nine different genera: Mastrevirus, Cur-tovirus, Topocuvirus, Begomovirus, Capulavirus, Era-grovirus, Becurtovirus, Turncurtovirus and Grablovirus (Zerbini et al., 2017). Among all genera, Begomovirus is the largest genus in the Geminiviridae, having more than 200 species vectored by whiteflies (Bemisia tabaci, Gen-nadius) (Zerbini et al., 2017). Begomoviruses are known to cause severe damage to many dicot plants in tem-

perate, subtropical, and tropical agroecosystems. The genome of begomoviruses is either bipartite, consisting of two (DNA A and DNA B) genomic components, ap-proximately 2.6-2.8 kb in size or monopartite (DNA A) consisting of a single component ranging from 2.6 to 2.8 kb in size. The bipartite begomoviruses frequently occur in the New World (NW), which includes Central America and South America, while the monopartite begomoviruses are commonly found in the Old World (OW), which consists of Australia, Japan, China, Indi-an subcontinent, Africa, Mediterranean and European region (Zerbini et al., 2017). The DNA A component of begomoviruses originating from the OW consists of genes that encode six proteins (Rep, TrAp, REn, CP and V2 and C4).

In the OW, the majority of monopartite begomovi-ruses are associated with betasatellites (family Tolecu-satellitidae, genus Betasatellite) (Briddon et al., 2018; Zhou et al., 2013), which are circular ssDNA molecules

استعراض الاكتشافات الجديدة لفيروسات البيجوموفيروس في عمانمحمد شفيق شاهد و عبدالله بن محمد السعدي

Abstract. Begomoviruses (family; Geminiviradae) consist of single-stranded (ss) and circular genome particles. They are transmitted by whiteflies, and represent a major constraint to agricultural crops in different parts of the world. In Oman, they have been causing huge losses to crops (tomato, cucumber, watermelon and beans). Research on begomo-viruses in Oman over the last years focused on molecular characterization, phylogenetic relationship, recombination analysis, pathogenicity test on model and host plants and the development of transgenic plants with resistance. Some studies focused on the association of DNA satellites (alphasatellite and betasatellite) molecules with begomoviruses. This review highlights the latest developments in begomovirus and associated DNA satellites discoveries in Oman over the last three decades. This period encountered changes in agricultural practices and developments in virus detection technologies from morphological to the application of genome diagnostics to the emergence of high throughput DNA sequencing, capable to sequence multiple and diverse DNA molecules in parallel, enabling of millions of DNA mole-cules to be sequenced at a time. In addition, several tomato cultivars bearing different Ty genes having resistance to TYLCD complex were developed.

Keywords: viruses, whitefly, transmission

الملخص:تتكــون فيروســات البيجوموفــيروس والــي تنتمــي الى عائلــة الجمنيفيريــديا مــن جزيئــات جينــوم أحاديــة ودائريــة و تنتقــل عــن طريــق الذبابــة البيضــاء. تمثــل هــذه الفيروســات عقبــة رئيســية أمــام المحاصيــل الزراعيــة في أجــزاء مختلفــة مــن العــالم، كمــا تســبب خســائر فادحــة في عــدة محاصيــل في ســلطنة عمــان، منهــا الطماطــم والخيــار والبطيــخ والفــول. ركــزت الأبحــاث الــي أجريــت علــى فيروســات البيجوموفــيروس في عمــان علــى مــدى الســنوات الماضيــة علــى التوصيــف الجزيئــي ، والعلاقــة التطوريــة ، وتحليــل إعــادة التركيــب ، واختبــار الإمراضيــة علــى النبــاتات، وتطويــر نبــاتات معدلــة وراثيــا ذات مقاومــة للأمــراض. كمــا ركــزت بعــض الدراســات علــى ارتبــاط جزيئــات الالفاســاتلايت والبيتاســاتالايت بالفيروســات. تســلط هــذه الورقــة الضــوء علــى آخــر الأبحــاث علــى الفــيروس في الســلطنة علــى مــدى العقــود الثلاثــة الماضيــة، وهــي الفــترة الــي شــهدت تغــيرات في الممارســات الزراعيــة وتطــورات في تقنيــات الكشــف عــن الفيروســات مــن الاعتمــاد علــى الشــكل المورفولوجــي إلى تطبيــق تشــخيص الجينــوم وتحليــل تسلســل الحمــض النــووي وإدخــال أصنــاف الطماطــم الــي تحمــل

جينــات Ty المختلفــة الــي لهــا مقاومــة لســلالات الفــيروس.الكلمات المفتاحية: الفيروسات، الذبابة البيضاء، الانتقال.

25Review Article

Shahid and Al-Sadi

of ~1350 nucleotides (nt) in size. Betasatellites depend on a helper virus (the main virus DNA genome) for rep-lication, movement, and transmission between plants (Briddon et al., 2002, 2001; Saunders et al., 1999; 2004; 2008). However, they have no sequence similarity to their helper begomoviruses, except the hairpin struc-ture, which has resemblance to the region of gemini-viruses replication which contains the nonanucleotide (TAATATTAC) sequence (Briddon et al., 2003). Many begomovirus strains and associated satellites have been identified in Oman on various plants, including vegeta-ble, legume, medicinal, weed and fruits crops. Contem-plating the significance of begomoviruses to Omani ag-riculture, the significant research accomplishments on begomoviruses in Oman over the last three decades are presented in this review.

Agriculture in OmanBeing a non-agricultural country as well as its geograph-ical location, Oman has historical trade relations with various countries around the globe, particularly with Asian and African countries. Agricultural commod-ities in Oman are particularly imported from Iran, In-dia, Pakistan, Egypt, Lebanon and from various other countries. The agricultural produce of Oman, mainly in winter season, is grown primarily for local consumption except for certain export to some neighbouring coun-tries like UAE. Al Batinah North and Dhofar in the south are the main agricultural cultivation areas in Oman. Ac-cording to MAF (2015) (www.maf.gov.om), the total area under cultivation in Oman is 67,000 ha, though most of planting material is imported from different countries. The import of planting material for commercial farms or via travellers and workers has led to the introduction of different begomoviruses into Oman. The exchange of planting material among farmers as well as local prop-agation of imported planting material that is infected with viruses helped spread viruses locally.

Begomovirus Research in Oman Over the past few years, extensive work has been carried out on the detection and characterization of begomo-viruses in Oman (originated from different countries) (Figure 1). Studies on begomoviruses utilized poly-merase chain reaction (PCR), rolling circle amplification (RCA), cloning, restriction endonuclease analysis, and the application of next generation sequencing technol-ogy (NGS). Extensive research has been done on bego-moviruses on their sequence analysis, phylogeny, patho-genicity, plant-virus interactions, pathogen-derived transgenic resistance as well as characterization of DNA satellites. Until now different begomoviruses and DNA satellites have been discovered from 16 different agricul-tural crops in Oman (Table 1). This review outlines the main crops affected by begomoviruses in Oman.

Tomato (Lycopersicon esculentum)Tomato is a leading vegetable crop, which is cultivated mainly in the Al-Batinah. Begomoviruses are the major biotic factor limiting tomato production in Oman (Fig. 4c). Tomato leaf curl disease (ToLCD) plants showing variable symptoms (yellow, upward curling, stunting and bushy appearance) were observed by the MAF in the early 1990s. However, the causal organism of the disease was characterized late in 2004. Tomato plants displaying symptoms of ToLCD were collected from tomato fields during the winter season of 2004-2005. Nucleic acid was extracted and used in rolling circle amplification (RCA). Sequence analysis showed 91% nt identity with the Ira-nian strain of tomato yellow leaf curl virus (TYLCV). Similarly, sequence analysis of associated betasatellite showed 88.5% nt identity with tomato leaf curl betasat-ellite (ToLCB) reported from Pakistan. This study was the first to report TYLCV and ToLCB causing ToLCD in Oman (Khan et al., 2008). In 2011, a complex of TYL-CV and a recombinant species of Tomato leaf curl Oman virus (ToLCOMV) associated with an alphasatellite and ToLCB were discovered. The alphasatellite shared max-imum nt identity with ageratum yellow vein Singapore alphasatellite (AYVSGA), which is unusual DNA-2-type alphasatellite that is rarely associated with monopartite begomovirus complex. The pathogenicity study was also done using Agrobacterium-mediated inoculation and it was found that in the coinfection with begomovirus complex, AYVSGA ameliorate the symptoms developed by the TYLCV and ToLCB (Idris et al., 2011; Shahid et al., 2020a). Afterward, a recombinant begomovirus of an African origin, Tomato leaf curl Sudan virus (ToLCS-DV), was identified near the Yemen border. Surprising-ly, no betasatellite was detected from the tomato plants harbouring ToLCSDV. Infectivity was achieved through infectious constructs in N. benthamiana and tomato plants. However, effort to find the interaction of ToLCS-DV with ToLCB in model host plant was not successful (Khan et al., 2012a).

Later, different begomovirus strains such as Chilli leaf curl virus (ChiLCV), Tomato leaf curl Al-Batinah vi-rus (ToLCABV) and Tomato leaf curl Barka virus (ToL-CBV) were also reported to infect tomato in Oman. To avoid further tomato production losses, resistant tomato lines (provided by the World Vegetable Centre, Taiwan) were screened under natural conditions in two different locations. During data recording, ToLCD symptoms were observed on few lines, and the infected leaves were collected and processed for virus identification. Surpris-ingly, a recombinant begomovirus, showing the maxi-mum levels of identity (92.9-93%) to the newly reported Cotton leaf curl Gezira virus (CLCuGeV) in the UAE was detected (KJ939446; Idris et al., 2014). Based on the 91% criteria for begomovirus strain identification by the ICTV (Brown et al., 2015), the name “Al Batinah” for CLCuGeV was proposed. The identified CLCuGeV-AB



begomovirus is a recombinant strain which evolved through intraspecific and interspecific recombination from the “Sudan” strain of CLCuGeV (KJ939446) and Oman strain of CLCuGeV (HF536716) (Figure 3a). The interspecific recombination events showed the presence of a DNA fragment from an African cassava mosaic vi-rus (ACMV), discovered from Burkina Faso (Figure 3b). Recently, ToLCD caused by mixed infection was identi-fied using NGS technology, where mixed infection was identified from tomato plants infected with TYLCV-IR strain, ToLCB and a legume infecting bipartite begomo-virus, Mungbean yellow mosaic India virus (MYMIV). The biological activities of the whole virus complex were also studied in N. benthamiana (a model host) and to-mato (natural) host plants (Shahid et al., 2019b).

Cassava (Manihot esculenta)Oman has long relations with Zanzibar in Africa, where many Omanis brought cassava tubers back into Oman. Although, the cultivation of cassava is at a limited scale in Oman, cassava mosaic disease (CMD) was observed during a begomovirus survey in A’Seeb, Muscat. A sin-gle bipartite begomovirus, East African cassava mosaic Zanzibar virus (EACMZV), has been identified as the causative agent for CMD in Oman (Khan et al., 2013a) (Figure 3b). This virus has narrow geographical distribu-tion as it was only reported from Zanzibar and Kenya. This suggests that EACMZV has been imported through cassava tubers into Oman. The Bemisia tabaci popu-lation was also noticed on infected cassava plants in Oman, yet their contribution in CMD dissemination has not been studied. Since cassava is grown at a small scale in Oman, which is very isolated from the major cassava cultivation regions of the world, so it should be easy to wipe out CMD in the country by the establishment of virus-free cassava tubers, subject to proper quarantine

measures to avoid future incursions. However, the emer-gence of CMD in Oman emphasizes how the human ac-tivities can disseminate plant pathogens, as reported for other crops (Phytophthora. Ramorum in Northern Cali-fornia) (Cushman et al., 2008).

CucurbitsWatermelon chlorotic stunt virus (WmCSV), a Middle Eastern virus, and Squash leaf curl virus (SLCV), hav-ing a New World origin, are two bipartite begomovirus-es that cause severe economic losses to Cucurbitaceae plants throughout the Middle East and the world. The first molecular characterization of WmCSV was from Squash (Cucurbita moschata) plants in Oman. The C. moschata plants exhibiting begomovirus symptoms were observed (Figure 4g) in an experimental field in the Agriculture Experimental Station (AES), Sultan Qaboos University Oman. Sequence analysis revealed the high-est nt identity with DNAA and DNA B components of WmCSV isolates of Iran (Khan et al., 2012b; Shafiq et al., 2020). Pathogenicity of the virus was confirmed using agrobacterium mediated inoculation into N. benthami-ana model host plants. N. benthamiana plants did not show any visible symptoms following inoculation with DNA A only. However, N. benthamiana plants pro-duced obvious symptoms after 15 days of inoculation when inoculated with DNA A and DNA B (Khan et al., 2012b). Watermelon (Citrullus lanatus) is an essential summer food crop in Oman. In 2015, C. lanatus plants displaying yellow, leaf curling, and crumpling symptoms with a disease incidence of 70%-80% were observed at SQU, Oman. The genomic components verified to be the monopartite begomovirus ChiLCV and ToLCB infect-ing watermelon plants (Shahid et al., 2017b; 2020b).

Cucumber (Cucumis sativus) is another greenhouse crop extensively grown in Oman. Recently, C. sativus

Figure 1. The world depicting possible origin and migration routes of begomoviruses identified in Oman, mainly from East and North Africa (purple and green arrows), Middle east (Brown arrow), Mediterranean (blue arrow) and Indian subconti-nent (dark blue arrow).

27Review Article

Shahid and Al-Sadi

plants showing yellow mosaic and crumpling, symptoms typical of begomovirus infection were observed (Figure 4b). Also, medium to high density of whitefly population was observed on cucumber plants in Barka farms. The whitefly is a complex of more than 40 crypitc species, or biotypes, including the widespread Middle East-Asia Minor 1 (MEAM1 or B biotype) and Mediterranean (MED or Q biotype). Transmission of begomoviruses solely depends on their interaction with B. tabaci, where begomoviruses have to cross the certain barriers situat-ed in the whitefly where some of the proteins bind with the Coat Protein (Czosnek et al., 2017; Fiallo-Olivé et al., 2019). After cloning and sequencing analysis, it was confirmed the MYMIV is associated with the cucumber disease (Shahid et al., 2018).

Squash leaf curl virus (SLCV) is a NW begomovirus, but according to few reports, it has been identified from many Middle Eastern countries like Jordan, Israel and Egypt. Recently, squash plants showing severe symp-toms typical of begomovirus infection were observed on squash plants (Fig. 4e). In molecular analysis, viral ge-nome DNA A and DNA B components were produced and sequenced. Sequence analysis confirmed that the squash plants are infected with a bipartite begomovirus SLCV, which has highest similarity with an SLCV isolate reported from Israel (IsSq-C2; KT099165, Rosario et al., 2015) (Figure 3b). SLCV is the first NW begomovirus infecting squash in Oman (Shahid et al., 2020c) (Ta-ble 1). Since, different exotic monopartite begomoviral strains have been discovered to infect agricultural crops in Oman and the introduction of another bipartite bego-movirus may cause extra risk through interaction with the former begomoviral strains.

LegumesYellow mosaic disease (YMD) is a vast spread disease of legumes in South Asia. YMD was first identified during 1960 in India (Nariani, 1960), infecting black-gram (Vigna mungo) and mungbean (V. radiata) and resulted in huge losses to legume production. Among legumes, Kidney bean (Phaseolus vulgaris) is a com-monly grown vegetable crop in Oman. During a field visit in 2015, foliar mosaic, yellow, and crumpling symp-toms, with whitefly population, was observed on kid-ney bean plants. Genomic DNA isolation followed by begomovirus identification using PCR and RCA was done. Sequencing and sequence analysis confirmed mixed infection by Mungbean yellow mosaic India virus (MYMIV), which was associated with ToLCB. Sequence analysis of DNA A sequences indicated 99% nt sequence identity (Figure 2B), which confirms that a single bego-movirus species is involved in the disease. In recom-bination analysis, DNA A sequence showed potential intraspecific genome recombination with MYMIV-PK and MYMIV-IN strains as the major and minor par-ents, respectively. The sequence of the homolog DNA B of MYNIV showed 97.8% nt sequence identity with

MYMIV-IN isolate, which was further verified by phy-logenetic analysis (Table 1). The MYMIV Oman demon-strated the greatest levels of nt identity to the isolates reported in Southeast Asia (Shahid et al., 2017). MYMIV are member of “legumoviruses” which are very unique among other bipartite begomoviruses discovered in the OW and phylogenetically they have a diverse group of begomoviruses (Ilyas et al., 2009) (Fig. 2B). MYMIV is common in India, Pakistan, Nepal, Indonesia and Chi-na (Tsai et al., 2013). Oman is far away in west, where the MYMIV has been reported. The isolates of the virus reported in Oman have high identity to isolates iden-tified from India from cowpea plants. This possibility leads to indicate that this unusual MYMIV has been possibly imported from the South Asian county (India).

Okra (Abelmoschus esculentus)Okra (Abelmoschus esculentus) is an extensively culti-vated vegetable crop, and it is believed to be originat-ed from western Africa. It is widely cultivated during winter season from small to large scale in different re-gions of Oman. Okra leaf curl disease (OLCD) is a main problem in okra cultivation. OLCD is characterized by curling, distortion, yellowing, mottling, mosaic, and stunted growth (Figure 4h). In Oman OLCD is caused by a begomovirus and associated betasatellites and alpha-satellites (Akhtar et al., 2014). The analysis of sequences confirms that the begomovirus has maximum identity (85%) with CLCuGeV (Figure 2A). Since the nt sequence identity of virus was lower according to the criteria set for species demarcation by International Committee on Taxonomy of Viruses (ICTV), hence it was discovered as a new virus species which was named as Okra leaf curl Oman virus (OLCOMV). Further sequence anal-ysis showed that the OLCOMV has evolved through different recombinant events among CLCuGeV and TYLCV-OM. The sequence analysis of DNA satellite revealed that betasatellite seemed to be of African ori-gin, known as okra leaf curl betasatellite (OKLCB) and the okra leaf curl alphasatellite (OKLCA) of Middle East origin. Although several begomovirus and DNA satel-lites complexes have been identified from Okra plants globally, however in Oman a single monopartite bego-movirus complex has been reported. This monopartite begomovirus complex infecting okra possibly provides an environment for mixed infection, which leads to the evolution of recombinant viruses and satellites through mutation and genomic components exchange.

Papaya (Carica papaya)Papaya (Carica papaya) belonging to the Caricaceae family and it is a dicot woody plant, native to Mexico, America (Central and South) but now adapted to al-most all tropical regions (https://www.arabnews.com/node/344838). Due to its dietary benefits and demand, its production has been significantly increased over the last few decades in different countries. Papaya is a wide-



ly grown fruit in Salalah, and as a minor crop in other regions of Oman, with an approximately 20 tons of fruit production annually. Symptomatic papaya plants were collected from Quriyat (Figure 4f ). The viral DNA was PCR amplified, cloned and sequenced. Genome analy-sis revealed that the amplified virus components showed 83.3%-95.1% nt identity to CLCuGeV genome (Figure 2A). Further analysis confirmed that the CLCuGeV has recombination with TYLCV-Iran strain as a major par-ent (Khan et al., 2012a). Different begomovirus species have been reported to infect papaya plant from South-East Asian countries, but so far, a single begomovirus in-fecting this crop has been identified in Oman. However, there are ongoing studies on the geographical distribu-tion and genetic diversity of plant viral strains infecting papaya crop in the country.

Chillies (Capsicum annuum L.) Chillies are an extensively grown vegetable crop after tomato in open fields during winter in Oman. Chili leaf curl disease (CLCD) causes main losses to the chili crop across the Old World and is caused by several begomovi-ruses (monopartite and bipartite). CLCD was first doc-umented in India during the 1960s (Dhanraj and Seth, 1968). Later this disease spread into the neighbouring countries. In Oman, leaf curl disease of chilli was inves-tigated using RCA and agrobacterium mediated inocula-tion approaches. In extensive surveys during 2010-2011, virus and betasatellite genomes were produced and se-quenced completely. According to the sequence anal-ysis with the accessions in the GenBank, they showed the maximum nt identity between 88.0% and 91.1% to the isolates of “Pakistan” strain of ChiLCV, indicating a different strain of ChiLCV for which the name as ChiL-CV-Oman strain (ChiLCV-OM) was proposed. On the other hand, the betasatellite genome sequences exhibit-ed the highest nt identity to a an earlier identified ToL-CB (Khan et al., 2013b; 2013c). Infectious clones were

produced, and infectivity analysis confirmed the biolog-ical role of ChiLCV and ToLCB in disease development in N. benthamiana and tomato plants. However, efforts to infect chilli plants with ChiLCV-OM or with ToLCB were not successful through agrobacterium mediated inoculum, nevertheless under natural field conditions virus and satellite can transmit the disease through the vector (B. tabaci).

Radish (Raphanus sativus)Radish, family Brassicaceae, is an essential and widely grown winter vegetable crop in Oman. It is usually grown as a mix crop along with cabbage, carrot, lettuce and squash. In an earlier study, reddish plants exhibiting typ-ical symptoms of begomovirus infection were observed in Al-Batinah, with severity ranging from 50‒80%. The infected leaves were collected to investigate the patho-gen. Molecular analysis proved that the disease is due to mixed infections of TYLCV and ChiLCV (Al-Shihi et al., 2018a). The begomovirus strains identified from radish showed 99% identity to the isolates of TYLCV and ChiL-CV (Table 1).

The agrobacterium mediated inoculation assays sug-gested mixed infection as evident from different viral symptoms compared with the single virus infection in N. benthamiana plants, which were further confirmed by southern hybridization and real time PCR analysis (Al-Shihi et al., 2018b). After individual inoculation of TYLCV or ChiLCV to N. benthamiana plants, typical begomovirus infections were produced. However, in co-inoculation with TYLCV and ChiLCV, the symptom severity has been enhanced. Southern hybridization and Real-time qPCR confirmed that both viruses interact synergistically where virus load and copy number in-creased in co-inoculation experiments compared with single virus inoculation (Al-Shihi et al., 2017).

Figure 2. Species Demarcation Tool analysis of monopartite begomoviruses (A) and bipartite begomoviruses (B).

29Review Article

Shahid and Al-Sadi

Tobacco (Nicotiana tabacum)Tobacco is grown in Oman in limited farms. In 2015, tobacco plants showing leaf curling (downward), yel-lowing, swelling of veins and stunting were noticed on tobacco plants in Suhar (Figure 4a). RCA was employed to augment the full genome of begomovirus and betasat-ellite. Full-length genome sequences of virus and beta-satellite were determined and after analysis, it was found the variants of ChiLCV and ToLCB were linked with the leaf curl disease of tobacco (Shahid et al., 2019a). More-over, pathogenicity of ChiLCV and ToLCB was verified by Agrobacterium-mediated inoculation into three Ni-cotiana host plants (Shahid et al., 2019). Different bego-moviruses have been identified from the tomato crop, however, ChiLCV is the only begomovirus infecting to-bacco, along with the first detection of ToLCB in tobac-co in Oman.

Basil (Ocimum basilicum)Basil (Ocimum basilicum L.), family: Lamiaceae is a medicinal annually grown plant with purple-white flowers (Danechian et al., 2009). Basil is frequently uti-lized in cooking cosmetics a well as in traditional drugs (Klimánková et al., 2008). Due to its economic value basil is cultivated extensively and consumed as fresh, dried as a cooking spice and domestic use. Due to the rich source of antioxidant and active ingredient properties, basil is consumed for stomach aches as well as for skin diseases. During a field visit in 2014 in Al-Seeb, basil plants show-ing yellowing, curling and leaf crinkling symptoms were observed and collected. After the application of molecu-lar tools, it was verified that the induction of symptoms in basil plants were due to the mixed infection by three monopartite begomoviruses TYLCV-OM, ToLCABV, and ChiLCV. Pairwise sequence analysis of complete ge-

Figure 3. Neighbour-joining phylogenetic trees with 1000 bootstrap iterations and pairwise identity matching with aligned full-length genome sequences of selected begomoviruses with the GenBank accessions, representing different species of monopartite begomoviruses (a) and betasatellites (b).

Figure 4. Different plant species infected by diverse begomoviruses and associated DNA satellites; tobacco (a), cucumber (b), tomato (c), Pumpkin (d), squash (e), papaya (f), watermelon (g), okra (h).



nome sequences of TYLCV-OM, ToLCABV and ChiL-CV showed 98%, 99% and 100% nt identity, respectively, with the previously identified begomovirus strains in Oman. It was further confirmed that these viruses also harbour ToLCB, which exhibited 95% nt identity with an isolate of ToLCB (Ammara et al., 2015) (Table 1).

WeedA weed (Senna italica Mill) showing yellowing and stunting symptoms suspected to begomovirus infection with a moderate density of whiteflies was observed near an infected tomato field in Khasab, Musandam, Oman.

Molecular analysis and phylogenetic analysis using Spe-cies Demarcation Tool (SDT) confirmed the association of ChiLCV with ToLCB with S. italica plants (Salma et al., 2020 unpublished) (Figure 2A). S. italica is the first weed host in Oman co-infected with ChiLCV and ToL-CB (Table 1).

MintMint belongs to genus Mentha (Family: Lamiaceae). It is a valuable herb that has been grown and used for food as well as for medicinal purposes since centuries. During a survey in 2016 in Salalah, Oman, begomovi-

Table 1. List of all monopartite and bipartite begomoviruses and DNA satellites infecting different crops in Oman.

DiseaseVirus(es) identified

Suggested origin

AcronymSymptoms produced

HostDetection

methodStrain in

OmanAssociation

of satellite(s)References(s)

Monopartite begomoviruses

Tomato leaf curl disease

Tomato yellow leaf curl virus

Middle East and/or Medi-terranean

TYLCV Y, LC, STo-mato, Basil, Radish

PCR/RCA TYL-CV-OM ToLCB

Khan et al. (2008)Aummar et al. (2016) Al-Shihi et al. (2018)

Bean yellow mosaic disease

Tomato yellow leaf curl virus

Middle East and/or Medi-terranean and Indian subconti-nent

TYLCV YM, LC, CrCom-mon beans

RCA TYL-CV-IR ToLCB Shahid et al.

(2018)

Leaf curl disease

Chili leaf curl virus

Indian subconti-nent

ChiLCV Y, LC, S

To-mato, Pepper, Water-melon, Basil, Radish, Mint, To-bacco, Urtica incisa

PCR/RCA ChiL-CV-OM ToLCB

Khan et al. (2013a)Shahid et al. (2017a, 2017b, 2019a, 2019d)Al-Shihi et al. (2018)


Cotton leaf curl Gezira virus

North Africa CLCuGV SC, VT, VD

Pa-paya, Toma-to

RCA CLCuGV ToLCB Khan et al. (2012a)

Okra leaf curl disease

Okra leaf curl virus

North Africa OLCV VC, Y, RLA,

RFZ Okra PCR/RCA OL-CV-OM

OLCB and OLCA

Khan et al. (2013b)


Tomato leaf curl Sudan virus

North Africa

ToLCS-DV VC, S, Y Toma-

to PCR/RCA ToLCS-DV-OM ToLCB Khan et al.

(2014a)


Tomato leaf curl Al-Batinah virus

Middle East and/or Indian subconti-nent

ToL-CABV VC, S, Y

To-mato, Basil

RCA ToLCABV ToLCB

Khan et al. (2013b)Aummar et al. (2016)


Tomato leaf curl Barka virus


ToLCBrV VC, S, Y Toma-to RCA ToLCBrV ToLCB Khan et al.

(2013b)


Tomato leaf curl Liwa virus


ToLCL-wV Y, VC, S,

To-mato, Basil

PCR/RCA ToLCLwV ToLCB and AYVSGA

Idris et al. (2011)Amara et al. (2016)

31Review Article

Shahid and Al-Sadi

rus-like symptoms (leaf yellowing and stunting growth) of mint plants were seen. Young symptomatic leaves of mint plants were collected for begomovirus detection. The complete genome sequences of begomovirus analy-sis by using NCBI-BLAST tool http://blast.ncbi.nlm.nih.gov/Blast.cgi) verified the yellow and stunting symptoms of mint were due to the infection by a ChiLCV strain, which is different from the one reported earlier from to-mato and pepper.

The SDT evaluation of ChiLCV sequences with avail-able begomovirus sequences showed mint begomovirus to have high levels of nucleotide sequence similarity to isolates of the “Oman” strain of ChiLCV-OM, showing maximum nt identity 94.9% (Muhire et al., 2014) (Figure 2A). This conclusion was further supported by phyloge-netic analysis, which proved that mint begomovirus to be segregated along with ChiLCV isolates and is divergent from other ChiLCV strains (Table 1). The ChiLCV was

also associated with betasatellite infection in Mentha (Shahid et al., 2019c). The SDT analysis showed 98.2% nt identity with ToLCB isolate (KX452232) recently re-ported from Phaseolus vulgaris (Shahid et al., 2017a). In a phylogenetic study, ToLCB grouped with earlier ToL-CB isolates identified from Arabian Peninsula, which are distinctive from South Asia isolates.

Factors affecting Begomovirus Distribution and Spread in OmanWhitefly vector plays a crucial part in the transmis-sion of begomoviruses. In Oman only B tabaci MEA-MI is reported, which can travel to limited distances, yet possibly, it contributes actively to the distribution of diverse virus species. However, we cannot ignore agri-culture trade activities among countries either through land, sea, or air as they may help disseminate the insect vector into different geographical locations. Another

Bipartite begomoviruses

Cassava mosaic disease

East African cassava mosaic Zanzibar virus

East Africa

EAC-MZV YM Cassava RCA EACMZV ToLCB Khan et al.

(2013a)

Mung-bean yellow mosaic disease

Mungbean yellow mo-saic India virus

Indian Subconti-nent

MYMIV Y, LC, S, YM Tomato, Bean

PCR/RCA/NGS MYMIV ToLCB

Shahid et al. (2019c, 2019d)

Water-melon leaf curl disease

Water-melon chlorotic stunt virus

Middle East and/or Africa

WmCSV LC, C, SSquash, cucum-ber

RCA/PCR WmCSV ToLCB

Khan et al. (2012b)Shahid et al. (2019c)

Squash leaf curl disease

Squash leaf curl virus

Middle East and/or Medi-terranean

SLCV SC, Y, S Squash RCA SLCV ToLCB Shahid et al. (2020)

DNA satellites


Tomato leaf curl betasatel-lite

Middle East ToLCB VC, S, Y Tomato PCR/RCA/

NGS ToLCB Shahid et al. (2019)


Okra leaf curl Oman


OLCB VC, Y, RLA, RFZ Okra PCR OLCOMB Sohail et al.

(2014)


Ageratum yellow vein Singapore alphasat-ellite

South East Asia and/or Indian subconti-nent

AYVSGA Y, VC, S Tomato RCA AYVSGA Idris et al. (2011)


Okra leaf curl Oman alphasat-ellite

Middle East OLCA VC, Y, RLA,

RFZ Okra RCA OLCO-MA

Sohail et al. (2014)

* Yellowing (Y), Leaf curling (LC), Chlorosis (C), Yellow mosaic (YM), Crumpling (Cr), Stunting (S), Severe curling (SC), Vein thickening (VT), Vein deformation (VD), Vein clearing (VC), Reduction leaf area (RLA), Reduction fruit size (RFZ). ** Polymerase chain reaction (PCR), Rolling circle amplification (RCA), Next generation sequencing (NGS)



contributing factor is human movement, which also contributes to the spread of viruses. However, there are other reasons including virus mutation, recombination, polyphagous nature of the vector, rigorous agricultural procedures like growing of single crop or cultivation of a single plant cultivar, cultivation of susceptible cultivars and the world-wide transport of agricultural goods are thought to increase the emergence and proliferation of viruses. Hence, begomoviruses form a major risk to the worldwide food security. Policies must be designed to prevent continuous crop failures due to plant infecting viruses and avoid the transport and spread of these lethal pathogens into new places (where environmental factors are suitable to enhance the population density of the whitefly vector). Environmental factors play a key role in plant-virus interaction, where an optimal temperature can influence disease development, disease severity and/or incidence. For instance, Papaya ringspot virus can multiply, infect, and transmit virus to papaya plants ide-ally between 26 °C to 31 °C (Mangrauthia et al., 2009). In cassava plants, Cassava mosaic virus (genus; begomovi-ruses family; Geminiviradae), enhanced symptoms and viral titres at 25 °C, compared to 30 °C (Chellappan et al., 2005). Banana bunchy top virus, which is vectored by an aphid (Pentalonia nigronervosa), can actively develop and has lowest mortality at 25 °C (Robson et al., 2007). Heat and drought have also an impact on the severity of viral diseases. Such as, in Arabidopsis heat, drought and turnip mosaic virus synergistically reduced the plant growth than the individual factor (Prasch et al., 2013).

Conclusion and Prospects Despite the existence of diverse viruses and DNA sat-ellites that have their origin out of Oman, there is no indication that these begomoviruses are spreading out from Oman. However, to restrict the movement of these pathogens, trade products could be regulated by improved phytosanitary measures. For instance, for dif-ferent import commodities arriving at Sohar port, hard quarantine should be applied to kill the insect vectors, particularly in containers importing wood products. Similar precautionary measures should be applied for the imports through airports and road border (UAE, Saudi Arabia and Yemen). The propagative plant mate-rials/ nursery stocks should be given special attention when inspecting diseases or insect pests. For example, Oman has introduced approximately one million tons of propagative plant material in 2012, which could have harboured vectors and diseases, including begomovirus-es. One latest example is the introduction of begomovi-rus disease of cotton in China, which is believed to be due to the negligence of quarantine material in import of ornamental plants (Sattar et al., 2013). Additionally, we cannot ignore the emergence of new and recombi-nant begomoviruses and DNA satellite strains that could evolve in one place and spread out through the same

trade routes, which are believed to bring the pathogens initially into the country. Hence, to avoid further trade of Geminiviruses, Oman requires to set-up a phytosanitary facility equipped with the latest virus detection and dis-covery technologies.

AcknowledgementThe funds were provided by Sultan Qaboos University to M.S. Shahid, under internal and research fund grants.

ReferencesAkhtar S, Khan AJ, Singh AS, Briddon RW. (2014).

Identification of a disease complex involving a novel monopartite begomovirus with beta- and alphasatel-lites associated with okra leaf curl disease in Oman. Archives of Virology 159: 1199-1205.

Al-Shihi AAM, Khan AJ, Akhtar S, Lima ATM, Zerbi-ni FM, Briddon RW. (2014). Occurrence of new re-combinant begomovirus species infecting tomato in the Al Batinah region of Oman. Plant Pathology 63: 1177-1184.

Al-Shihi AA, Al-Sadi, AM, Deadman M, Briddon RW, Shahid M.S. (2018a). Identification of a distinct strain of Cotton leaf curl Gezira virus infecting tomato in Oman. Journal of Phytopathology 166(3): 199-205.

Al-Shihi AA, Hanson P, Al-Sadi AM, Al-Yahyai A, Brid-don RW, Deadman M, Shahid MS. (2018b). Evalua-tion of tomato inbred lines for resistance to the to-mato yellow leaf curl disease complex in Oman. Crop Protection 110: 91-98.

Ammara UE, Al-Ansari M, Al-Shihi A, Amin I, Mansoor S, Al-Maskari AY, Al-Sadi AM. (2015). Association of three begomoviruses and a betasatellite with leaf curl disease of basil in Oman. Canadian Journal of Plant Pathology 37(4): 506-513.

Briddon RW, Bull SE, Mansoor S, Amin I, Markham PG. (2002). Universal primers for the PCR-mediated amplification of DNA β; a molecule associated with some monopartite begomoviruses. Molecular Bio-technology 20: 315-318.

Briddon RW, Bull SE, Amin I, Idris AM, Mansoor S, Bed-ford ID, Dhawan P, Rishi N, Siwatch SS, Abdel-Salam AM. (2003). Diversity of DNA β: a satellite molecule associated with some monopartite begomoviruses. Virology 312: 106-121.

Chellappan P, Vanitharani R, Ogbe F, Fauquet CM. (2005). Effect of temperature on geminivirus-induced RNA silencing in plants. Plant Physiology 138(4): 1828-1841.

Czosnek H, Hariton-Shalev A, Sobol I, Gorovits R, Ghanim M. The incredible journey of begomoviruses in their whitefly vector. Viruses. 2017; 9(10):273.

Danechian A, Gurbuz B, Cosge B, Ipek A. (2009). Chem-

33Review Article

Shahid and Al-Sadi

ical components of essential oils from basil (Ocimum basilicum L.) grown at different nitrogen levels. In-ternational Journal of Engineering, Science and Technology 3: 9-13.

Dhanraj KS, Seth ML. (1968). Enation in Capsicum an-num L (Chilli) caused by a new strain of leaf curl vi-rus. Indian Journal of Horticulture 25: 70–71.

Idris AM, Shahid MS, Briddon RW, Khan AJ, Zhu J-K, Brown JK. (2011). An unusual alphasatellite associ-ated with monopartite begomoviruses attenuates symptoms and reduces betasatellite accumulation. Journal of General Virology 92: 706-717.

Idris A, Al-Saleh M, Amer M, Abdalla O, Brown J. (2014). Introduction of Cotton leaf curl Gezira virus into the United Arab Emirates. Plant Disease 98: 1593-1593.

Khan A, Idris A, Al-Saady N, Al-Mahruki M, Al-Subhi A, Brown J. (2008). A divergent isolate of Tomato yellow leaf curl virus from Oman with an associated DNAβ satellite: an evolutionary link between Asian and the Middle Eastern virus–satellite complexes. Vi-rus Genes 36: 169-176.

Khan AJ, Akhtar S, Al-Matrushi AM, A-Shihi AA, Al-Hi-nai FM, Briddon R. (2012a). Identification of Cotton leaf curl Gezira virus in papaya in Oman. Plant Dis-ease 96(11): 1704.

Khan AJ, Akhtar S, Briddon RW, Ammara U, Al-Ma-trushi AM, Mansoor S. (2012b). Complete nucleotide sequence of Watermelon chlorotic stunt virus origi-nating from Oman. Viruses 4: 1169-1181.

Khan AJ, Akhtar S, Al-Matrushi AM, Fauquet CM, Briddon RW. (2013a). Introduction of East African cassava mosaic Zanzibar virus to Oman harks back to “Zanzibar, the capital of Oman”. Virus Genes 46: 195-198.

Khan AJ, Akhtar S, Al-Zaidi AM, Singh AK, Briddon RW. (2013b). Genetic diversity and distribution of a distinct strain of Chili leaf curl virus and associated betasatellite infecting tomato and pepper in Oman. Virus Research 177: 87-97.

Khan AJ, Akhtar S, Singh AK, Briddon RW. (2013c). A distinct strain of Tomato leaf curl Sudan virus causes tomato leaf curl disease in Oman. Plant Disease 97: 1396-1402.

Khan AJ, Akhtar S, Singh AK, Al-Shehi AA, Al-Matrushi AM, Ammara U, Briddon RW. (2014a). Recent evolu-tion of a novel begomovirus causing tomato leaf curl disease in the Al-Batinah region of Oman. Archives of Virology 159: 445-455.

Khan AJ, Mansoor M, Briddon RW. (2014b). Oman: a case for a sink of begomoviruses of geographically diverse origins. Trends in Plant Sciences 19: 67-70.

Klimánková E, Holadová K, Hajšlová J, Čajka T, Poust-ka J, Koudela M. (2008). Aroma profiles of five basil (Ocimum basilicum L.) cultivars grown under con-

ventional and organic conditions. Food Chemestry 107: 464-472.

Mangrauthia SK, Singh Shakya VP, Jain RK, Praveen S. (2009). Ambient temperature perception in papaya for papaya ringspot virus interaction. Virus Genes 38(3): 429–434.

Muhire BM, Varsani A, Martin DP. (2014). SDT: A virus classification tool based on pairwise sequence align-ment and identity calculation. PLoS ONE 9: 1-8.

Prasch CM, (2013). Sonnewald U. Simultaneous applica-tion of heat, drought, and virus to Arabidopsis plants reveals significant shifts in signaling networks. Plant Physiology 162: 1849–1866.

Robson JD, Wright MG, Almeida RPP. (2007). Biology of Pentalonia nigronervosa (Hemiptera, Aphididae) on banana using different rearing methods. Environ-mental Entomology 36(1): 46–52.

Rosario K, Marr C, Varsani A. (2015). Begomovirus-As-sociated Satellite DNA Diversity Captured Through Vector-Enabled Metagenomic (VEM) Surveys Using Whiteflies (Aleyrodidae). Viruses 8: 1-16 (Article 36).

Sattar MN, Kvarnheden A, Saeed M, Briddon RW. (2013). Cotton leaf curl disease–an emerging threat to cotton production worldwide. Journal of General Virology 94: 695–710.

Saunders K, Stanley J. (1999). A nanovirus-like compo-nent associated with yellow vein disease of Ageratum conyzoides: evidence for interfamilial recombination between plant DNA viruses. Virology 264: 142-152.

Saunders K, Norman A, Gucciardo S, Stanley J. (2004). The DNA β satellite component associated with ager-atum yellow vein disease encodes an essential patho-genicity protein (βC1). Virology 324: 37-47.

Saunders K, Briddon RW, Stanley J. (2008). Replica-tion promiscuity of DNA-β satellites associated with monopartite begomoviruses; deletion mutagenesis of the Ageratum yellow vein virus DNA-β satellite lo-calises sequences involved in replication. Journal of General Virology 89: 3165-3172.

Al-Mabsili S, Al-Wahibi AK, Al-Sadi MA, Shahid MS. (2020). Association of a monopartite begomovirus and associated betasatellite with yellow vein disease of a weed host, Senna italica Mill in Oman (unpub-lished VirusDisease).

Shafiq M, Sattar MN, Shahid MS, Al-Sadi AM, Briddon RW. (2020). Interaction of watermelon chlorotic stunt virus with satellites. Australasian Plant Pathology 3: 1-2.

Shahid MS, Briddon RW, Al-Sadi MA. (2017a). Identi-fication of Mungbean yellow mosaic India virus as-sociated with tomato leaf curl betasatellite infecting Phaseolus vulgaris in Oman. Journal of Phytopathol-ogy 165: 204–211.



Shahid MS, Al-Sadi AM, Briddon RW. (2017b). First report of Chilli leaf curl virus and tomato leaf curl betasatellite infecting watermelon (Citrullus lanatus) in Oman. Plant Disease 101(6): 1063.

Shahid MS, Al-Mahmooli IH, Al-Sadi MA, Briddon RW. (2018). Identification of Mungbean yellow mosaic In-dian virus infecting cucumber in Oman. Plant Dis-ease 102: 465-465.

Shahid, M.S., Shafiq, M., Raza, A., Al-Sadi, M. A. and Briddon, R. W. (2019a). Molecular and biological characterization of Chilli leaf curl virus and associat-ed Tomato leaf curl betasatellite infecting tobacco in Oman. Virol Journal 16: 1-9 (Article 131).

Shahid MS, Shafiq M, Ilyas M, Raza A, Al-Sadrani, MN, Al-Sadi MA, Briddon RW. (2019b). Frequent occur-rence of Mungbean yellow mosaic India virus in to-mato leaf curl disease affected tomato in Oman. Sci-entific Report 9: 1-14 (Article 16634).

Shahid MS, Raza A, Shafiq M, Al-Sadi MA, Briddon RW. (2019c). Identification of chili leaf curl virus associat-ed with tomato leaf curl betasatellite infecting Men-tha in Oman. Canadian Journal of Plant Pathology 41(2): 291-295.

Shahid MS, Raza A, Shafiq M, Al-Sadi AM, Briddon RW. (2019d). Infection of Urtica incisa with chili leaf curl virus and tomato leaf curl betasatellite in Oman. Journal of Plant Pathology 101: 395-395.

Shahid MS. (2020a). Tomato yellow leaf curl virus inter-action with betasatellites–a global threat to tomato production. Plant Pathology 69: 1191-1192.

Shahid MS. (2020b). Molecular and biological charac-terization of Chilli leaf curl virus and associated beta-satellite infecting Cucurbita maxima in Oman. Virus Disease 31: 378-382.

Shahid MS, Al-Sulaimani H, Al-Sadi AM. Squash leaf curl virus: (2020c). A New World bipartite begomo-virus threatening squash production in Oman. Plant Disease 104(9) (in press).

Tsai WS, Shih SL, Rauf A, Safitri R, Hidayati N, Huyen BTT, Kenyon L. (2013). Genetic diversity of legume yellow mosaic begomoviruses in Indonesia and Viet-nam. Annual Appllied Biology 163: 367–377.

Zerbini FM, Briddon RW, Idris A, Martin DP, Moriones E, Navas-Castillo J, Rivera-Bustamante R, Varsani A, Consortium IR. (2017). ICTV Virus Taxonomy Pro-file: Geminiviridae. Journal of General Virology 98: 131-133.

Zhou X. (2013). Advances in understanding begomovi-rus satellites. Annual Review of Phytopathology 51: 357-381.

ReseaRch aRticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 35–41DOI: 10.24200/jams.vol26iss2pp35-41Received 15 Dec 2020Accepted 13 Mar 2021

Characterization of Genetic Diversity in Dhofari Wild Gazelles

Ahmed Jashool1, Alya Al Ansari2, Waleed Al Marzooqi2, Othman Alqaisi3, Mansour Al Gahdhami3, Mohammed A Al-Abri2,*

Mohammed A Al-Abri2,*( ) [email protected],2Department of Animal and Veterinary Sciences, College of Agriculture and Marine Sciences, Sultan Qaboos University, 1Office of the Conservation of Environment, Royal Court Affairs, 3Department of Biology, College of Science, Sultan Qaboos University

Introduction

The genus gazelle belongs to family Bovidae. Ac-cording to the International Union of Conser-vation of Nature, IUCN, there are eleven differ-

ent gazelle species (Mallon and Kingswood, 2001). In Oman, two known Gazelle species have been document-ed. Namely, Gazella arabica and Gazella subgutturosa marica. Gazella arabica is a vulnerable gazelles species found in the Arabian peninsula (IUCN, 2017; Massolo et al., 2008). In Oman, gazelles are found in protected areas and are scattered in various the wild areas around the country. The numbers of gazelles in the wild are es-timated to be 1737 animals in Jabal Samhan and Nejed areas of Dhofar governorate (Al Hikmani et al., 2015).

توصيف التنوع الجيني للغزال البري بمحافظة ظفارأحمد جشعول، علياء الأنصاري، وليد المرزوقي، عثمان القعيسي، منصور الجهضمي ومحمد العبري

Abstract. Wild gazelles are scattered in most arid and semi-arid areas in the Sultanate of Oman particularly in val-leys, mountains and sandy zones of Rub’ al Khali desert. Recently, however, gazelles’ numbers have been declining in Oman mainly due to the loss of habitat. Consequently, a gradual loss of their genetic diversity is inevitable. However, little is known about the status of the genetic diversity of the Omani wild gazelles. This study aimed to determine the extent of inbreeding, population structure and genetic diversity in the Omani gazelles’ populations in Dhofar region. Samples from four different locations namely Gara, Stom, Solot and Ayon were collected. DNA belonging to 74 gazelles’ fecal samples was extracted using the human stool DNA extraction protocol. Following extraction, four microsatellite nuclear markers were used to calculate the levels of inbreeding, population differentiation and genetic diversity. PCR inhibitors were significantly removed using Bovine Serum Albumin (BSA) and dimethyl sulfoxide (DMSO). The mean inbreeding for the population was 0.228 for all loci with a standard error of 0.09. It is therefore postulated that Dhofari gazelles are generally undergoing gradual inbreeding, which may lead to lack of fitness in future generations. The ge-netic differentiation (Fst) ranged between 0.071 (between Gara and Stom) and 0.231 (between Gara and Ayon). On the other hand, the Fst estimate between Solot (most distant) versus other Dhofari gazelles populations (pooled together) was 3.7%. Principle Components Analysis (PCA) clustered Ayon and Gara populations apart from one another and closer to Stom while placing Solot further than all other populations, which is in agreement with the Fst results and the geographical distribution. In conclusion, the results of this preliminary study provides an insight towards the conserva-tion of wild gazelles in Dhofar in Oman. It provides an initial report on the status of the genetic diversity of Dhofari wild Gazelles and serves as a reference point for future studies assessing their genetic diversity and variability.

Keywords: noninvasive samples, microsatellite, inbreeding, genetic diversity, population structure.

الملخص:تنتشــر الغــزلان البريــة في معظــم المناطــق القاحلــة وشــبه القاحلــة مــن ســلطنة عمــان وخاصــة في الــوديان والجبــال والمناطــق الرمليــة مــن صحــراء الربــع الخــالي، وفي الآونــة الأخــرة ، تواجــه الغــزلان إنخفاضــا في أعدادهــا، الأمــر الــذي قــد يــؤدي الى فقــدان التنــوع الجيــي تدريجيــا ممــا قــد يتســبب في انقراضهــا مــن البريــة، ويعتــبر الفقــدان التدريجــي للتنــوع الجيــي خســارة لأحــد المقومــات الرئيســية الــي قــد تحمــي مــن الأنقــراض، وحــى الان لا يعــرف ســوى القليــل عــن حالــة التنــوع الوراثــي للغــزلان العربيــة البريــة في محافظــة ظفــار. هــدف هــذا المشــروع إلى تحديــد أفضــل الطــرق لأخــذ عينــات روث الغــزال وتحليلهــا والتعــرف علــى أفضــل بروتوكــول لإســتخاص الحمــض النــووي الريبــوزي )DNA( والتحســن مــن أداء تفاعــات سلســلة البوليمــرز )PCR(. ويعتــبر إســتخاص الحمــض النــووي مــن الــروث مــن أفضــل البدائــل للحيــوانات البريــة وهــو بديــل عــن إســتخاصه مــن الــدم والــذي قــد يتطلــب تخديــر الحيــوان ممــا يعــد عمليــة مضنيــة وخطــرة علــى الحيــوانات البريــة، أمــا الأهــداف الثانويــة فهــي تطويــر فهــم مســتويات زواج الأقــارب و نوعيــة التركيبــة الجينيــة والتنــوع الوراثــي لــدى مجموعــات الغــزلان البريــة، وقــد إســتنتج أن أفضــل بروتوكــول لإســتخراج الحمــض النــووي مــن عينــات الــروث هــو البروتوكــول الــذي يســتخدم في اســتخراج الحمــض النــووي للــبراز البشــري، وبعــد اســتخراج الحمــض النــووي مــن هــذه العينــات تم اســتخدام أربعــة عامــات وراثيــة مــن نــوى الخــايا الجســمية في تحديــد مســتوى زواج الأقــارب والتنــوع الجيــي في الغــزلان، ولقــد تحســنت هــذه )DMSO( وثنائــي ميثيــل سلفوكســيد )BSA( وذلــك عــن طريــق إضافــة مــادة المصــل البقــري الــزالالي PCR القياســات بعــد أن تمــت إزالــة مثبطــات تفاعــل سلســلة البوليمريــزوأظهــرت النتائــج بأن متوســط زواج الأقــارب هــو 0.228 لجميــع عينــات محافظــة ظفــار وبنســبة خطــأ قياســي )SE( قــدره 0.09، حيــث يشــر ذلــك بأن الغــزلان تمــر بمرحلــة مبكــرة مــن التــزاوج الداخلــي التدريجــي، أمــا فيمــا يتعلــق بالتنــوع الوراثــي الجيــي فقــد إعتمــد علــى حســابات Fst المتبعــة بــن مجموعتــن مــن الغــزلان مثــل نتائــج Fst الــي تصــل الى 3.7٪ بــن مجموعــة غــزلان منطقــة صولــوت Solot و باقــي الغــزلان المضمنــه في الدراســة، وأمــا قياســات ال Fst لباقــي الغــزلان البريــة فهــي تــتراوح مــا بــن 0.071 )بــن وادي غــارة ووادي ســتوم( و 0.231 )بــن وادي غــارة ووادي عيــون(، ولقــد حللــت الخلفيــة الجينيــة بطريقــة تحليــل المكــونات الرئيســية للمجموعــات الأربــع مــن الغــزلان البريــة الموجــودة في أربــع وديان رئيســية وأشــارت النتائــج عــن بعــد غــزلان عيــون عــن غــارة جينيــا وتبعــد عنهــا بقليــل غــزلان وادي ســتوم وأمــا غــزلان منطقــة صولــوت فقــد كانــت الأبعــد عــن غــزلان المناطــق الأخــرى، وتتفــق هــذه النتائــج الFst وواقــع التوزيــع الجغــرافي لمواقــع جمــع العينــات، وفي الختــام ، تعــد نتائــج هــذه الدراســة هــي الأولى مــن نوعهــا في دراســة إمكانيــة إســتخاص الحمــض النــووي مــن عينــات الــروث في الغــزال في الســلطنه وهــي ذات أهميــة في معرفــة التركيبــة الجينيــة للغــزلان البريــة في ســلطنة عمــان ويمكــن اســتخدام نتائجهــا كمرجــع للدراســات المســتقبلية المعنيــة

بالتنــوع الجيــي في الغــزال العــربي في الســلطنة.



The first action taken by the Omani government to pro-tect wild gazelles was to set up several sanctuaries that encompassed gazelles. These sanctuaries include Ras Al Shagar protected Area, Al Wusta Wildlife Reserve, and Jabal Samhan protected area, established in 1982, 1994 and 1997 respectively. Together, these sanctuaries have greatly attributed to the protection of gazelles’ popula-tion in Oman although several populations are still strug-gling to survive due to habitat destruction (as a result of highways construction and urban sprawl), pouching and reduction of pastures due to lack of rainfall (Ministry of Environment and Climate Affairs, Sultanate of Oman, personal communication). Other areas where wild ga-zelles have been reported including Al Saleel Natural Park, Al Hajar Mountain, and southern coastal plain of Mirbat and Sadah. Additionally, few separated individ-uals have been reported throughout Dhofar Nejd areas (Ministry of Environment and Climate Affairs, Sultanate of Oman, personal communication).

Unfortunately, gazelles population are continuously declining due to illegal hunting and animal capturing (Al Hikmani et al., 2015; Massolo et al., 2008). Gazelles are a main dietary component for some wild species, such as the Arabian leopard Panthera pardus nimr (com-monly found in Dhofar mountains) which (Judas et al., 2006). In addition, gazelle’s juveniles are considered one of the opportunistic mammalian preys for the scaven-ger white vulture’s (considered an endangered species by the IUCN, 2017) which relies on gazelles juveniles as feed for its hatchlings (Margalida et al., 2012). In addition, habitat degradation and population fragmen-tation also threaten Arabian gazelles. The presence of various kinds of flora in many valleys in Oman is a pri-mary source of feed for many wildlife species. However, plants destruction along valleys due draught or weather conditions is common. An example of conditions is the floods caused by the tropical cyclone Gonu in northern Oman in 2007, and more recently, the destructive cy-clone (Mekunu) and the cyclone (Luban), which impact-ed Dhofar Governorate in 2008. These cyclones could diminish the numbers of wild gazelles and the types of plants that they feed on in addition to threatening their livelihood as gazelles become unable to adapt to sudden habitat and environmental catastrophes (Ministry of Environment and Climate Affairs, Sultanate of Oman, personal communication). Another challenge facing the gazelle populations is the construction of road networks across gazelles habitats separating gazelles herds small-er herds, which could increase inbreeding and reduce fitness. For instance, the road between Qurayyat and Sur Wilatats splits the wild gazelles population into two herds (groups) of gazelles with little interbreeding be-tween both populations. The pouching of adult gazelles in various parts of Oman remains a continuous threat the gazelles’ population.

Non-invasive sampling is advantageous and it is easier and cheaper than invasive sampling (Taberlet et al., 1999) and is also in line with ethics and conserva-tion strategies for wild animals. Nevertheless, there are some drawbacks associated with in non-invasive sam-pling. For instance, in fecal samples, there is a chance of cross contamination of feces belonging to different individuals. This can be avoided by properly selecting the pellets exactly from the top of the fecal colony to get fecal pellets belonging to only one individual. The challenge associated with fecal DNA is its degradation because of the sun’s UV light (King et al., 2018). The fecal moisture is yet another concern as it enhances the attachment of the soil to the feces and increase the inhibitors from the soil, which in turn prevents prop-er amplification of DNA. Thus, gathering fresh fecal samples and preserving them in very dry and low tem-perature is essential for successful DNA amplification (Murphy et al., 2007). The feces of both Nubian ibex and domestic goats is occasionally confused with the gazelles scats and this could affect the accuracy of the results of genetic diversity studies. In such cross-spe-cies contamination of fecal samples, the alleles obtained for the analysis could give false genotyping results re-sulting in allelic dropout or multiple alleles. In order to avoid such complications, developing basic knowl-edge of differentiation between species fecal samples becomes essential. The separation between individual gazelles fecal samples is also important in assessing the level of genetic diversity of the species. Collecting scat samples from a spot scat of different gazelles are found and it is assumed that it belongs to one individual could result in higher estimates of heterozygosity.

Although the threats of gazelle populations in Oman are continuous, the impacts of these threats on the fit-ness and genetic variation of these populations had not been assessed. It is therefore a matter of importance to assess the status of the genetic variation in the Omani Gazelle population. Such assessment is not only import-ant to guide policy makers to take appropriate actions today, but can be a reference point helping future re-searchers compare today’s genetic variation with their future findings. Monitoring the genetic diversity of Omani gazelles is crucial as it helps us to predict their future fitness, disease susceptibility and the levels of inbreeding (Hedrick and Garcia-Dorado, 2016; Szulkin et al., 2013). Therefore, genetic diversity assessment is required for shaping policies in gazelles’ protection. The aim of this project was to determine population struc-ture and genetic diversity of the Arabian gazelles in Dhofar using microsatellite DNA markers. We utilized a non-invasive sampling approach in which we extracted DNA from gazelles’ scat samples. Our approach is the initial of its kind in assessment of genetic diversity in ga-zelles’ populations in Oman.

37Research Article

Jashool, Al-Ansari, Al-Marzooqi, Alqaisi, Al-Gahdhami, Al-Abri

Materials and Methods

Collection and Grading of Faecal Samples for DNA ExtractionIn this project, 110 gazelles’ feces specimens were col-lected from 69 locations from four different valleys in Dhofar Governorate Stom, Gara, Ayon and Solot (Ta-ble 1). Gazelles scat samples were located by tracing ga-zelles toe prints. Gazelle toes prints are small footprints shaped like a longitudinal symmetrical cross section of an apple with clear med-line as shown in Figure 1.

The diameter of a scat pellet’s area is roughly 30 cm. In collection zones, different pellets from different gazelles usually exist in the same spot. Therefore, in a cluster of fe-ces, old or fresh samples can be found. However, only fresh scat pellets were sampled carefully from the top of any scat colony in order to best ensure they belong to the same indi-vidual. Although we took this measure, it is still imperative to indicate that the samples number is not always reflective of the individuals’ number in a certain site since an individ-ual can defecate at more than one spots within a location. We graded the gazelle’s faecal sample based on their color on a scale of A (fresh gazelle’s feces) to D (at least 5 days old feces). The colors of grades A to D samples ranged from dark black to white respectively as shown in Figure 2. The difference in color is attributed to evaporation of moisture

Table 1. Collection of scat samples in gazelles habitats for Dhofar governorate.

Population Valleys Locations Samples

1 Solot 25 38

2 Wadi Ayon 11 14

3 Wadi Gara 18 29

4 Wadi Stom 15 29

Total 69 110

and physicochemical changes the difference of plants spe-cies that gazelles graze on in different locations. The phys-ical characteristics and grading of scat samples of various colors are given in Table 2.

Samples collection was conducted in the same day and in any given location to limit the collection of scat from the same herd twice. This mitigated the chance of double sampling of the same individual as gazelles could migrate from one location to another especially during lack of water resources and competitions for pasture. The fecal samples were collected in plastic bags, labeled and preserved in a cool box and later frozen at -80°C until DNA extraction.

DNA ExtractionPre-DNA extraction, crusting of fecal samples was per-formed using sterile and disposable blades into 4 mL Ep-pendorf tubes. For the extraction protocols in this proj-ect, we crusted the outer layer of 11 pellets from each sample for a total weight of 0.18 g to 0.22 g. In total, 913 pellets belonging to 83 fecal samples were crusted for DNA extractions. DNA extraction was performed using the QIAamp® human stool DNA extraction protocol fol-lowing the manufacturer’s procedure. DNA concentra-tion and purity were assessed using a nano-drop.

Polymerase Chain Reaction (PCR) Fecal samples carry some compounds that inhibit

PCR reactions. These compounds came from the soil, bile salts, complex polysaccharides, collagen, heme, hu-mic acid, and urea. To overcome PCR inhibitors, 50% DMSO and 10% BSA were used in an amount 2.5µL of total PCR volume. The composition of the master mix was used for amplifying various gazelle molecular mark-ers. These were performed in 25 µL of total volume (1X) containing on average 25 ng/µL of DNA, 200 µM of each dNTP, 2 µM MgCl2, 5 pmol of each primer, 1-unit hot start polymerase, 2.5 µL of the same amount of both 50% DMSO and 10% BSA. Finally, 7.8 µL nuclease free water were added to complete the total PCR volume. The phases of PCR cycles started with 94°C for 7 min and ended with 72°C for 7 min and in-between cycles were as follows: (i) DNA denaturation at 94°C for 30 s, (ii) primers annealing phase for 30 s (at a temperature chosen to be the lowest annealing temperature amongst both primers), and (iii) DNA extension took place at 72°C for 30 s in presence of (Taq) polymerase enzyme.

Fragment AnalysisA size standard “ROX 400” (ABI) (Internal Lean Stan-dard) was run concurrently in each capillary to create the standard curve. Three markers (FAM, HEX and TA-MARA) labeled with different dyes, were used to label the product of the 9 Microsatallite markers shown in Table 4. The markers were run in groups of three (A<B and C) according to the melting point, to reduces the re-quired consumables and duration of analysis. The used composition of the Master Mix for each run is given in Table 3. 10.1µL of the total volume were loaded in 96

Figure 1. An image showing gazelles toe print on the soil.



plate and centrifuged 500 rpm for 1 min. Then, the plate was incubated at 95°C for 5 min and kept on ice for 1min before being centrifuged at 500 rpm for 1 min before ge-notyping using the ABI Genetic Analyzer (model 3130xl).

Measures of Genetic Diversity and Population StructureThe fixation index (F), inter-population differentiation (FST), Hardy Weinberg Equilibrium (HWE) and Prin-ciple Component Analysis (PCA) were calculated using GenALEx V.6.51 (Peakall & Smouse, 2012).

Results

Fragment analysisOut of the 110 DNA samples extracted in this study, 74 samples yielded enough DNA for successful genotyp-ing and only four polymorphic microsatellite markers (BM4505, TEXAN19, INRA40, and BM415) were suc-cessfully amplified. For these markers, four population Gara, Solot (area between Merbat and Sadah), Stom, and Ayon were investigated. Stutter peaks were carefully evaluated to avoid mistakes in allele sizing.

Genetic DiversityA chi-square test of the HWE was performed at a α=0.05 with the null hypothesis (Ho) that the distribution of sample markers followed HWE. The results indicat-ed that there was no significant deviation from HWE in markers frequencies in two populations, Gara and Ayon. However, three markers in Solot, and two in Stom showed a significant deviation from HWE at α=0.05 as illustrated in Table 5. Although not all the loci were in HWE, we decided to include which are not at HWE due to the limitation of small sample size and the few mark-ers used in this study. Therefore, all four loci were used to evaluate the genetic diversity of the four population. The fixation index (F), mean and standard error (SE) of sample size (N), no. alleles (Na), effective alleles (Ne),

Table 2. Physical characteristics of fecal samples as graded in this study.

Grade A B C DColor Black/ green Brown/black Black/Brown White

Moisture Moist Dry Dry Dry

Mucus presence Yes No No No

Soil presence Soil (crystals) Sometimes No No

Scattered Combined Somewhat Scattered Very Scattered

Table 3. Composition of the Master Mix used.

Master mix 1X(µL)

Formamide 9.2

Internal Lean Standard, Rox dye 0.3

DNA form three dilution mixes of labeled dyes of PCR results (2:2:3 or 2:2:4) 0.6

Total volume 10.1

Figure 2. Gazelle fecal samples grades A (fresh) to D (oldest).

39Research Article


observed heterozygosity (Ho), and expected heterozy-gosity (He) and the genetic differentiation values (Fst) for all the populations are presented in the Tables 6 and 7, whereas the PCA is shown in Figure 3.

Table 4. Multiplexes A, B, C: primer names, primers sequences, dye name and melting temperatures of various primers used in the study.

# Loci Primer sequence (´5-> 3´) Forward Reverse Dye Tm C°

A BM302 F-GAATTCCCATCACTCTCTCAGCR-GTTCTCCATTGAACCAACTTCA 5´ HEX 58.4

SR-CRSP6 F-CATAGTTCATTCACAATATGGCAR-CATGGAGTCACAAAGAGTTGAA 5´ FAM 57.5

ETH10 F-GTTCAGGACTGGCCCTGCTAACAR-CCTCCAGCCCACTTTCTCTTCTC 5´ TAMRA 66.4

B TEXAN6 F-AGGCAGTTACCATGAACCTACCR-ATCCTGGTGGGCTACAGTCTAC 5´ FAM 62.1

BM4505 F-TTATCTTGGCTTCTGGGTGCR-ATCTTCACTTGGGATGCAGG 5´ HEX 58.4

TEXAN19 F-CTGAAACCCTCTTATTCAAATTGTGR-TGCAGAGTCAGATAAAAATCCC 5´ TAMRA 58.4

C OarFCB304 F-CCCTAGGAGCTTTCAATAAAGAATCGGR-CGCTGCTGTCAACTGGGTCAGGG 5´ FAM 66.8

INRA40 F-TCAGTCTCCAGGAGAGAAAACR-CTCTGCCCTGGGGATGATTG 5´ TAMRA 59.4

D BM415 F-GCTACAGCCCTTCTGGTTTGR-GAGCTAATCACCAACAGCAAG 5´ TAMRA 59.4

Table 5. Summary of Chi-Square Tests for Hardy-Weinberg Equilibrium. The markers names, degree of freedom (DF), Chi-Square value (ChiSq) and its probability are shown.

Population Locus DF ChiSq Prob.

Gara BM4505 15 20.160 0.166

Gara TEXAN19 28 39.020 0.081

Gara INRA40 1 0.194 0.659

Gara BM415 1 0.000 1.000

Solot BM4505 3 6.000 0.112

Solot TEXAN19 36 56.525 0.016

Solot INRA40 21 67.089 0.000

Solot BM415 3 20.989 0.000

Solot BM4505 15 30.000 0.012

Solot TEXAN19 36 73.229 0.000

Solot INRA40 21 30.238 0.087

Solot BM415 6 11.194 0.083

Ayon BM4505 3 4.160 0.245

Ayon TEXAN19 28 48.333 0.010

Ayon INRA40 15 22.440 0.097

Ayon BM415 1 0.141 0.708

Table 6. Mean and standard error (SE) of sample size (N), no. alleles (Na), no. effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and fixation index (F) for the populations.

Pop Mean/SE

N Na Ne Ho He F

Gara Mean 7.250 4.500 2.863 0.519 0.563 0.030

SE 0.479 1.500 0.708 0.086 0.122 0.075

Solot Mean 21.250 5.500 3.127 0.248 0.617 0.595

SE 6.223 1.500 0.651 0.118 0.106 0.152

Stom Mean 13.000 6.500 4.172 0.663 0.740 0.067

SE 2.415 1.041 0.611 0.111 0.048 0.222

Ayon Mean 8.500 4.750 2.494 0.357 0.505 0.219

SE 1.555 1.377 0.713 0.070 0.119 0.143

Table 7. Gazelle populations pairwise population Fst values.Gara Solot Stom Ayon

Gara

Solot 0.000

Stom 0.073 0.000

Ayon 0.104 0.133 0.000

Fst Values below diagonal. Fst=0 (panmixis), Fst=0.01 (moder-ate diversity), Fst<0.2 (High diversity).



DiscussionThe largest allele number obtained was in Solot (21.25) followed by Stom (13) and lowest sample size observed was in Gara (7.25). However, the number of alleles only increased slightly as the sample size increased. The ob-served heterozygsity did not depart largely from the observed heterzygosity except for Solot and Ayon. The results of the fixation index (Table 6) showed some de-gree of inbreeding in all the locations. However, it was the highest in Solot (0.595) and lowest in Gara (0.030). The Fst values showed the presence of a clear population differentiation in our data with no panmixic populations (lower that 1%). The Fst value between Solot and Stom

populations was 7.3%, which indicates that the two pop-ulations are genetically close. This is also an indication that the two populations are near panmixia and might be undergoing random mating. The Fst value between Gara and Ayon (23.1%) is a relatively higher genetic dif-ferentiation compared to that between other popula-tions. This suggests that there was little interbreeding or migration between the two populations. The Fst value between Gara and Stom was 7.1%, which was moderate and similar to the value between Solot and Stom (7.3%), while that between Ayon and Solot was 10.4%. However, the genetic diversity between Gara and Solot, was 14.5%, which was higher than Ayon and Solot.

Altogether, our results indicated a moderate to high genetic diversity in wild Dhofar gazelle’s populations. In contrast, computing Fst pairwise between two gazelles population (Solot versus remaining populations) gives 3.7% of genetic diversity. Taken together, our results show that all populations had a moderate genetic differ-entiation from one another. However, the levels of ge-netics differentiation found in this study are considered within the range reported for gazelle populations. In a previous study on wild gazelles of the southern Levant, the pairwise Fst between Dorcas gazelles (Arava) and Acacia gazelles was found to be 30.9 % which is a rel-atively high genetic differentiation (Hadas et al., 2015). Principle components analysis of PC 1 vs PC 2 shown in Figure 3a agreed with Fst results and showed that Gara and Stom (lowest pairwise Fst) were closer to each other compared to the rest of the populations. It also placed Gara and Ayon distantly from one another (Highest pairwise Fst).

ConclusionThere was a low to moderate inbreeding levels and moderate to high genetic diversity in wild gazelles pop-ulations included in this study, which indicated higher within population mating and lower between popula-tions mating. Our genetic differentiation (Fst) analysis showed that the highest differentiation was between Gara and Ayon (23.1%). The PCA was in agreement with the genetic differentiation analysis and clustered Gara and Ayon further away from one another. In ad-dition to that, the PCA analysis clustered the popula-tions according to their geographical distribution in the map with Solot being further away from the other sampling locations. Our study illustrates the successful utilization of noninvasive sampling in assessment of genetic diversity in wild gazelle populations in Oman. Nevertheless, additional markers and a larger sample size are required in order to get accurate estimation of population genetics parameters in future studies. Alternatively, utilization of modern genotyping tech-niques such as genotyping by SNPs would ultimately yield more markers and increase the confidence and reliability of the results compared to microsatellites.

Figure 3. Clustering of gazelle populations using principal coordinates analysis a (PC1 vs PC2), b (PC2 vs PC3) and c (PC1 vs PC3).

41Research Article


AcknowledgmentWe would like to thank the Office for Conservation of the Environment, Sultanate of Oman for funding this study. We would also like to thank the following individuals for assisting this project: From the Office for Conservation of the Environment: Yasser Al-Salami, Salim Al-Rabei, Zaher Al-Alawi, Mosleem Al-Amri, Khalid Al-Hakma-ni, Nasser Zabanoot, Suhail Bait Said and Ali Al-Rasbi. From the Ministry of Environment and Climate Affairs: Hamed Al-Wihaibi, Mohammed Al-Sherieqi. From the Minister of Agriculture and Fisheries, Zaken, Korea.

ReferencesAl Hikmani H, Zabanoot S, Al Shahari T, Zabanoot N,

Al Hikmani K, Spalton A. (2015). Status of the Ara-bian Gazelle, Gazella arabica (Mammalia: Bovidae), in Dhofar, Oman. Zoology in the Middle East 61(4): 295–299.

Hadas L, Hermon D, Boldo A, Arieli G, Gafny R, King R, Bar-Gal, GK. (2015). Wild gazelles of the southern Levant: genetic profiling defines new conservation priorities. PloS One 10(3): 1-18 (Article e0116401).

Hedrick PW, Garcia-Dorado A. (2016). Understanding inbreeding depression, purging, and genetic rescue. Trends in Ecology and Evolution 31(12): 940-952.

IUCN. (2017). Gazella arabica. http://dx.doi.org (ac-cessed 5 July 2020).

Judas J, Paillat P, Khoja A, Boug A. (2006). Status of the Arabian Leopard in Saudi Arabia. Cat News, IUCN Species Survival Commission, 1, 1–9. http://www.catsg.org (accessed 15 March 2020).

King SRB, Schoenecker KA, Fike JA, Oyler-McCance SJ. (2018). Long-term persistence of horse fecal DNA in the environment makes equids particularly good can-didates for noninvasive sampling. Ecology and Evolu-tion 8(8): 4053–4064.

Mallon D, Kingswood S. (2001). Global Survey and Regional Action Plans, Antelopes, Part 4: North Africa, the Mid-dle East and Asia. IUCN Publications Services Unit.

Margalida A, Benitex JR, Sanchez-Zapata JA, Avila E, Arenas, R, Donzar JA. (2012). Long-term relation-ship between diet breadth and breeding success in a declining population of Egyptian Vultures Neophron percnopterus. Ibis 154(1): 184–188.

Massolo A, Spalton A, Al-Lamki F. (2008). Notes on the status and conservation of the reem gazelle gazella subgutturosa marica in the Sultanate of Oman. Ital-ian Journal of Zoology 75(3): 305–309.

Murphy MA, Kendall KC, Robinson A, Waits LP. (2007). The impact of time and field conditions on brown bear (Ursus arctos) faecal DNA amplification. Con-servation Genetics 8(5): 1219–1224.

Peakall R, Smouse PE. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28(19): 2537–2539.

Szulkin M, Stopher KV, Pemberton JM, Reid JM. (2013). Inbreeding avoidance, tolerance, or preference in an-imals? Trends in Ecology & Evolution 28(4): 205–211.

Taberlet P, Waits LP, Luikart G. (1999). Noninvasive ge-netic sampling: look before you leap. Trends in Ecol-ogy & Evolution 14(8): 323–327.

ReseaRch aRticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 42–50DOI: 10.24200/jams.vol26iss2pp42-50Received 14 Sep 2020Accepted 27 Jan 2021

Physical and Chemical Fruit Quality Attributes of Two Pomegranate Cultivars Grown at Varying Altitudes of Al-Hajar Mountains in Oman

Basim S. AL-Kalbani1,2*, Rashid A. Al-Yahyai1, Abdullah M. Al-Sadi1, Al-Ghaliya H. Al-Mamari2

Basim S. Al-Kalbani 1,2,*( ) [email protected], 1Depart-ment of Plant Sciences, College of Agricultural and Marine Sciences, Sultan Qaboos University, Al-Khod, Sultanate of Oman, 2Directorate General of Agriculture and Livestock Research, Ministry of Agricul-ture, Muscat, Sultanate of Oman

Introduction

Fruit quality of pomegranate is affected by climat-ic and cultural variables, especially for cultivars that are grown in marginal lands, such as those

cultivated in Al-Hajar Mountains of Oman (Al-Said et al., 2009). Pomegranate is one of the main fruit crops grown in the northern Oman in Al-Hajar Mountain at an altitude of 2000-3000 m above sea level (Al-Said et al., 2009; Al-Yahyai et al., 2009). Omani pomegranates

have a special economic significance in the growing regions of Oman and have attracted customers world-wide, primarily tourists and residents from neighboring Gulf Cooperation Council (GCC) countries leading to a great demand of fruits during harvesting time in Sep-tember every year and huge potential for expansion of cultivated area (Al-Said et al., 2013). Pomegranate is one of the most important fruit crops that gained interest in recent years and currently produced widely around the world. India, Iran, Turkey, China and USA are the leading pomegranate producers and more than 76% of the pomegranate fruits world export is from these coun-tries (Martínez-Nicolás et al., 2019). Pomegranate fruit quality is important to increase the profits of producers.

الخصائص الفيزيائية والكيميائية لجودة صنفين من فاكهة الرمان يزرعان على ارتفاعات مختلفة في جبال الحجر في عمان

باسم الكلباني , راشد اليحيائي , عبدالله السعدي , الغالية المعمريAbstract. The present study investigated the differences in fruit physical and chemical quality characteristics of two popular local pomegranate cultivars, namely Helow and Malasi, as influenced by the altitudinal microclimates. Three sites of varying altitudes were selected for this study at Al-Hajar Mountains in northern Oman that included, high (2019 m, Saiq), mid (1876 m, Sograh) and low altitudes (1540 m, Wakan). The results showed that at lower altitudes of Wakan, the Malasi cultivar had better color attributes than Helow cultivar. Malasi also had more lightness (L), yellowness (b) and color intensity (chroma) but less greenness (a), while in mid-altitude, Helow had better color compared with Malasi cultivar. Furthermore, Helow colors was developed as evidenced in terms of brightness, skin and arils redness at higher altitude compared to the two lower altitude sites. Physical fruit qualities were also investigated and the results indicated that in most measured parameters, the Malasi fruit quality was better in both locations (Sograh and Wakan) than Helow cultivar, while Helow cultivar had superior fruit quality at higher elevation in Saiq. Additionally, Malasi had higher juice volume (JV), total soluble solid (TSS) and titratable acidity (TA) than Helow in Wakan. Helow fruits in Saiq showed better performance and higher results for juice volume (JV), total soluble solid (TSS) and maturity index (MI) as followed by those in Sograh and Wakan. Our study showed that the fruit physical and chemical quality attributes of local pomegranate cultivars are strongly influenced by growing location and altitude.

Keywords: pomegranate, physical and chemical quality, altitudes, microclimates

الملخص:بحثــت الدراســة الحاليــة في الاختلافــات في خصائــص الجــودة الفيزيائيــة والكيميائيــة للفاكهــة لصنفــين محليــين شــائعين مــن الرمــان وهمــا الحلــو و الملاســي، حيــث أنهمــا يتأثــران بالمنــاخ المحلــي المرتفــع. تم اختيــار ثلاثــة مواقــع بارتفاعــات متفاوتــة للدراســة في جبــال الحجــر في شمــال عمــان والــي تضمنــت ارتفــاع )2019 م ، ســيق( ، منتصــف )1876 م ، الســوجرة( والارتفاعــات المنخفضــة )1540 م ، وكان(. أظهــرت النتائــج أنــه في الارتفاعــات المنخفضــة مــن وكان ، وكان للصنــف الملاســي صفــات لونيــة أفضــل مــن الصنــف حلــو. وكان لــدى الملاســي أيضــا خفــة أكثــر في اللــون )L( و اصفــرار )b( وكثافــة )chroma( ولكــن أقــل خضــرة )a( ، بينمــا في الارتفــاع المتوســط ، كان الحلــو يتمتــع بســمات لونيــة أفضــل مــن الصنــف الملاســي. عــلاوة علــى ذلــك ، تطــورت ألــوان الحلــو بشــكل جيــد للغايــة مــن حيــث الســطوع واحمــرار القشــرة والحــب علــى ارتفاعــات أعلــى مقارنــة بالموقعــين المنخفضــين. كمــا تم فحــص الصفــات الفيزيائيــة للفاكهــة وأظهــرت النتائــج أنــه في معظــم المتغــرات الــي تم قياســها كانــت جــودة ثمــار الملاســي أفضــل في كلا الموقعــين )الســوجرة ووكان( مــن الصنــف الحلــو ، بينمــا كان الصنــف حلــو يتمتــع بجــودة ثمــار أعلــى في المرتفعــات العاليــة في ســيق. بالإضافــة إلى ذلــك ، كان لــدى الملاســي كميــة عصــر أعلــى )JV( ، وإجمــالي مــواد صلبــة قابلــة للــذوبان )TSS( وحموضــة قابلــة للمعايــرة )TA( مــن الحلــو في وكان. أظهــرت ثمــار الحلــو في ســيق أداء أفضــل ونتائــج أعلــى في كميــة العصــر )JV( وإجمــالي المــواد الصلبــة الذائبــة )TSS( ومؤشــر النضــج )MI( تليهــا تلــك الموجــودة في

الســوجرة ووكان. أظهــرت دراســتنا أن سمــات الجــودة الفيزيائيــة والكيميائيــة للفاكهــة لأصنــاف الرمــان المحليــة تتأثــر بشــدة بموقــع النمــو والارتفــاع.الكلمات المفتاحية: الرمان ، الجودة الفيزيائية والكيميائية ، الارتفاعات ، المناخ.

43Research Article

AL-Kalbani, Al-Yahyai, Al-Sadi, Al-Mamari

Fruit physico-chemical qualities plays an important role in defining price structure of pomegranate fruits (Al-Said et al., 2009). High demand of pomegranate fruits in the world is because of its health benefits from the juice, arils, dehydrated seeds, rind and other parts of the fruit (Melgarejo et al., 2013).

The local cultivars grown in Oman, are Helow, Qu-sum, Malasi and Hamedh. The Helow cultivar is the most popular with the sweetest taste which occupies the largest cultivated area (Al-Yahyai et al., 2009). Un-desirable characteristics of the other cultivated cultivars like Qusum having hard seeds Malasi smaller in size smoother skin being more susceptible to bruising. Sim-ilarly, Hamedh is a wild cultivar that usually grows on the edges of farms, has highly acidic taste and small fruit size with undesirable eating quality (Al-Said et al., 2009).

Pomegranate quality depends on the factors, such as climate, cultivar, growing conditions, maturity and cul-tural practices. It is important to select suitable climatic conditions to cultivate the best cultivar of pomegranate with desirable quality fruit (El-Salhy et al, 2019). There is variability in performance of these cultivars in dif-ferent agro-climatic conditions (El-Salhy et al., 2019). Despite its great international success, ‘Wonderful’ is one of commercial pomegranate cultivar which has not done well in pomegranate growing regions of Oman. Mphahlele et al. (2016) conducted a study which showed that ‘Wonderful’ pomegranate quality and the maturity stage affected its biochemical and aroma volatile attri-butes under different agro-climatic locations (altitudes). Like pomegranates, Naryal et al. (2019) showed that the fruit sugar contents and sugar profiles of dried apricot (Prunus armeniaca L.) affected when cultivated at dif-ferent altitudes. Further, Boussaa et al. (2020) found that physical properties of pomegranate, such as bioactive compounds, and antioxidant activity also changed with altitude. Peng et al. (2020) grouped 37 varieties of pome-granate in China into three categories based on cluster analysis after analysis of fruit physico-chemical quality parameters. In Al-Hajar mountain, fruits cultivars differ with different elevations. In Saiq (altitude, 2019 m above sea level), Helow cultivar is the dominant among culti-vars as compared to Malasi which is dominant in Wakan at (altitude, 1540 m) and Sograh (altitude, 1876 m). This present study investigated the effects of growing at dif-ferent altitudes on pomegranate fruit and aril physical and chemical quality characteristics of two major culti-vars (i.e. Helow and Malasi).


Sample CollectionThree locations in Al-Hajar Mountain were selected from Al-Jabal Al-Akhdar and Wadi Mastel where pome-granate is commonly cultivated as the primary fruit crop. Two locations in Al-Jabal Al-Akhdar namely; Saiq

(23.0872618 latitude, 57.6938060 longitude and 2019 m altitude) and Sograh (23.144504 latitude, 57.672766 longitude and 1876 m altitude) were used. Other loca-tion from Wadi Mastel, Wakan, (23.1421282 latitude, 57.7340133 longitude and 1540 m altitude) was used. Fruits were harvested from farmers’ field during two years 2018 and 2019. Fruits were hand-picked at skin color change (maturity index) commercial ripening time. Fruits were harvested during the month of September. In Wakan and Sograh, two pomegranate cultivars ‘Helow’ and ‘Malasi’ were selected for the study and one culti-var ‘Helow’ from the 3rd site, i.e. Saiq. Ten ‘Malasi’ and five ‘Helow’ trees were selected for fruit harvest, due to the limited number of representative trees. Five mature fruits per tree were collected for physical and chemical quality measurements.

Analysis of Fruit Physio-chemical Characteristics Color: Color measurements were performed using a colorimeter (Model CR 200, Minolta, Milton Keynes, UK). Fruit color (FC) measurements were taken along the equatorial axis of three selected fruit. Three read-ings of each color index (L* a* b) were taken per fruit, given a total measurement per fruit sample, where L is difference in lightness/darkness value. Negative (L) val-ues indicate darkness and higher positive (L) values in-dicate lightness. On the other hand, negative (a) values indicate green and higher positive (a) values indicate red color. Higher positive (b) values indicate a more yellow skin color and negative (b) indicate a blue color. These values were then used to calculate hue degree, where 0° = red-purple, 90° = yellow, 180° = bluish green, and 270° = blue, and (Chroma), which indicates the intensity or color saturation (Selcuk and Erkan, 2015). Chroma and hue were calculated as follows:

Chroma = √(a*²+b*²) (1)Hue = arctan (b*/a*) (2)

Also arils color was measured with the same colorimeter from tow fruit sample per tree and three readings from each fruit.

Physical quality parameters of fruits and arils: The length and diameter of the fruit and arils were deter-mined with a digital venire caliper while the weight was determined using a weighing balance. Three mature fruits from each tree were taken from Helow and Malasi cultivars. Fruit total length (FL2), fruit total length ex-cluding the calyx (FL1), calyx diameter (FD2), fruit equa-torial diameter (FD1), and fruit skin thickness (Ec). Arils maximum width (Sw) and arils length (SL) were mea-sured. Three arils were used from each fruit sample. Also the seeds of the arils were used to determine width (w), length (L) and weight of woody portion (WPW). Fruits were weighed using a balance of exactitude of 0.001 g. Fresh weights (FW) were taken for three fruits per tree. Rind weight plus weight of capillary membranes (PcMc), aril weight (AW) and weight of woody portion (WPW) inside the aril were measured. Number of carpels (Nc)



in each fruit were also counted. The arils were removed from the fruit and arils fresh weight or arils yield (Rs) were determined (Rs= FW- PcMc).

Chemical quality parameters of fruits: The fruits were peeled and the skin covering the arils was removed. The juice was extracted from pomegranate arils using a juice extractor. The juice was used to determine juice volume (JV) and the chemical properties of each individual fruit and replicated according to the type of measurements. Total soluble solids (TSS) (Brix) were determined on three fruit samples per tree using a temperature com-pensating hand-held refractometer. Juice acidity was measured using three samples per fruit. Percentage of titratable acidity (TA), expressed as percent citric acid, was determined using a 10 ml homogenized extracted juice sample. The juice sample was added to 10 ml dis-tilled water. Aliquot of 20 ml were titrated with 0.1M NaOH until the color changed to pink as indicated by phenolphthalein indicator (AOAC, 2000). Three ho-mogenized samples per cultivar were analyzed for TA.

Statistical analysisThe experimental design used was a Completely Ran-domized Design (CRD). Statistical analysis was done by SAS software using Duncan’s Multiple Range Test (SAS Institute, Cary, N.C.). Treatment means were compared using Duncan’s Multiple Range Test at P ≤ 0.05.

Results

Effect of Locations and Cultivars on Color ParametersEffects of location on the color parameters of Helow and Malasi cultivars and difference among the cultivars (Helow or Malasi) in different locations are shown in Table 1. All cultivars showed significant differences be-tween locations in fruit and arils color parameters except Malasi, which showed no significance different between different locations in arils color. In the lower altitude, Wakan, Malasi cultivar showed higher values in all fruit color parameters than Helow cultivar, where Malasi had more brightness (L), yellowness (b), intense (Chroma) and less greenness (a). Hue values from fruits in Wakan showed that both cultivars were from red to purple, as degree near to zero. In the middle altitude, Sograh, Helow cultivar had more brightness, greenness and yel-lowness while Malasi was more intensely red. Arils color in Wakan and Sograh showed that Helow cultivar had brighter color and yellower than Malasi, which had more intensely red color. Hue was same as in Wakan that both cultivars were from red to purple as degree near to zero. In the higher altitude, Saiq, Helow cultivar was domi-nantly cultivated. Helow cultivar in Saiq showed higher red (a), less yellowness (b) and less intense (Chroma) in fruit color than Sograh and Wakan. Aril color of Helow

fruits was brighter, yellower and less intensely red at low-er altitudes (Wakan and Sograh) than at highest altitude (Saiq). On the other hand, fruit color of Malasi cultivar was brighter, yellower and more intense at lower alti-tudes (Wakan). Malasi cultivar showed more red in color in Sograh than Wakan. Arils color of Malasi cultivar had same brightness, yellowness and intensely same in lower and middle altitudes. Fruit and aril differences among cultivars and locations in color are shown in Figure 1. Fruit and aril color development varies among growing altitudes and between cultivars. Color of Helow cultivar was more affected by location compared with Malasi. Helow cultivar in lower altitudes (Wakan) showed lower brightness (L), less red and intensely in color comparing to Helow and Malasi cultivars in same, middle (Sograh) and higher (Saiq) altitudes in fruits and arils color pa-rameters. Malasi in Wakan was brighter and yellower in fruit color. Malasi arils In Wakan and Sograh higher red in color comparing to the cultivars in the other altitudes.

Effect of Locations and Cultivars on Physical and Chemical Quality Parameters

The effects of locations and cultivars on fruit quality properties were tested by comparing fruit weight (FW), total fruit length (FL), fruit length without calyx (FL1), calyx length (CL), fruit diameter (FD), calyx diameter (CD), number of carpels (Nc), rind weight plus weight of capillary membranes (PcMc), skin thickness (Ec) and arils yield (Rs) of Helow and Malasi cultivars in Saiq, So-grah and Wakan (Table 2). All physical and chemical quality parameters between locations were significant-ly different except for the number of carpels (Nc), skin thickness (Ec) and arils yield (Rs). Also cultivars were significant different (P<0.05) in all parameters except number of carpels (Nc).

Starting with Wakan, the results showed Malasi cul-tivar was significantly better than Helow in fruit weight (FW), total fruit length (FL), fruit length without calyx (FL1), fruit diameter (FD) and rind weight plus weight of capillary membranes (PcMc) (Table 2), while Helow cultivar had higher calyx diameter (CD). In Sograh, there was no significance different in fruit weight (FW) between Malasi and Helow cultivars but Malasi had more total fruit length (FL), fruit length without calyx (FL1), fruit diameter (FD), calyx diameter (CD) and rind weight plus weight of capillary membranes (PcMc). However, Sograh showed same results when comparing between Helow and Malasi cultivars as Wakan which was illustrated previously. Over all, Malasi cultivar performed better in Wakan and Sograh than Helow cultivar. Helow in Saiq was the best in all fruit physi-cal quality parameters than the other locations. It was higher in fruit weight (FW), total fruit length (FL), fruit length without calyx (FL1), calyx length (CL), fruit di-ameter (FD), calyx diameter (CD) and rind weight plus weight of capillary membranes (PcMc). Helow cultivar in Wakan had calyx length (CL) and calyx diameter

45Research Article


(CD) similar to Helow in Saiq. However, there was no significant difference between Saiq and Wakan in calyx length (CL) and calyx diameter (CD) but there was a significant difference from Helow in Sograh, which was lower. Also there was no significance different between Helow in Saiq and Sograh in fruit diameter (FD), total fruit length (FL), fruit length without calyx (FL1) but there was a significant difference from Helow in Wakan which was showed lower on previous parameters. Re-sults clearly indicated that fruit weight (FW) and rind weight plus weight of capillary membranes (PcMc) were significantly higher (P<0.05) in Saiq than Sograh fol-lowed by Wakan. Over all Malasi cultivar quality per-formed better in Sograh and Wakan, while Helow cul-tivar was better in higher elevation in Saiq. There was no interaction between cultivars and locations in all fruit physical quality parameters as showed in Table 2.

The effects of locations and cultivars on fruit quality properties (physical and chemical of fruit quality param-eters) were tested by comparing arils width (SW), arils length (SL), Aril weight (AW), juice volume (JV), total soluble solid (TSS), titratable acidity (TA), maturity in-dex (MI), seed width (W), seed length (L), woody por-tion weight (WPW) and woody portion index (WPI) of Helow and Malasi cultivars in Saiq, Sograh and Wakan (Table 3). Location effects were significantly different with respect to all arils and chemical parameters while cultivars were significantly different with all except arils length (SL), woody portion weight (WPW) and woody portion index (WPI). Firstly, comparing Malasi and Helow cultivars in Wakan, the results showed that Malasi had more aril weight (AW), juice volume (JV), total sol-uble solid (TSS), titratable acidity (TA) and seed width (W) while Helow had higher arils length (SL), maturity index (MI) and seed length (L). Malasi had better aril quality than Helow in Wakan. Secondly, Malasi showed higher chemical quality parameters [juice volume (JV), total soluble solid (TSS), titratable acidity (TA) then

Helow which showed higher physical quality parameters (arils length (SL), aril weight (AW), maturity index (MI), seed width (W) and seed length (L)]. Comparing Malasi cultivars between Wakan and Sograh, it was found that there was no significance different in juice volume (JV), total soluble solids (TSS) and seed length (L). Wakan had higher arils width (SW), aril weight (AW) and seed width (W) while in Sograh, Malasi cultivar showed higher arils length (SL), titratable acidity (TA), maturity index (MI), woody portion weight (WPW) and woody portion index (WPI).

On the contrary, comparing Helow cultivar in the three locations it was observed that higher arils width (SW), arils length (SL), aril weight (AW), titratable acid-ity (TA) and seed width (W) were found in Sograh but there was no significance different between Sograh and Saiq in aril weight (AW) and Sograh and Wakan in ti-tratable acidity (TA). There was no significant differ-ence between the three locations in seed length (L). Saiq Showed higher results for Juice volume (JV), total sol-uble solids (TSS), maturity index (MI), woody portion weight (WPW) and woody portion index (WPI), fol-lowed by Sograh and after that Wakan. Overall, Helow cultivar performed better at higher altitude in Saiq, com-pared with Sograh and the least was for lowest altitude which was Wakan. As the elevation decreased the phys-ical and chemical quality parameters of Helow cultivar decreased. In Malasi there was not much difference be-tween Sograh and Wakan in physical and chemical qual-ity parameters, which was not commonly grown in high elevation areas like Saiq as has been reported by farmers.

Interaction between locations and cultivars also was illustrated in Table 3. Arils physical quality properties showed no significant interaction except in arils weight which showed higher arils weight (AW) in Helow cul-tivar in Saiq while Helow in Wakan was the lowest. There was no significant difference between Helow in Saiq and Sograh and also between Malasi in Sograh

Figure 1. Fruits and arils of Helow and Malasi cultivars in Saiq, Sograh and Wakan.



and Wakan. In seed, physical quality properties there was no interaction except width of the seeds, which was higher in Malasi than Helow in Wakan. The difference in arils weight (AW) and seed width (W) was not high because it differs (0.1 mg) in arils weight and (1.0 mm) in seed width. Arils chemical quality properties high-ly interact between locations and cultivars. Helow in Saiq had higher juice volume (JV) followed by Helow and Malasi of Sograh. Also there were no significant differences between Malasi in Sograh and Wakan and Helow of Wakan where it was the least. Malasi showed higher (TSS) and (TA) than Helow cultivars in all lo-cations. Malasi in Sograh was the highest followed by Malasi of Wakan then Helow of Saiq followed by Helow of Sograh, where Helow of Wakan were the lowest. It was clearly seen that in Helow cultivar, TSS decreased as the elevation decreased. Titratable acidity (TA) also was higher in Malasi of Sograh than Wakan followed by Helow of Wakan. Helow of Wakan and Sograh showed no significant difference with Helow in Sograh and Saiq, which was the lowest. Maturity index (MI) decreased as elevation decreased in Helow cultivar, which was high-er than Malasi cultivar. There was no significant dif-ference between Malasi in Wakan and Sograh in (MI).

Discussion

Experiment on Physical and Chemical Description of Pomegranate FruitsEffect of locations and cultivars on color parameters: Color parameters of Helow and Malasi cultivars of pomegranate fruits grown in Saiq, Sograh and Wakan were significantly different. Fruit brightness as deter-mined by L value at CIELAB scale, showed that the lower altitude Wakan fruits were brighter in color than mid-elevation Sograh in Malasi cultivar, and lowest in Helow cultivar than Sograh followed by Saiq. Fruit brightness (L) indicated how light colors developed in the fruit at the time of harvest and can be attributed to many variables, including the development of other colors (such as tallow background, green, and red col-ors). In fruits, González et al. (2011) suggested that the change in L value may be attributed to genetic variabil-ity among genotypes, which is evident when comparing two cultivars grown in the same location. The increase of L values may be related also to degradation of chloro-phyll as fruits turn red with a differential susceptibility to degradation of chlorophylls among genotype (Ku-mari et al., 2019). In terms of red color of fruits, a* value results showed as the elevation increase red color also increased while yellowness b* increased inversely with elevation which was observed for both cultivars. Dif-ferent trees gown at different elevations are exposed to different microclimatic conditions (such as temperature and relative humidity), which highly influence the col-oration of the fruits. This was observed in the color de-

velopment of deciduous fruits such as in the case of skin color of apple by increasing the carotenoids because of the temperature factor (González et al., 2011). In peach the high-altitude improved skin red blush intensity June Gold cultivar (Karagiannis et al., 2016). Environmental factors like day/night temperature, solar radiation wave lengths or a mixture of these factors can control fruit ripening and the variances between these environmental factors growing with altitude, and it determined the fruit quality at harvest (Kumari et al., 2019). Nour et al. (2015) found that the red color was the product of chlorophyll degradation and synthesis of lycopene and other carot-enoids, as chloroplasts converted into chromoplasts (Bi-lalis et al., 2018). Hue value which was indicated in Table 1 showed that the fruits ranged from red to purple col-or as the degree ranged from (0 to 90). Also intensity of color (Chroma) was higher in Malasi then Helow and as elevation increased intensity decreased and that because of increased in temperature as elevation decreased as found in fruit color tomato by Nour et al. (2015). High-er mean air temperature in the fruiting stage during the second year of the study resulted in more reddish tomato fruits because color saturation increases during the rip-ening of tomato fruits (Bilalis et al., 2018). Also in arils, our finding showed that cultivars varied in size of fruits and fruit and aril color at maturity stage (Al-Said et al., 2009). So different elevations lead to different climate conditions (light intensity, temperature and relative hu-midity) which effect on the color parameters of fruits.

Effect of locations and cultivars on physical and chemical quality of pomegranates: The effects of lo-cations and cultivars were significantly different in all fruits and arils physical and chemical quality parameters as shown in Tables 2 and 3. The results indicated that variations between locations and cultivars was expected because each location (elevation) differs in microclimate (light intensity, temperature and humidity), which leads to variation in fruits and arils physical and chemical quality parameters. Fruit weight (FW) was not signifi-cantly different between Helow and Malasi cultivars. The Helow and Malasi fruit weight decreased as eleva-tion decreased. Helow scored the highest mean for fruit weight (FW) in Saiq and the lowest in Wakan. Solarte et al. (2014) found that altitude influenced fruit weight of different guava genotypes. Regional Roja and Guavatá Victoria guava genotype in the lower altitude had a high-er fruit weight while Regional Blanca and Ráquira Blanca guava genotype reversely affected in higher altitude be-cause of variations between day and night temperatures and higher radiation at lower altitudes that changes the balance between sugar accumulation and degradation resulting in increased fruit weight (Kumari et al., 2019).

Most of the fruits physical quality parameters were influenced by elevation and these increased in both cul-tivars as elevation increased like total fruit length (FL), fruit length without calyx (FL1), fruit diameter (FD) and rind weight plus weight of capillary membranes (PcMc).

47Research Article


Orazem et al. (2011) stated that the fruit size was stimu-lated by genotype in peach fruit (Kumari et al., 2019). In rosehip fruits, physio-chemical features showed signifi-cant differences, and these differences were affected by type, genotype and ecological conditions (Eroğul et al., 2018). Skin thickness (Ec) and arils yields (Rs) were sig-nificant between Malasi and Helow cultivars and this was expected since they were different. The similar findings of Al-Said et al. (2009) showed that cultivars vary in fruit and aril color, and size at maturity which was also ob-served in by Hamid et al. (2018). Porterville fruit had low aril yield regardless of their fruit weight. This might be excused by climatic conditions, which possibly favor the growth of membranes more than arils (Opara et al., 2013).

Measured physical and chemical quality parameters of arils of Malasi and Helow cultivars showed variable response to elevation, particularly in aril length (SL) and width (SW) and weight (AW). Differences in aril and seed physical quality parameters were similarly observed by Opara et al. (2013). In the present study, total soluble sol-ids (TSS) was found to increase with increasing altitudes which is in line with Kumari et al. (2019) in their study on physical and biochemical attributes of three Indian apples (Malus demostica Borkh.) cultivars as affected by

elevation and genotype. Titratable acidity (TA) was also found to decrease as elevation decreased in Helow culti-var, while Malasi showed no difference in this character between locations. Higher juice volume (JV) was ob-served in Helow cultivars than Malasi except in Wakan, where it was found lowest in Helow which was expected because of the lowest fruit weight. Malasi was higher in titratable acidity (TA) than Helow and also it was higher in Sograh than in Wakan while in Helow cultivar, it was higher in Wakan and lower in Saiq. Thus, different culti-vars responded differently to elevations, which had dif-ferent microclimates (Opara et al., 2013). Maturity index (MI) was lower in Malasi cultivars than in Helow and also for high titratable acidity (TA) was found in Malasi cultivars (26.6 and 22.9) in Sograh and Wakan, respec-tively. Seed width was different between locations and cultivars while seed length was no significant between locations but significant between cultivars. Al-Said et al. (2009) observed that cultivars varied in fruit and aril color, and size at maturity and this finding was con-firmed our results which showed Woody portion weight (WPW) and woody portion index (WPI) of Helow and Malasi cultivars decreased as the elevation decrease.

Table 1. Effects of locations on the color parameters of the cultivars and interaction between location and cultivars.

Location CultivarFruit color Arils color

L a b Hue Chroma L a b Hue Chroma

WakanHelow 66.50 B c -3.29 B c 42.96 B a -1.50 B c 43.13 B a 76.07 Aa -0.14 Bc 30.17 A a -0.15 Bc 30.19 B b

Malasi 83.54 A a -0.08 A b 46.67 A a -0.02 A b 46.70 A a 59.77 B Ns 41.78 A Ns 18.68 B Ns 0.42 A Ns 45.81 ANs

SograhHelow 82.48 A a -0.33 B b 38.15 A b -0.27 B b 38.17 B b 76.89 A a 5.31 B b 29.08 Aa 1.39 A a 29.61 Bb

Malasi 73.23 B b 29.54 A a 30.73 B b 0.81 A a 42.94 A b 59.36 B Ns 42.25 A Ns 18.91 B Ns 0.42 BNs 46.34 A Ns

Saiq Helow 75.31 b 8.91 a 33.32 c 1.31 a 34.56 c 70.43 b 17.61 a 27.07 b 0.99 b 32.36 a

P values

Cultivar <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.0282 <.0001

Location <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001

Cultivar*Location <.0001 <.0001 <.0001 0.0265 0.1406 0.2815 <.0001 0.1003 <.0001 0.2172

Cultivar*LocationFruit color Arils color

L*** a*** b*** Hue* Chroma NS L NS a*** b NS Hue*** Chroma

NS

Helow Saiq 75.31 c 8.91 b 33.32 d 1.31 a 34.56 70.43 17.61 c 27.07 0.99 b 32.36

Helow Sograh 82.48 ab -0.33 cd 38.15 c -0.27 d 38.17 76.89 5.31 d 29.08 1.39 a 29.61

Helow Wakan 66.50 e -3.29 e 42.96 b -1.50 e 43.13 76.07 -0.14 e 30.17 -0.15 e 30.19

Malasi Sograh 73.13 d 29.46 a 30.81 e 0.80 b 42.97 59.36 42.25 a 18.91 0.42 c 46.34

Malasi Wakan 83.54 a -0.08 c 46.67 a -0.02 c 46.70 59.77 41.78 ab 18.68 0.42 cd 45.81

Values marked with different letters in the same column indicate significant differences (P < .05); ns=not significant. the capital letters in the tables illustrate the difference of cultivars in same location while the small letters illustrate the difference of the same cultivar in different locations. Where L difference in lightness/darkness value. Negative (L) values indicate darkness and higher positive (L) values indicate a lightness. On the other hand, negative (a) values indicate green and higher positive (a) values indicate a red color. Higher positive (b) values indicate a more yellow skin color and negative (b) indicate a blue color. These values were then used to calculate hue degree, where 0° = red-purple, 90° = yellow, 180° = bluish green, and 270° = blue, and (Chroma), which indicates the intensity or color saturation (Selcuk and Erkan, 2015). Chroma was calculated using formulas Chroma = (a2 + b2)1/2 and Hue = arctan (b*/a*).



Table 2. Effect of locations and cultivars on Fruit physical quality parameters.

Location Cultivar

Mean fruit

Dependent Variable

FW (g) FD (mm)

CD (mm)

FL (mm)

FL1 (mm)

CL (mm) Nc NS PcMc

(g)

Ec (mm)

NSRs (%)NS

WakanHelow 261.49 Bc 80.15 Bb 23.04 Aa 68.53 Bb 82.89 Bb 14.36 a 6.10 112.79 Bc 4.31 B 55.55 A

Malasi 347.60 Ab 94.79 Ab 21.22 Ba 86.39 Ab 99.87 Ab 13.48 6.10 170.72 Ab 5.06 A 49.70 B

SograhHelow 392.83 b 90.30 Ba 18.86 Ab 83.53 Ba 93.29 Ba 9.76 b 6.47 172.63 Bb 4.71 A 55.30 A

Malasi 407.50 a 108.45 Aa 17.89 Ab 102.86 Aa 114.92 Aa 12.06 6.04 212.34 Aa 5.09 A 48.78 B

SaiqHelow 464.72 a 93.10 a 23.15 a 81.89 a 97.11 a 15.22 a 6.52 207.24 a 4.40 55.38

Malasi - - - - - - - - - -

P values

Year 0.6424 0.1462 <.0001 0.005 0.1374 0.0042 0.0257 0.0322 0.0014 <.0001

Location <.0001 0.0001 0.2051 <.0001 <.0001 0.0002 0.2244 <.0001 0.7176 0.9996

Cultivar 0.0082 <.0001 <.0001 <.0001 <.0001 0.4399 0.1422 <.0001 0.0328 0.0024

Location*Cultivar 0.0676 0.4478 0.4206 0.9303 0.4116 0.1416 0.0418 0.3175 0.3125 0.9010

Values marked with different letters in the same column indicate significant differences (P < .05); ns=not significant. The capital letters in the tables illus-trate the difference of cultivars in same location while the small letters illustrate the difference of the same cultivar in different locations. fruit weight (FW), total fruit length (FL), fruit length without calyx (FL1), calyx length (CL), fruit diameter (FD), calyx diameter (CD), number of carpels (Nc), rind weight plus weight of capillary membranes (PcMc), skin thickness (Ec) and arils yield (Rs).

Table 3. Effect of locations and cultivars on arils physical and chemical quality parameters.

Location Cultivar

Mean seed

Aril Physical Properties Aril Chemical Properties Seed Physical Properties

SW (mm)

SL (mm)

AW (mg)

JV (ml)

TSS(oBrix) TA MI W

(mm)L

(mm)WPW (mg) WPI %

WakanHelow 5.80 b 9.34 Ab 0.19 Bb 68.87 Bc 12.20 Bc 6.10 Ba 2.08 Ac 2.64 Bb 6.79 Aa 0.03 c 0.53 c

Malasi 6.04 a 8.50 Bb 0.26 Aa 105.75 Aa 16.23 Aa 22.94 Ab 0.82 Bb 3.63 Aa 6.28 Ba 0.03 b 0.50 b

SograhHelow 6.50 a 10.52 Aa 0.29 Aa 120.03 Ab 14.12 Bb 5.88 Ba 2.52 Ab 3.20 Aa 6.84 Aa 0.04 b 0.60 b

Malasi 5.82 b 9.39 Ba 0.25 Bb 109.64 Ba 16.41 Aa 26.65 Aa 0.66 Ba 2.66 Bb 6.32 Ba 0.04 a 0.62 a

Saiq Helow 5.92 b 9.56 b 0.30 a 134.10 a 15.65 a 4.75 b 3.96 a 2.70 b 6.64 a 0.041 a 0.74 a

P values

Location <.0001 <.0001 <.0001 <.0001 <.0001 0.0002 <.0001 0.0021 0.0215 <.0001 <.0001

Cultivar 0.1937 <.0001 0.0345 <.0001 <.0001 <.0001 <.0001 0.0023 <.0001 0.0331 0.2056

Location*Cultivar <.0001 0.9059 <.0001 <.0001 <.0001 <.0001 0.004 <.0001 0.4567 0.9485 0.8425

Cultivar*Location

Aril Physical Properties Aril Chemical Properties Seed Physical Properties

SW (mm)

NS

SL (mm)

NSAW *** JV (ml)*** TSS*** TA*** M1**

W (mm)

NS

L (mm)

NS

WPW NS

WPI NS

Helow Saiq 5.92 9.56 0.30 a 134.10 a 15.65 c 4.745cde 3.96 a 2.70 c 6.64 0.04 0.74

Helow Sograh 6.50 10.52 0.29 ab 120.03 b 14.12 d 5.88 cd 2.52 b 3.20 b 6.84 0.04 0.60

Helow Wakan 5.80 9.34 0.19 e 68.87 e 12.20 e 6.10 c 2.06 c 2.64 cde 6.79 0.03 0.53

Malasi Sograh 6.03 9.65 0.25 cd 112.30 bc 16.76 a 26.92 a 0.64 de 2.69 cd 6.43 0.03 0.58

Malasi Wakan 6.04 8.50 0.26 c 105.75 cd 16.23 b 22.94 b 0.82 d 3.63 a 6.28 0.03 0.50

Values marked with different letters in the same column indicate significant differences (P < .05); ns=not significant. The capital letters in the tables illus-trate the difference of cultivars in same location while the small letters illustrate the difference of the same cultivar in different locations. arils width (SW), arils length (SL), Aril weight (AW), juice volume (JV), total soluble solid (TSS), titratable acidity (TA), Maturity index (MI), seed width (W), seed length (L), woody portion weight (WPW) and woody portion index (WPI).

49Research Article


ConclusionThe results led to conclusion that Helow cultivar per-formed better in Saiq which was at the highest elevation as compared to those grown at mid-elevation in Sograh and at lower altitude in Wakan in terms of fruit color, fruit and aril physical and chemical quality parame-ters. As the elevation decreased the fruit and aril qual-ity of Helow cultivar also decreased. However, quality measurements of Malasi cultivar showed no differenc-es between Sograh and Wakan in fruit and arils color, physical and chemical quality parameters. Traditional pomegranate farmers by their inherited experience, rarely grow Malasi cultivar at higher elevations and they know for certain that the quality could not be the same as when it was grown at lower elevation. However, Helow, a highly popular cultivar, showed the opposite and quality was best at higher altitudes. The effect of micro-climate (light intensity, temperature and humid-ity) on the quality of pomegranate cultivars need to be studied with a wide range of cultivars and also on differ-ent deciduous fruit crops to determine their impact on fruit physical quality (such as color development) and edible chemical qualities, such as TSS & TA. This could help growers to select suitable cultivars for each eleva-tion and predict the future of pomegranate cultivation in marginal mountainous regions of the world, as tempera-ture might change due to global warming. The results of this study contributed to adaptation mechanisms of mit-igating the impact of climate change, particularly rising temperatures, which has significant importance in the conservation of local genotypes of deciduous fruit crops grown in Al-Hajar Mountain of Oman.

ReferencesAOAC. (2000). Official Methods of Analysis. Associa-

tion of Analytical Chemists, Rockville, MD, US.Al-Said FA, Al-Yahyai RA, Opara UL. (2013). Traditional

cultivation of pomegranate in Oman. Acta Horticul-ture 1007: 549-555.

Al-Said F, Opara L, Al-Yahyai R. (2009). Physico-chem-ical and textural quality attributes of pomegranate cultivars (Punica granatum L.) grown in the Sultanate of Oman. Journal of Food Engineering 90:129-134.

Al-Yahyai R, Al-Said F, Opara L. (2009). Fruit growth characteristics of four pomegranate cultivars from northern Oman. Fruits 64(6): 335-341.

Bilalis D, Krokida M, Roussis I, Papastylianou P, Trav-los I, Cheimona N, Dede A. (2018). Effects of organ-ic and inorganic fertilization on yield and quality of processing tomato (Lycopersicon esculentum Mill.). Folia Horticulturae 30(2): 321-332.

Boussaa F, Zaouay F, Burlo-Carbonell F, Noguera-Artia-ga L, Carbonell-Barrachina A, Melgarejo P, Mars, M. (2020). Growing Location Affects Physical Properties,

Bioactive Compounds, and Antioxidant Activity of Pomegranate Fruit (Punica granatum L. var. Gabsi). International Journal of Fruit Science 20(2): 508-523.

El-Salhy, AM, Ibrahim, RA, Abou-Zaid, EA, & Ali, MA. (2019). Comparative Study of some Pomegranate Cultivars (Punica granatum L.) Under Assiut Climat-ic Conditions. Assiut Journal of Agricultural Sciences 50(3): 134-149.

Eroğul D, Oğuz HI. (2018). Determining the Physi-co-Chemical Characterstics of the Rosehip Geno-types Grown Naturally in Adiyaman Province. Er-werbs-Obstbau 60(3): 195-201.

Hmid I, Hanine H, Elothmani D, Oukabli A. (2018). The physico-chemical characteristics of Morrocan pome-granate and evaluation of the antioxidant activity for their juices. Journal of the Saudi Society of Agricul-tural Sciences 17(3): 302-309.

Karagiannis E, Tanou G, Samiotaki M, Michailidis M, Diamantidis G, Minas IS, Molassiotis A. (2016). Comparative physiological and proteomic analy-sis reveal distinct regulation of peach skin quality traits by altitude. Frontiers in Plant Science 7: 1-14.

Kumar P, Sethi S, Sharma RR, Singh S, Saha S, Sharma VK, Varghese E. (2019). Influence of altitudinal vari-ation on the physical and biochemical characteristics of apple (Malus demostica). Indian Journal of Agri-cultural Sciences 89(1): 145-152.

Martínez-Nicolás, JJ, Galindo A, Griñán I, Rodríguez P, Cruz ZN, Martínez-Font R, Melgarejo P. (2019). Irrigation water saving during pomegranate flow-ering and fruit set period do not affect Wonderful and Mollar de Elche cultivars yield and fruit com-position. Agricultural Water Management 226: 1-1.

Mditshwa A, Fawole OA, Al-Said F, Al-Yahyai R, Opara UL. (2013). Phytochemical content, antioxidant ca-pacity and physicochemical properties of pomegran-ate grown in different microclimates in South Africa. South African Journal of Plant and Soil 30(2): 81-90.

Melgarejo P, Melgarejo-Sánchez P, Martínez JJ, Hernán-dez F, Legua P, Martínez R. (2013). The pomegranate tree in the world: new cultivars and uses. III Interna-tional Symposium on Pomegranate and Minor Medi-terranean Fruits 1089: 327-332.

Mphahlele RR, Caleb OJ, Fawole OA, Opara UL. (2016). Effects of different maturity stages and growing loca-tions on changes in chemical, biochemical and aro-ma volatile composition of ‘Wonderful’pomegranate juice. Journal of the Science of Food and Agriculture 96(3): 1002-1009.

Naryal A, Acharya S, Bhardwaj AK, Kant A, Chaurasia OP, Stobdan, T. (2019). Altitudinal effect on sugar contents and sugar profiles in dried apricot (Prunus armeniaca L.) fruit. Journal of Food Composition and Analysis 76: 27-32.



Nour V, Ionica ME, Trandafir I. (2015). Bioactive com-pounds, antioxidant activity and color of hydroponic tomato fruits at different stages of ripening. Notulae Botanicae Horti Agrobotanici Cluj- 43(2): 404-412.

Orazem P, Stampar F, Hudina M. (2011). Fruit quality of redhaven and royal glory peach cultivars on seven different rootstocks. Journal of Agricultural and Food Chemistry 59: 9394–401.

Peng Y, Wang G, Cao F, Fu, FF. (2020). Collection and evaluation of thirty-seven pomegranate germplasm resources. Applied Biological Chemistry 63(1): 1-15.

Sancho LE, Yahia EM, González-Aguilar, GA. (2011). Iden-tification and quantification of phenols, carotenoids, and vitamin C from papaya (Carica papaya L., cv. Maradol) fruit determined by HPLC-DAD-MS/MS-ESI. Food Research International 44(5): 1284-1291.

Selcuk N, Erkan M. (2015). Changes in phenolic com-pounds and antioxidant activity of sour–sweet pome-granates cv. ‘Hicaznar’during long-term storage un-der modified atmosphere packaging. Postharvest Biology and Technology 109: 30-39.

Solarte ME, Melgarejo LM, Martínez O, Hernández MS, Fernández-Trujillo, JP. (2014). Fruit quality during ripening of Colombian guava (Psidium guajava L.) grown at different altitudes. Journal of Food, Agricul-ture & Environment 12(2): 669-675.

ReseaRch aRticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 51–55DOI: 10.24200/jams.vol26iss2pp51-55Reveived 24 July 2020Accepted 17 Dec 2020

Seroprevalence of Trypanosoma evansi infections among dromedary camels (Camelus dromedaries) in North Ash-Sharqiya Governorate,

Sultanate of Oman

A. H. Al-Kharusi1, Elshafie I. Elshafie2,5*, K. E. M. Ali4, R. Al-Sinadi1, N. Baniuraba3, F. Al-Saifi1 and Y. Al-Mawali1

Elshafie I. Elshafie2,5*( ) [email protected], 1Ministry of Ag-riculture, Fisheries Wealth and Water Resources, Sultanate of Oman, 2Department of Animal and Veterinary Sciences, College of Agri-cultural and Marine Sciences, Sultan Qaboos University, Muscat PC. 123, Sultanate of Oman, 3Nizwa University, Sultanate of Oman, 4Veterinary Pharmacy, Abu Yahya AlAbrawi Trad, Sultanate of Oman, 5Central Veterinary Research Laboratory, Al Amarat, P.O. Box 8076, Khartoum, Sudan.

Introduction

Parasite remains a major constraint for optimum animal production throughout the world. Try-panosoma evansi, which belongs to the genus Try-

panosoma, subgenus Trypanozoon is a blood parasite that infects domestic livestock and wild animals; and caused disease called surra (Bargash et al., 2014). The parasite has a wide geographical distribution in many

الانتشار المصلي لعدوى المثـقبية الإيفانسية بين الإبل وحيدة السنام في محافظة شمال الشرقية، سلطنة عمان

أمل حمد الخروصية، الشفيع ابراهيم الشفيع، كمال على، راشد السنيدي، نادية بني عرابة، فاطمة السيفية، يحيى المعولي

Abstract. Trypanosoma evansi is a well-known hemoprotozoa that infects diverse domestic and wild animals world-wide and causes a devastating disease called surra. This research aimed to investigate seroprevalence of Trypanosoma evansi and its associated risk factors in dromedary camels in North Ash-Sharqiya Governorate, Sultanate of Oman. A total of 4364 serum samples was collected from three Willayat in North Ash-Sharqiya Governorate of Sultanate of Oman; Ibra (926, 21.2%), Qabil (1119, 25.6%) and Bidiyah (2319, 53.1%). Samples were examined for the presence of antibodies against T. evansi using card agglutination test for T. evansi (CATT/T. evansi). Binary logistic regression was used to study the association of T. evansi seroprevalence and risk factors such as location, gender, purpose and age of camels. The overall seroprevalence of T. evansi detected by CATT/T. evansi test was 38% (1659/4364, CI: 36.6-39.5%). There was a significant difference (p=0.001) between location and T. evansi seroprevalence, whereas the highest sero-prevalence was found in Ibra (49.9%, CI: 46.7-53.1%) followed by Bidiyah (35%, CI: 33-36.9%) and Qabil (34.5%, CI: 31.8-37%). Camels from Ibra were almost two times more likely to have circulating antibodies of T. evansi than camels from Bidiyah (OR=1.89, CI: 1.591-2.168). The results of this study showed a significant difference between seropreva-lence and sex (p=0.023), whereas the age of camels did not show any significant difference (p>0.05). To our knowledge, this is the initial research that indicated that T. evansi antibodies were circulating among camels in Oman, and further research needs to be tackled to study the molecular characterization of T. evansi and its prevalence in other animal species. Furthermore, cross-sectional studies of T. evansi from different regions in Oman warrant further investigation.

Keywords: Camels, T. evansi, CATT, Seroprevalence, Oman

الملخص:المثـقبيــة الإيفانســية هــو نــوع معــروف مــن الأوليــات وحيــدة الخليــة يصيــب الحيــوانات الأليفــة والبريــة المتنوعــة في جميــع أنحــاء العــالم ويســبب وحيــدة الإبــل في بهــا المرتبطــة الخطــر وعوامــل الإيفانســية للمثقبيــات المصلــي الانتشــار دراســة إلى البحــث هــذا يهــدف الزنبــور. يســمى مرضــا الســنام بمحافظــة شمــال الشــرقية، ســلطنة عمــان. تم جمــع 4364 عينــة مــن مصــل الــدم مــن ثــاث ولايات في محافظــة شمــال الشــرقية ســلطنة عمــان.

إبــراء )926، ٪21.2(، القابــل )1119، ٪25.6(، بديــة )2319، ٪53.1( تم فحــص وجــود الأجســام المضــادة ضــد المثـقبيــة الإيفانســية باســتخدام اختبــار تــراص البطاقــة للمثـقبيــة الإيفانســية )CATT(. تم اســتخدام الانحــدار اللوجســي الثنائــي لدراســة الارتبــاط بــن الانتشــار المصلــي للمثـقبيــة الإيفانســية وعوامــل الخطــر مثــل الموقــع والجنــس والغــرض والعمــر للإبــل. كان الانتشــار المصلــي الكلــي للمثـقبيــة الإيفانســية المكتشــف بواســطة اختبــار تــراص البطاقــة للمثـقبيــة الإيفانســية )CATT( 38% (1659/4364, CI: 36.6-39.5%(. كان هنــاك فــرق إحصائــي )p = 0.001( بــن الموقــع والانتشــار المصلــي )CI: 33-36.9٪ ،35٪( تليهــا بديــة )CI: 46.7-53.1٪ ،49.9٪( للمثـقبيــة الإيفانســية، حيــث تم العثــور علــى أعلــى معــدل انتشــار مصلــي في إبــراءوالقابــل )CI: 31.8-37٪ ،34.5٪(. كانــت الإبــل مــن إبــراء أكثــر عرضــة بمرتــن لوجــود الأجســام المضــادة المنتشــرة مــن المثـقبيــة الإيفانســية مقارنــة بجمــال بديــة )OR = 1.89، CI: 1.591-2.168(. أظهــرت النتائــج في هــذه الدراســة فرقــا احصائيــا بــن الانتشــار المصلــي والجنــس )p = 0.023(، بينمــا لم يظهــر عمــر الإبــل أي فــرق إحصائــي )p> 0.05(. علــى حــد علمنــا، هــذا هــو البحــث الأولي الــذي أشــار إلى أن الأجســام المضــادة للمثـقبيــة الإيفانســية توجــد بــن الإبــل في عمــان، وهنــاك الحاجــة إلى المزيــد مــن البحــث لدراســة خصائــص المثـقبيــة الإيفانســية وانتشــارها في أنــواع الحيــوانات الأخــرى، عــاوة

علــى ذلــك، يتطلــب مزيــدا مــن البحــث والدراســات للمثـقبيــة الإيفانســية في مناطــق مختلفــة مــن عمــان.الكلمات المفتاحية: الإبل، المثـقبية الإيفانسية، اختبار تراص البطاقة، الانتشار المصلي، سلطنة عمان


Seroprevalence of Trypanosoma evansi infections among dromedary camels (Camelus dromedaries) in North Ash-Sharqiya Governorate, Sultanate of Oman

tropical and subtropical countries due to the adaptation of mechanical transmission by different types of hema-tophagous flies, such as Tabanus, Stomoxys, Lyperosia and Haematobia species (Desquenes et al., 2013). The disease was reported in camels from different regions of the Kingdom of Saudi Arabia (AlTaqi et al., 2011; Amoudi et al., 2011; El-Wathiq et al., 2016), in Kuwait (Al-Taqi, 1989) and United Arab Emirates (Chaudhary and Iqbal, 2000). Camels along with horses and dogs are considered the principal hosts to the parasite and this may show symptoms, such as fever, anorexia, and edema (Abdel-Rady, 2008). The disease has a significant impact on animal’s health, production and efficiency and can result in death of animals if no timely treatment is offered. Some biochemical changes have been docu-mented in camels related to Trypanosoma infection in dromedary camels. (Sazmand et al., 2011). The disease causes infertility in the dromedary camels by changing plasma steroids concentration and semen characteris-tics (Al-Qarawi et al., 2004).

The disease can be diagnosed by parasitological methods, such as microhematocrit centrifugation technique and microscopic examination of thin blood smears (Babeker and Hassab, 2014; Bennoune et al., 2013; Bogale et al., 2012; Hagos, 2009) and serological methods such as ELISA and card agglutination test for T. evansi (CATT/T. evansi) (Babeker et al., 2014; Zayed et al., 2010; Hagos, 2009). The introduction of molecular diagnosis enhanced the accuracy of T. evansi detection due to the dynamics of parasitaemia (Baraghash et al., 2014; Tehseen et al., 2015). The Card agglutination test was more common to be used for screening a large num-bers of animals under field conditions (Uilenberg, 1998). On the other hand, the CATT test can render false posi-tive results due to the circulation of antibodies.

The estimated number of camels in the Sultanate of Oman is 242833 heads (Agriculture Censuses, 2013). The highest density of the camel population in Oman is located in the Dhofar Governorates, as most people use camels for milk and meat production. The second highest density of camels is in Ash-Sharqiya North Gov-ernorate with a total of 21577 camels and mostly are raced camels. Since the first detection of the parasite in 1984 (Srivastava,1984) and the continuing reports of the disease from the Ministry of Agriculture, Fisheries Wealth and Water Resources, Trypanosoma evansi was wandering in the country and negligible cohort study has been done to identify the frequency and risk factors of the disease in livestock. Due to lack of work on se-roprevalence of Trypanosoma among camel population in Oman, the present study was planned to determine the seroprevalence and risk factors of T. evansi in Omani camels in North Ash-Sharqiya Governorate using sero-logical techniques.


Study Area and Sampling CollectionThis study was conducted in three Willayat in North Ash-Sharqiyah (Ibra, Qabil and Bidiyah). A total of 4364 camel blood samples were collected between July 2014 and November 2015 from Ibra (283 farms), Qabil (260 farms) and Bidiyah (394 farms). Ten millilitres of blood was collected from jugular vein of each camel in a plain tube and transported in a cool box to the lab for screen-ing T. evansi using card agglutinin test (CATT/ T. evan-si). Information on location, sex, age and camel purpose were collected during blood sample collection. In this study, camels were divided into three groups according to age (<5, 5-10 and >10 years old).

Diagnosis of Serum by Serological ExaminationCard agglutination test for T. evansi kit (CATT/ T. evan-si) was used to detected anti-trypanosome antibodies in serum of infected animal by direct agglutination method according to the manufacturer’s instructions (Institute of Tropical Medicine, Antwerp, Belgium). The antigen contains fixed, freeze-dried and stained bloodstream from trypanosomes type RoTat 1.2, a predominant variable antigen type of Trypanosome evansi expressed during the early course of infection (Bajyana-Songa and Hamers, 1988). About 2.5 ml of CATT/T. evansi buffer was added to a vial of freeze dried CATT/ T. evansi anti-gen and shake the vial immediately for a few seconds to obtain homogeneous suspension. Then 0.5 ml of CAT-T/T. evansi buffer was added to a positive and negative control. On the test area of the card, one drop (45 μl) of the homogenized CATT/T. evansi antigen was added in each test area and 25 μl of the serum diluted at 1:4 with PBS pH 7.2 according to the manufacturer’s instructions was then added. The reaction was mixed using a stirring rod and the test card was rotated for 5 minutes for sub-sequent reading of the results.

Statistical AnalysisThe statistical analysis was conducted using SPSS version 20 (IBM, SPSS) at a = 0.05 significance level. Seropreva-lence and associated risk factors were conducted at 95% confidence level. Univariate analysis for individual risk factors to identify association between the seroprevalence and the potential risk factors were tested using Pearson Chi-square or Fisher Exact test. A binary logistic regres-sion was used to examine the significance that revealed by the univariate analysis and to determine odds ratio.

Results and DiscussionOut of 4364 blood samples examined using CATT/T. evansi, 1659 (38%, CI: 36.6-39.5%) were found to be se-ropositive for T. evansi (Table 1). The frequency of in-fection was high in Ibra 49.9% (462/926, CI: 46.7-53.1%)

53Research Article

Al-Kharusi, Elshafie, Ali, Sinadi, Baniuraba, Al-Saifi, Al-Mawali

followed by Bidiyah 35% (811/2319, CI: 33-36.9%) and Qabil 34.5% (386/1119, CI: 31.8-37%). There was sig-nificant difference between disease seroprevalence and location (x2 =70.43, p=0.001) (Table 2). Based on logistic regression, camels that sampled from Ibra region were 1.89 times more likely to have circulating antibodies against T. evansi than camels sampled from Bidiyah re-gion (OR=1.89, 95%CI: 1.591-2.168).

The results showed a significant difference between seroprevalence and sex (p=0.023). The female had high-est infection rate 38.7% (1435/3706) than male 34% (224/658). The female seropositive camels were about 1.2 times more likely than male camels. Moreover, there was no significant association between diseases seropreva-lence and the purpose (p=0.053). Despite the non-sig-nificance difference, camels used for production 38.6% (1488/3858) had a higher rate of being seropositive than racing camels 34.1% (168/493). On the other hand, there was no statistical significant difference between diseases seroprevalence and the age (p>0.05) (Table 1).

To our knowledge, this is the initial study that pro-vides information about the seroprevalence of T. evansi infections in three regions in Oman using serological test (CATT/T. evansi). The results showed significant

difference between diseases seroprevalence and camel sex and sample location. On the other hand, there is no significant difference between the diseases seropreva-lence with camel age and purpose of camels. The overall seroprevalence of T. evansi infections was found to be 38%. Our finding is relatively lower than the results re-ported in Saudi Arabia with a seroprevalence of 39.4% by card agglutination test with considerable differences between eastern and central regions (Al-Afaleq et al., 2015). The seroprevalence of this study was higher than

other studies done in Ethiopia by Bogale et al. (2012), Birhanu et al. (2015), Hagos et al. (2009), and in Somalia by Mohamoud (2017), who reported a prevalence of T. evansi in camels 18.22%, 13.76%, 24.88%, 15.9% respec-tively. However, our results of T. evansi seroprevalence was relatively lower than that reported in Sudan and Egypt as estimated to be 52.2% and 43.5% respectively (Babeker and Hassab Elrasoul, 2014; Abdel-Rady 2008). Since CATT/T. evansi cannot differentiate between cur-rent and past infections, the higher seroprevalence of T. evansi revealed by this research may be attributed either to genetic variation of camels breeds existed in same farms or weak farm management programs adopted by camel’s owner as the causative agent was reported in the country without comprehensive study to reveal its distribution. Trypanosoma evansi seroprevalence was higher in Ibra (49.9%) than Qabil and Bidiyah, this might be due to environmental factors as Ibra is a mountainous area and had wetland that may enhance the propagation of the parasite vectors, whereas Qabil and Bidiyah are sand areas with significantly less vector density.

In the present study, a significant difference was reported in camel sex, the highest seroprevalence of Trypanosoma evansi was observed in female 38.7% fol-lowed by male 34%. This result in accordance with that found by Babeker and Hassab Elrasoul (2014) and Mo-hamoud (2017). However, our results are not in line with study done by Bogale et al. (2012) which showed that a higher infection rates in males (20.25%) compared to female (17.72%) with approximately similar prevalence rates among both sexes. Study conducted by Bhutto et

Table 1. : Association of location, age and sex with seroprevalence of Trypanosoma evansi using card agglutination test (CATT/ T. evansi).

Risk factors No.CATT/ T. evansi

Chi-square P-valuePositive (%) Negative (%)

Location

IbraQabil

Bidiyah

92611192319

462 (49.9)386 (34.5)811 (35)

464 (50.1)733 (65.5)1508 (65)

70.43 0.001*

Age (years)

<55-10>10

15552152649

608 (39.1)811 (37.7)237 (36.5)

947 (60.9)1341 (62.3)412 (63.5)

1.49 0.47

Sex

MaleFemale

6583706

224 (34)1435 (38.7)

434 (66)2271 (61.3) 5.19 0.023*

Purpose

RaceProduction

4933858

168 (34.1)1488 (38.6)

325 (65.9)2370 (61.4) 3.74 0.053

*Significant association (p<0.05)


Seroprevalence of Trypanosoma evansi infections among dromedary camels (Camelus dromedaries) in North Ash-Sharqiya Governorate, Sultanate of Oman

al. (2010) indicated that females were more suscepti-ble to the infection with Trypanosoma species as host immunity decreased during pregnancy and lactation period. Despite the non-significant result of the age, we observed an increase in T. evansi seroprevalence in younger camels with age less than five years (39.1%) as compared to camels with age between five and ten years (37.7%). This study disagreed with previous studies, which found that adult camels were more susceptible to have the diseases than younger camels (Mohamoud, 2017; Atarhouch et al., 2003). Detection of antibodies against T. evansi in the host does not necessarily indi-cate a current infection since antibodies can persist for 2.3–22.6 months after trypanocidal treatment (Monzón et al., 2003). Therefore, younger camels of age less than five years have a higher chance of encountered antibod-ies against T. evansi in their blood compare to the elder one. In addition, younger camels are used to transport to different places in country for racing purposes and exposing these animals to infections. Camels used in production showed higher percentage of T. evansi sero-prevalence than camels using for race 34.1% and 38.6%, respectively. This might be because camel’s keepers care more about racing camels and keep them in open area for grazing, provide them with sufficient complementa-ry diet and treat them against parasites whereas, camels that used for production get less care from camel owner. This could also be due to disparity in management, vet-erinary care, and parasite control offered to race camels compared to production animals.

ConclusionTo our knowledge, this research was the initial report on T. evansi infections in Oman by using card agglutina-tion test (CATT/T. evansi). The results showed that the T. evansi was circulating in camels within the investigat-ed areas and certain potential risk factors may be asso-ciated with the spreading of the disease in the country. The disease might cause great economic losses due to impairment of camel’s health, which leads to decrease in production and performance. This study was done in North Ash-Sharqiya Governorate of Sultanate of Oman, so further studies are highly needed to investigate the prevalence of the diseases in different parts of Oman in different livestock using different diagnostic techniques.

AcknowledgementWe would like to thank the Agriculture Development Fund for supporting the project and all staff of General Directorate of Agriculture and Animal wealth of North and South Al-Sharqiya Governorate for their collabora-tion in samples collection.

Conflict of interestThe authors declare that they have no conflict of interest.

ReferencesAbdel-Rady A. (2008). Epidemiological studies (parasito-

logical, serological and molecular techniques) of Try-panosoma evansi infection in camels (Camelus drom-edaries) in Egypt. Veterinary World 1(11): 325-328.

Agriculture Censes. (2013). Ministry of Agriculture and Fisheries, The Sultanate of Oman.

Al-Faleq AI, Elamin EA, Fatani A, Homeida AM, (2015). Epidemiological Aspects of Camel Trypanosomosis in Saudi Arabia. Journal of Camel Practice and Re-search 22: 231-234.

Al-Qarawi AA, Omar HM, Abdel-Rahman HA, El-Mougy SA, El-Belely MS. (2004). Trypanosomi-asis-induced infertility in dromedary (Camelus dromedarius) bulls: changes in plasma steroids con-centration and semen characteristics, Animal Repro-duction Sciences 84:,73–82.

Al-Taqi MM. (1989). Characterisation of Trypanosoma (Trypanozoon) evansi from dromedary camels in Ku-wait by isoenzyme electrophoresis. Veterinary Para-sitology 32(2-3): 247-253

Amoudi MA, Al-Yousif M, Al-Shawa Y. (2011). Morpho-logical forms of Trypanosoma evansi from blood of Arabian camel (Camelus dromedaries) in the Riyadh Metropolitan areas. Journal of Egypt Society Parasi-tology (Cairo) 41: 29–34

Atarhouch TM, Rami M, Bendahman MN, Dakkak NA. (2003). Camel trypanosomisis in moroccol: Results of first epidemiology survey. Veterinary Parasitology 111: 277-286.

Babeker EA, Hassab YM. (2014). Incidence and treat-ment of camel trypanosomosis (Guffar) in West Om-durman in Sudan. Journal of Veterinary Advances 4(6): 582-593.

Bajyana S, Hamers R. (1988). A CATT test for veterinary use based on early VAT RoTat 1.2 of T. evansi. Ann Soc Belge Med Trop 63: 233-240.

Bhutto B, Gadahi G, Shah P, Dewani G, Arjo. (2010). Field investigation on the prevalence of trypanoso-miases in camels in relation to sex, age, breeds and herd size. Pakistan Veterinary Journal 30: 1-3.

Table 2. Binary logistic regression of T. evansi infections and associated camel’s location.

Locationβ SE- β

AOR (95% CI) P-value

Bidiyah 0.000 - 1.000 -

Ibra 0.619 0.079 1. 1.89 (1.591-2.168) 0.001*

Qabil -0.019 0.077 00.982 (0.845-1.141) 0.810

β: logistic coefficients; SE: standard error; AOR: adjusted odds ratio; CI: confidence interval; *Significant association (p<0.05)

55Research Article

Al-Kharusi, Elshafie, Ali, Sinadi, Baniuraba, Al-Saifi, Al-Mawali

Bennoune O, Adili N, Amri K, Bennecib L, Ayachi, A. (2013). Trypanosomiasis of camel (camelus drome-daries) in Algeria: First report, Veterinary Research Forum 4(4): 273-275.

Birhanu HA, Fikru R, Said M, Kidane W, Gebrehiwot T, Hagos A, Alemu T, Dawit T, Berkvens D, Goddeeris BM, Büscher P. (2015). Epidemiology of Trypano-soma evansi and Trypanosoma vivax in domestic animals from selected districts of Tigray and Afar regions, North Ethiopia. Parasites Vectors 8: 1-11 (Article 212).

Bogale B, Kelemework F, Chanie M. (2012). Trypano-mosis in camel (Camelus dromedaries) in Delo-Mena District, Bale Zne, Oromia Region, South West Ethi-opia. Acta Parasitologica Globalis 3(1): 12-15.

Chaudhary Z, Iqbal J. (2000). Incidence, biochemical and haematological alterations induced by natural trypanosomosis in racing dromedary camels. Acta Tropical 77(2): 209-213.

Desquesnes M, Holzmuller P, Lai DH, Dargantes A, Lun ZD, Jittaplapong S. (2013). Trypanosoma evansi and Surra: A review and perspective on origin, his-tory, distribution, taxonomy, morphology, hosts, and pathogenic effects. Biomed Research International 2013: 1-22.

El-Wathig M, Faye B, Thevenon S, Ravel S, Bossard G. (2016). Epidemiological surveys of camel trypano-somosis in Al-jouf, Saudi Arabia based on PCR and ELISA. Emirates Journal of Food Agriculture 28: 212–216.

Hagos A, Yilkal A, Esayass T, Alemu T, Fikru R, Fese-ha G, Goddeeris BM, Claes F. (2009). Prasitological and Serological Survey on Trypanosomis (Surra) in Camels in dry and wet areas of Bale Zone, Oromyia Region, Ethiopia. Revue de Medicine Veterinary 160 (12): 569-573.

Mohamoud AH. (2017). Sero-prevalence study of camel Trypanosomiasis in selected village of Galkayo, So-malia. Open Journal of Veterinary Medicine 7: 31-37.

Monzón CM, Mancebo OA, Russo AM. (2003). An-tibody levels by indirect ELISA test in Trypanoso-ma evansi infected horses following treatment with quinapyramine sulphate. Veterinary Parasitology 111: 59–63.

OIE. (2018). Manual of diagnostic tests and vaccines for terrestrial animal. Chapter, 3.4.16, World Organiza-tion for Animal Health, Paris, p. 1222-123.

Sazmand A, Rasooli A, Nouri M, Hamidinejat H, Hek-matimoghaddam S. (2011). Serobiochemical alter-ations in subclinically affected dromedary camels with Trypanosoma evansi in Iran. Pakistan Veteri-nary Journal 31(3): 223-226.

Srivastava VK, Obeid HM, Elbosadi SM. (1984). Try-panosomiasis in camels in the Sultanate of Oman. Tropical Animal Health and Production 16: 1-7 (Ar-ticle 148).

Uilenberg G. (1998). A Field guide for the diagnosis, treatment and prevention of African Animal Try-panosomosis, Food and Agriculture Organization of the United Nations. Rome, Italy.

Zayed AA, Habeeb SM, Allam NAT, Ashry HMZ, Mo-hamed AHH, Ashour AA, Taha HA. (2010). A Criti-cal Comparative study of Parasitological and Serolog-ical Differential Diagnostic Methods of Trypanosoma evansi Infections in Some Farm Animals in Egypt, American-Eurasian. Journal of Agricultural and En-vironmental Sciences 8(6): 633-642.

ReseaRch aRticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 56–63DOI: 10.24200/jams.vol26iss2pp56-63Received 11 Nov 2020Accepted 08 April 2021

Anti-diabetic Potential Properties of Two Edible Omani Wild Plants (Pteropyrum scoparium and Oxalis corniculata)

Iman R. S. Al-Qalhati, Mostafa I. Waly*, Lyutha Al-Subhi, Zaher Al-Attabi

Mostafa I. Waly*( ) [email protected], Department of Food Science and Nutrition, College of Agricultural and Marine Sciences, Sultan Qaboos University, P. O. Box 34-123, Sultanate of Oman

Introduction

Diabetes is a major health concern due to its high incidence coupled with complications includ-ing cardiovascular problems, renal failure, and

compromised immune system that in turn contribute to the increased mortality rate in adults (Waly et al.,

2010). Oxidative stress has been involved in the etiolo-gy of various human chronic diseases including diabetes (Suresh et al., 2017), and more than 1200 plant species have been suggested for the treatment of these diseases (Krishnaiah et al., 2011). Recent studies have declared the effectiveness of some therapeutic plants and herb-al preparations in the improvement of hyperglycemia (Petrovska, 2012). Edible wild plants are considered as natural therapeutic agents due to their antioxidant prop-erties, minimum side reactions, and low cost (Petrovska, 2012). The traditional use of plants as medicine precedes

الخصائص المحتملة المضادة لمرض السكري لاثنين من النباتات البرية العمانية: السيداف)Oxalis corniculata( و الحميض )Pteropyrum scoparium(

إيمان القلهاتي و مصطفى والي* و ليوثة الصبحي و زاهر العطابي Abstract. The use of plants for medicinal purposes has a long history worldwide. There is a lack of research that identifies the antidiabetic effect of edible Omani wild plants. Oxidative stress mediates the pathogenesis of diabetes and it has been suggested that natural antioxidants might be considered as an effective intervention for combating diabetes. This study aimed to assess the anti-diabetic and antioxidant potential properties of two edible Omani wild plants (Pteropyrum scoparium and Oxalis corniculata) or their mixture in streptozotocin (STZ)-induced diabetic rats. Thirty-seven male Sprague Dawley rats, weighing 250–300 g, were allocated into 5 groups: non-diabetic (9 rats/group), diabetic group (7 rats/group), and three diabetic groups that received oral feeding of either Pteropyrum scoparium, Oxalis corniculata, or their mixture (7 rats/group). Diabetes was induced by a single intraperitoneal injection dose of STZ drug, 50 mg/kg body weight. At the end of the experimental trial, after 8 weeks, all rats were fasted overnight and sacrificed; blood glucose was measured, meanwhile, pancreatic tissues were dissected and homogenized for the bio-chemical assessment of oxidative stress markers (glutathione, GSH, and total antioxidant capacity, TAC). STZ resulted in hyperglycemia and oxidative stress (GSH depletion and TAC impairment) in the diabetic group as compared to the non-diabetic group. Meanwhile, the concomitant treatment of diabetic groups with the two wild edible Omani plants or their mixture has shown a protective effect against the STZ-induced hyperglycemia, but with no effect on oxidative stress. It was noted that for the final body weight, the improvement was not significant. Histopathological examination of the pancreatic tissues showed that the STZ injection leads to pathological changes associated with diabetes in the pancreatic tissues of all diabetic groups. Pteropyrum scoparium and Oxalis corniculata combated the STZ-induced hyperglycemia with no effect on oxidative stress. There was no synergistic effect of Pteropyrum scoparium and Oxalis corniculata on hyperglycemia or oxidative stress.

Keywords: Diabetes, Pteropyrum scoparium, Oxalis corniculata, Oxidative Stress

الملخــص:إن اســتخدام النبــاتات للأغــراض الطبيــة لــه تاريــخ عريــق في جميــع أنحــاء العــالم، الا ان هنــاك نقــص في الأبحــاث الــي تحــدد تأثــر النبــاتات البريــة العمانيــة الصالحــة لــلأكل ضــد مــرض الســكري. يتســبب الإجهــاد التأكســدي في تغــرات فيزيولوجيــة مرتبطــة بمــرض الســكري، وتعتــبر مضــادات الأكســدة الطبيعيــة مــن التدخــات الفعالــة لتخفيــف درجــة الأكســدة الناتجــة عــن مــرض الســكري وبالتــالي التحكــم بــه. هدفــت هــذه الدراســة إلى تقييــم خصائــص مضــادات الأكســدة لاثنــن مــن النبــاتات البريــة العمانيــة الصالحــة لــلأكل وفعاليتهــا لضبــط مــرض الســكري، وهــي الســيداف Pteropyrum scoparium والحميــض Oxalis corniculata في الجــرذان المصابة بداء السكري اثر حقنها بمركب الستربتوزوتوسن )STZ(. ولقــــد اشــــتملت التجربــــة علــــى سبعة وثاثن ذكرا مــــن جرذان ســــالة ســــبراغ داولي ، بوزن 250-

300 جــرام ، مقســمة كالأتي: المجموعــــة الضابطــــة )9 جــرذان ( و المجموعــــة المصابــة بمــرض الســكري بعــد حقنهــا بمركــب STZ )7 جــرذان ( بينمــــا تلقــــت المجموعــــات الثاثــة الأخــرى )7 جــرذان / مجموعــة( مســــتخلصات أوراق الســيداف أو الحميضــة أو خليطهمــا بعــد حقنهــم بمركــب STZ . اســــتمرت التجربــــة لمــــدة 8 أســابيع و بعدها تم التضحية بالجرذان و تم قياس مستوى الجلوكوز في الدم ؛ كما تم تقييم مؤشرات الإجهاد التأكسدي في أنسجة البنكرياس لجميع الجرذان . وقد أظهــرت نتائــج هــــذه الدراســــة زيادة ملحوظة في نســبة جلوكوز الدم في الجرذان المصابة بمرض الســكري و كذلك نقص حاد في مســتوى مركب الجلوتاثيون ) GSH( و القدرة الخلوية الإجماليــة المضــادة للأكســدة )TAC( وكذلــك أظهــر الفحــص النســيجي لأنســجة البنكــرياس أن حقــن الجــرذان بمركــب STZ أدى إلى تغــرات مرضيــة مرتبطــة بمــرض الســكري في أنســجة البنكــرياس لجميــع مجموعــات داء الســكري. ومــن جانــب اخــر، أظهــر كلأ مــن الســيداف والحميــض علــى حــدى تأثـيـــرا خافضــا لجلوكــوز الــدم دون تأثر على الإجهاد التأكســــدي المرتبــــط بمرض الســكري، إلا أن خليط هذه النباتات لم يظهر أي تأثر تآزري ســواء على مســتوى جلوكوز الدم أو الاجهاد التاكســدي.

الكلمات المفتاحية: مرض السكري ، الإجهاد التأكسدي ، النباتات البرية العمانية )السيداف و الحميض(.

57Research Article

Al-Qalhati, Waly, Al-Subhi, Al-Attabi

modern medicine throughout the world (World Health Organization, 2009). According to the World Health Or-ganization, almost 80% of the people in the world used medicinal plants for their primary health care (World Health Organization, 2009). There are many natural products that have been isolated from plants such as fla-vonoids, phenolics, curcuminoids, tannins, coumarins, xanthones, terpenoids, and lignans (Jeong et al., 2004). In addition, synthetic antioxidants like butylated hy-droxytoluene (BHT), tert-butylhydroquinone (TBHQ), and butylated hydroxyanisole (BHA) are manufactured chemically and used in the food industry because they are more effective and cheaper than natural antioxidants (Lourenco et al., 2019). But, the use of synthetic anti-oxidants as food additives has raised some concerns re-lated to their potential health problems and toxicity as TBHQ, BHA and BHT might be carcinogenic and had been banned in several western countries (Lourenco et al., 2019). Therefore, there is a lot of potential commer-cial use of natural antioxidants from plant extracts as an alternative for artificial synthetic ones.

There are numerous edible indigenous plant species in the Gulf Region, but there are limited studies about the health aspects of these plants in the daily food sup-ply chain (Al-Attabi et al., 2015). Oxalis corniculata is a cosmopolitan weed spreading with a slim stem covered with rounded tipped hairs (Brown, 1989). It is commonly known as “sour grass” (Pickering et al., 2008). It grows in shady moist places and traditionally, was used for treat-ing wounds and certain diseases (Pickering et al., 2008).

Pteropyrum scoparium grows mainly in February af-ter the rainy season in December. It is used in the tradi-tional food in which it is mixed with dried anchovies. The leaves were used medicinally for blood purification and the treatment of indigestion (Al-Badi, 2011). Streptozo-tocin (STZ) is a potent diabetic-inducing agent common-ly used in rats; the STZ effect is mediated by oxidative stress in pancreatic cells (Al-Maskari et al., 2012). STZ induces diabetes in experimental animals via a mecha-nism that is mediated by glutathione (GSH) depletion and impairing total antioxidant capacity in pancreatic cells of rats (Al-Maskari et al., 2012). GSH is a tripeptide and acts as a part of the defense system against oxidative stress compounds like reactive oxygen and nitrogen spe-cies (Waly et al., 2015). GSH acts as antioxidants since it is a carrier for the active thiol group, and has a direct an-tioxidant effect through interacting with electrophiles, reactive oxygen, or nitrogen (Waly et al., 2015). Oxida-tive stress in pancreatic tissue is a condition under which GSH and antioxidant enzymes (glutathione peroxidase, superoxide dismutase, and catalase) are not counter-balancing ROS, and subsequently, induce pancreatic cellular damage (Unuofin and Lebelo, 2020; Matough et al., 2012). Oman region is rich in medicinal plants with antioxidant properties, therefore understanding the biological aspects of these plants in relation to oxida-tive-stress mediated diabetes might be considered as an

effective dietary intervention in the primary prevention of diabetes. In the current study, we aimed to assess the biochemical significance of two edible Omani indige-nous plants (Pteropyrum scoparium and Oxalis cornic-ulata) using an in vivo experimental model for diabetes.

Methods

Plants PreparationThe two edible Omani wild plants, Pteropyrum scopar-ium and Oxalis corniculata, were freshly collected in October 2014 from two areas, Nizwa and Sur, and were identified by a specialized botanist from the Crop Scienc-es Department at the College of Agricultural and Marine Sciences, Sultan Qaboos University. The leaves of the col-lected plant were separated from the undesirable mate-rials. Then the leaves were washed and rinsed by distilled water and dried by free zone 6-liter benchtop freeze dry system (Labconco, USA) at -40 ºC. The dried leaves were powdered by an electrical grinder (PHILIPS, HR2027). One gram of the dried powder was mixed with 50 mL distilled water. At the end, the mixture was stored in air-tight container at -40 ºC until used for later experiments.

Experimental Animals Thirty-seven adult Sprague Dawley male rats weighing approximately 250-300 g were used in this study. Ani-mals were adapted to the animal house conditions for one week before starting the experiment. Animals were housed in standard laboratory room conditions at 23±2 ºC, with a 12 h light/dark cycle, relative humidity of 55±10 % and were maintained with free access to stan-dard diet and tap water. The standard diet was acquired from Oman Flour Mills Company (Muscat, Oman). All the animal procedures were implemented accordingly to the “Guide for the Care and use of Laboratory Animals” published by the National Institutes of Health. An eth-ical approval from University Animal Research Ethics Committee was obtained (SQU/AEC/2010-11).

Experimental Design and Diabetes InductionThe thirty seven rats were randomly allocated into five groups as follow: Non-diabetic control rats (n=9) that fed standard diet, Diabetic control rats (n=7) that were injected with STZ and fed standard diet, Diabetic rats (n=7) that were injected with STZ and fed standard diet and an oral dose of Pteropyrum scoparium extract (5 ml/week), Diabetic rats (n=7) that were injected with STZ and fed standard diet and an oral dose of Oxalis corniculata extract (5 ml/week), Diabetic rats (n=7) that were injected with STZ and fed standard diet and an oral dose of a mixture of the extracts of both plants (10 ml/week). The oral dose supplementations were carried out in the same day and time on weekly basis for all groups.

The experiment was carried out for 8 weeks. Through-out the experimental period, all rats were weighed once a



week, using a laboratory scale (Electronic Balance kern; PCB 6000-0) to the nearest gram. The allocated diabetic groups were injected with a single intra peritoneal injec-tion of STZ (50 mg/ kg body weight) while the non-dia-betic group received a single intra peritoneal injection of 0.1 M citrate buffer solution. STZ was purchased from Sigma-Aldrich Chemical Company (product number S0130), and dissolved in a freshly prepared 0.1 M citrate buffer (pH 4.5). Diabetes was confirmed after three days of the STZ injection by measuring blood glucose. Brief-ly, the diabetic rats were fasted overnight and the distal part of each rat’s tail was lightly snipped; the first blood drop was discarded and the second drop was absorbed by a test strip inserted in a portable glucose meter (One Touch II; Johnson & Johnson, Milpitas, CA, USA).The blood glucose level for all rats in the diabetic groups was ≥ 200 mg/dl.

Animals Sacrifice and Pancreatic Tissue HomogenizationAfter eight weeks of the experiment, all rats were fasted overnight and blood samples were taken from the tails to measure blood glucose level. Then all rats were anesthe-tized with a lethal dose of a mixture of ketamine (1 mg), xylazine (5 mg) and acepromazine (0.2 mg). The pancre-as was dissected and removed. Small pieces of the pan-creatic tissues were placed in 10% of formalin for histo-pathological examination. The rest of pancreas samples (2 g) were homogenized in 0.1 M phosphate buffer and centrifuged at 4000 rpm at 4°C for 5 minutes. The re-sulting supernatants were used for protein content mea-surement using the Lowry’s method (Lowry et al., 1951) and for biochemical measurements of glutathione and total antioxidant capacity.

Biochemical Measurements The Glutathione (GSH) was measured using the GSH assay kit from Biovision Company (kit number; K251). The assay uses a dye that forms an adduct with glutathi-one which is monochlorobimane (MCB). The unbound MCB is mainly non fluorescent, while the dye fluoresces blue when bound to glutathione. This reaction is cata-lyzed by glutathione S-transferase. The assay identifies both reduced and oxidized glutathione.

Total antioxidants capacity (TAC) was estimated using assay kit from Biovison Company (kit number; K274), which can measure both the small molecule an-tioxidants and proteins or small molecules alone in the presence of protein Mask. Cu²+ ion is converted to Cu+ by both small molecule and protein. The Protein Mask prevents Cu²+ reduction by protein, enabling the analy-sis of only the small molecule antioxidants. The reduced Cu+ ion is chelated with a colorimetric probe giving a broad absorbance peak around 570 nm, relative to the total antioxidant capacity.

Histopathological ExaminationPancreatic tissues saved in 10% formalin at room tem-perature were used to study their histological structures. The fixed specimens were dehydrated in graded ethanol, cleared in xylene and embedded in paraffin wax. Tissue blocks were sectioned into 10 μm thickness using rotary microtome (Thermo Scientific STP120, Thermo Fisher Scientific UK Ltd.). The sections were stained by hema-toxylin and eosin (H&E) to examine the pancreatic tissues under conventional light microscope by a pathologist.

Statistical AnalysisThe statistical analysis was performed using one-way analysis of variance (ANOVA) followed by Tukey’s test using GraphPad Prism (version 5.03; GraphPad Soft-ware Inc. San Diego, CA). P<0.05 is considered as statis-tically significant. The results are expressed as means ± Standard Error of Means (SEM).

Results

Final Body WeightThe effect of the treatment with Pteropyrum scoparium, Oxalis corniculata or their mixture on body weight in all groups is presented in Figure 1. The results exhibited that the diabetic control group showed a significant reduc-tion in the final body weight as compared to the non-di-abetic group, P< 0.05. Diabetic groups treated with Pteropyrum scoparium, Oxalis corniculata or their mix-ture showed an improvement in the final body weight, although the differences were not significant (P> 0.05)

Fasting Blood Glucose Levels after Animal’s SacrificeFigure 2 illustrates the effect of Pteropyrum scoparium, Oxalis corniculata and their mixture on the fasting blood glucose level. STZ injection induced a significant in-crease in fasting blood glucose level of all diabetic groups as compared with the non-diabetic group, P<0.05. Feed-ing diabetic groups with Pteropyrum scoparium, Oxal-is corniculata or their mixture positively ameliorated the elevation of blood glucose level as compared to the diabetic control group, but not significantly (P>0.05).

Pancreatic Tissue Antioxidants Markers Table 1 presented the potential effect of Pteropyrum sco-parium, Oxalis corniculata or their mixture on the cel-lular antioxidants markers (GSH and TAC). In all diabet-ic groups (treated and untreated), there was a depletion in the GSH level compared to the non-diabetic control group (P<0.05). There was a significant impairment of TAC level of the diabetic groups treated with the extracts of Pteropyrum scoparium, Oxalis corniculata and their mixture as compared to control non-diabetic group.

59Research Article


Histopathological Examination Figure 3 shows the histological appearance of the pan-creatic islet cells of all experimental groups. The pan-creatic section from the non-diabetic control group showed the normal histological structure of pancreatic cells with increased size and cellularity of the cells (Fig-ure 3.A). On the other hand, microscopic examination of the pancreatic sections of the diabetic control rats revealed decreased size and number of lymphocytes of β-cells of islets of Langerhans (Figure 3.B). Figures 4C-E represents the pancreatic sections of the diabet-ic rats that were treated with Pteropyrum scoparium, Oxalis corniculata and their mixture, respectively. A mild to chronic lymphocytic infiltration is noted be-tween acini in Figure 3.C; cystic dilatation of pancre-atic duct was detected in Figure 3D and a congestion of pancreatic blood vessel was observed in Figure 3E.

Discussion

There is an increasing effort in searching for plants prod-ucts possessing anti-diabetic activity with fewer side ef-fects. Diabetes is a challenging metabolic disease that affects the population worldwide (Pradeepa et al., 2013). The total number of people with diabetes in the globe is estimated to increase sharply in the future (Abdul Sani et al., 2014). Several treatments were used to cure diabetes mellitus, yet these treatments have limitations and un-desirable effects (Pradeepa et al., 2013). Therefore, there was an increasing effort in searching for plant products possessing anti-diabetic activity with fewer side effects (Habibuddin et al., 2008). The recent scientific studies as the traditional practices believed that the combination of many plants will be more efficient than using a single plant (Ogbonnia et al., 2008).

Few studies revealed the effect of Oxalice cornicula-ta in diabetic animal models (Agila, 2012), while there

is no study conducted with Pteropyrum scoparuim or the combination of these two plants. The present study has been undertaken to assess the effect of Pteropyrum scoparuim, Oxalice corniculata and their mixture in STZ-induced diabetic model. In the present study, the diabetic control group showed a significant decrease in the final body weight compared with non-diabetic group. The obtained findings were in agreement with a previous reported that the injection of STZ has been related with body weight loss because of the elevation in protein catabolism and muscle wasting. Moreover, the lack of insulin secretion leads to unavailability of carbo-hydrate which is a source of energy resulting in the ob-served body weight loss among the diabetic groups. This finding is consistent with what was reported earlier that administration of 50 mg /kg of STZ resulted in a signif-icant reduction in the body weight of diabetic animals (Suresh et al., 2017; Waly et al., 2015). There were no previous studies to verify the effect of supplementation with Pteropyrum scoparium, Oxalis corniculata or their mixture on the body weight of STZ-diabetic rats. Our results showed an improvement trend in the final body weight of all three treated diabetic groups compared to the untreated diabetic control group. However, the ob-tained results were not significant and this may be due to the size of the dose used which might have not been enough to relief the weight loss resulting from the dia-betes insult.

In our study, STZ-induced diabetic control rats showed a significantly elevation in the fasting blood glu-cose level when compared with the control non diabet-ic group, P<0.05. A similar result was reported earlier which stated that STZ in a dose of 50 mg/kg induced di-abetes in the experimental animals (Suresh et al., 2017). Diabetes mellitus is characterized by a disturbance of glucose homeostasis and adversely affects carbohy-drates, fat, and protein metabolism due to lack of insu-

Figure 1. Final body weight in the rat groups aAll the diabetic groups had significantly lower body weight than the non-diabetic group, P< 0.05.



lin (Waly et al., 2015). The increase in the blood glucose level is attributed to the cytotoxic effect of STZ on pan-creatic cells (Waly et al., 2015). In addition, STZ leads to destruction of β-cells of Islets of Langerhans and mal-functioning of the pancreas resulting in the blood glucose elevation (Sung et al., 2019; Agila and Kavitha, 2012).

Furthermore, our study revealed amelioration in the fasting blood glucose levels of all the treated diabetic groups. In contrast to our findings with respect to Ox-alis corniculata, it was demonstrated that a single daily

oral administration of an aqueous extract of Oxalis cor-niculata (100 mg/kg body weight) caused a significant reduction in the blood glucose in Alloxan-induced di-abetic mice when treated for a period of ten days (do Prado et al., 2020). The results observed in our study are based on a different dose and feeding duration. On the other hand, there were no studies to compare the results obtained from treating diabetic animals with Pteropyrum scoparium or the mixture of two plants. Long term of untreated hyperglycemia in diabetes is as-

Figure 2. Fasting blood glucose measurements in the rat groups. All the diabetic groups treated with Pteropyrum scopari-um, Oxalis corniculata or their mixture positively ameliorated the elevation of blood glucose level as compared to diabetic control group, but not significantly, P>0.05 a, bSimilar superscripts are not significantly different.

Figure 3. Histopathological examination of the pancreatic tissues of rat groups (H&E stain x 400). Section A: pancre-atic tissue of the non-diabetic group consisting of acini; ducts and islets of Langerhans with no evidence of inflammation and necrosis. Section B: pancreatic tissue of the diabetic group; the islets are small (atrophic) and a few lymphocytes (black arrow) are noted. Section C: Diabetic + Pteropyrum scoparium; occasional islets show moderate chronic inflammatory cells infiltrate (black arrow) and necrosis (red arrow) with mild lymphocytic infiltration noted between acini (black arrow). Section D: Diabetic + Oxalis corniculata; show dilated and congested blood vessels (black arrow). Section E: Diabetic + Pteropyrum scoparium & Oxalis corniculata; show moderate number of lymphocytes (black arrow), occasional single cell necrosis (red arrow) and dilated ducts (large black arrow). No improvement in the STZ-mediated pathological effects were seen in any of the three treated groups.

61Research Article


sociated with oxidative stress generating from glucose autoxidation, protein glycation and glycoxidation lead-ing to tissue injury and damage (do Prado et al., 2020). Induction of STZ generates H2O2 and increased the production of free radicals in vitro as well as in vivo in-creasing the oxidative stress level (Balaji et al., 2020).

Those reactive free radical species generated by STZ contribute to DNA fragmentation and induce other damaging changes in the cells. The formation of superoxide anions could be a result of STZ action or/and an increased activity of xanthine oxidase on mito-chondria (Hassanzadeh et al., 2019). Thus high blood glucose level induces a damage to the body by many mechanisms that lastly leads to cellular stress (Jakus, 2000). In the present study, STZ-induced diabetic rats showed a depletion trend in the glutathione level. Sim-ilar results were observed in the three treated diabetic groups. Such a finding could be due to hyperglycemia which causes osmotic stress to cells by increasing the movement of glucose through polyol pathway and the production of sorbitol that consumes dihydronicotine amide adenine dinucleotide phosphate causing deple-tion in intracellular glutathione (Pradeepa et al., 2014).

It was reported that the best solvents of extracting the flavonoid from Oxalis corniculata are the polar solvents such as methanol and water (Al Qalhati, 2016). Moreover, the polar solvents like the ethanolic extract of Pteropy-rum scoparium showed better free radical scavenging ac-tivity indicating that the Pteropyrum scoparium is a rich source of some antioxidants constituents like epicate-chin-3-O-gallate (Al Qalhati, 2016). In the present study the plants extracts were aqueous-based, and the results obtained in our study showed a significant impairment of total antioxidants capacity in the three treated groups.

STZ as a diabetic insult is causing specific cytotox-icity to β-cells of the pancreas (Waly et al., 2015). It generates high level of free radicals causing DNA frag-mentation of ß cells and cells necrosis which leads to decreasing the level of insulin and increasing the blood glucose level (Suresh et al., 2017). The microscopic ex-

amination of the pancreatic tissue of the diabetic control group is in conformity with what was reported earlier that atrophy of β-cells of islets of Langerhans, necrosis along with cystic dilatation of pancreatic duct, reduc-tion in cells size, decrease cellularity, and congestion of pancreatic blood vessels (Kakkar et al., 1998). These changes in pancreatic cells can be attributed to the STZ cytotoxicity causing a destruction of β-cells of the pan-creas (Khattab et al., 2013). Also, this effect may be ex-plained by generation of H2O2 in the pancreatic β-cells by induction of STZ causing DNA fragmentation. In addition, the hyperglycemia stimulates the production of free radicals causing cell dysfunction and damaging the pancreatic cells (Singab et al., 2014). The microscop-ic examination of the pancreatic tissues of the treated diabetic groups showed no histopathological changes indicating that treatment with Pteropyrum scopari-um, Oxalis corniculata or their mixture have any ef-fect on the pancreatic tissues. This may be due to the increase in the oxidative stress (Srikanth et al., 2012).

ConclusionIn conclusion, our study demonstrated that STZ induced diabetes and oxidative stress in the experimental rat model. In addition, it indicated that Pteropyrum scopar-ium, Oxalis corniculata, and their mixture improved the STZ-induced hyperglycemia and the final body weight but not significantly. Neither the two plants nor their mixture has an effect on the cellular antioxidant markers or the histopathological changes in pancreatic tissues. There was no significant synergistic effect of the two plants (Pteropyrum scoparium and Oxalis corniculata) on STZ-induced diabetes and oxidative stress. Further research is needed to investigate the dose and time-de-pendent attributes of Pteropyrum scoparium and/or Ox-alis corniculata in relation to diabetes.

Table 1. . Biochemical measurements of glutathione (GSH) and total antioxidant capacity (TAC) in the rat groups.

Antioxidant Marker

Group GSH(ng/mg protein)

TAC(ng/mg protein)

Non-diabetic 1.24 ±0.17 251.16 ±64.11

Diabetic *0.89 ± 0.24 *143.71 ± 34.15

Diabetic + Pteropyrum scoparium 0.70 ± 0.16 82.23 ± 20.41

Diabetic + Oxalis corniculata 0.75 ± 0.13 73.4 ± 11.13

Diabetic + Pteropyrum scoparium & Oxalis corniculata 0.72 ± 0.09 68.10 ± 5.44

*Significantly lower than non-diabetic group, P< 0.05.In all diabetic treated and non-treated groups there was depletion in the GSH level compared to the control non-diabetic group but this depletion was not significant P>0.05. Meanwhile, a significant impairment of TAC level of diabetic groups treated with Pteropy-rum scoparium, Oxalis corniculata or their mixture was observed as compared to control non-diabetic group.



ReferencesAbdul Sani NF, Belani LK, Pui Sin C, Abdul Rahman

SNA, Das S, Zar Chi T,Yusof YAM. (2014). Effect of the combination of gelam honey and ginger on ox-idative stress and metabolic profile in streptozoto-cin-induced diabetic Sprague-Dawley rats. Biomed Research International 2014:1-9.

Agila K. (2012). Antidiabetic, antihyperlipidaemic and antioxidant activity of Oxalis corniculata in alloxan induced diabetic mice. Journal of Natural Sciences Research 2(7): 9-17.

Al Qalhati I. 2016. Anti-diabetic Effect of Pteropyrum scoparium, Oxalis corniculata and Their Mixture in Rats, M. Sc. Thesis, Sultan Qaboos University, Oman.

Al-Attabi Z, AlMamri R, Al AbdAslam K. (2015). Antiox-idant potential properties of three Wild Omani plants against hydrogen peroxide-induced oxidative stress. Canadian Journal of Clinical Nutrition 3(2): 16-22.

Al-Maskari MY, Waly MI, Ali A, Al-Shuaibi YS, Ouh-tit A. (2012). Folate and vitamin B12 deficiency and hyperhomocysteinemia promote oxidative stress in adult type 2 diabetes. Nutrition 28: 23-26.

Balaji P, Madhanraj R, Rameshkumar K, Veeramanikan-dan V, Eyini M, Arun A, Thulasinathan B, Al Farraj DA, Elshikh MS, Alokda AM, Mahmoud AH, Tack JC, Kim HJ. (2020). Evaluation of antidiabetic activity of Pleurotus pulmonarius against streptozotocin-nic-otinamide induced diabetic wistar albino rats. Saudi Journal of Biological Science 27(3): 913-924.

Brown CE. (1989). Medicinal and Other Uses of North American Plants: A Historical Survey with Special Reference to the Eastern Indian Tribes. Dover Publi-cations Inc., pp 1-510.

do Prado FC, Vieira WF, Fernandes de Magalhaes S, Bonet IJM, Tambeli CH, Parada CA. (2020). The onset speed of hyperglycemia is important to the development of neuropathic hyperalgesia in strep-tozotocin-induced diabetic rats. European Journal of Neuroscience 52: 3642-3651.

Habibuddin M, Daghriri HA, Humaira T, Al Qahtani MS, Hefzi AAH. (2008). Antidiabetic effect of alco-holic extract of Caralluma sinaica L. on streptozoto-cin-induced diabetic rabbits. Journal of Ethnophar-macology 117(2): 215-220.

Hassanzadeh KN, Kim EY, Dryer SE. (2019). TRPC6 inac-tivation does not protect against diabetic kidney dis-ease in streptozotocin (STZ)-treated Sprague-Daw-ley rats. FASEB Bioadvances 1(12):773-782.

Jakus V. (2000). The role of free radicals, oxidative stress and antioxidant systems in diabetic vascular disease. Bratislavske Lekarske Listy 101(10): 541-551.

Jeong SM, Kim SY, Kim DR, Jo SC, Nam KC, Ahn DU, Lee SC. (2004). Effect of heat treatment on the anti-

oxidant activity of extracts from citrus peels. Journal of Agricultural Food Chemistry 52(11): 3389-93.

Kakkar R, Mantha SV, Radhi J, Prasad K, Kalra J. (1998). Increased oxidative stress in rat liver and pancreas during progression of streptozotocin-induced diabe-tes. Clinical Science 94(6): 623-632.

Khattab HA, Al-Amoudi NS, Al-Faleh A. (2013). Effect of Ginger, Curcumin and Their Mixture on Blood Glucose and Lipids in Diabetic Rats. Life Science Journal 10(4): 428-442.

Krishnaiah D, Sarbatly D, Nithyanandam R. (2011). A review of the antioxidant potential of medicinal plant species. Food and Bioproducts Processing 89(3): 217-233.

Lourenço SC, Moldao-Martins M, Alves VD. (2019). Antioxidants of Natural Plant Origins: From Sourc-es to Food Industry Applications. Molecules 24(22): 1-25 (Article 4132).

Lowry OH, Rosebrough NJ, Farr AL, Randall RJ. (1951). Protein measurement with the Folin phenol reagent. Journal of Biological Chemistry 193: 265-275.

Matough FA, Budin SB, Hamid ZA, Alwahaibi N, Mo-hamed J. (2012). The role of oxidative stress and an-tioxidants in diabetic complications. Sultan Qaboos University Medical Journal 12(1): 5-18.

Al-Badi MSM. (2011). Oligomeric pronthocyandins from Petropyrum scoparium and their antioxidant proper-ties. Sultan Qaboos University, M. Sc. Thesis, Oman.

Ogbonnia SO, Odimegwu JI, Enwuru VN. (2008). Evalu-ation of hypoglycaemic and hypolipidaemic effects of aqueous ethanolic extracts of Treculia africana Dec-ne and Bryophyllum pinnatum, Lam and their mix-ture on streptozotocin (STZ)-induced diabetic rats. African Journal of Biotechnology 7(15): 2535-2539.

Petrovska BB. (2012). Historical review of medicinal plants’ usage. Pharmacognosy Reviews 6(11): 1-5.

Pickering H, Patzelt A. (2008). Field guide to the wild plants of Oman: Royal Botanic Gardens, Oman.

Pradeepa S, Subramanian S, Kaviyarasan V. (2013). Biochemical evaluation of antidiabetic properties of Pithecellobium dulce fruits studied in streptozoto-cin induced experimental diabetic rats. International Journal of Herbal Medicine 1(4): 21-28.

Pradeepa S, Subramanian S, Kaviyarasan V. (2014). Antioxidant role of Pithecellobium dulce fruit pulp extract in ameliorating hyperglycemia induced oxi-dative stress studied in streptozotocin induced exper-imental diabetic rats. Journal of Pharmacy Research 8(3): 377-384.

Qihui L, Shuntian D, Xin Z, Xiaoxia Y, Zhongpei C. (2020). Protection of curcumin against streptozo-cin-induced pancreatic cell destruction in T2D rats. Planta Medica 86(2): 113-120.

63Research Article


Singab AN, Youssef FS, Ashour ML. (2014). Medicinal plants with potential antidiabetic activity and their assessment. Med Aromat Plants 3(1): 151-156.

Srikanth M, Swetha T, Veeresh B. (2012). Phytochem-istry and pharmacology of Oxalis corniculata Linn. International Journal of Pharmaceutical Sciences and Research 3(11): 1-12.

Sung Y, Jeong J, Kang RJ, Choi M, Park S, Kwon W, Lee J, Jang S, Park SJ, Kim SH, Yi J, Choi SK, Lee MH, Liu K, Dong Z, Ryoo ZY, Kim MO. (2019). Lin28a expression protects against streptozotocin-induced β-cell destruction and prevents diabetes in mice. Cell Biochemisty and Function 37(3):139-147.

Suresh S, Waly MI, Rahman MS, Guizani N, Al-Kindi MAB, Al-Issaei HKA, Al-Maskari SNM, Al-Ruqa-ishi BRS, Al-Salami A. Broccoli (Brassica oleracea). (2017). Reduces oxidative damage to pancreatic tissue and combats hyperglycaemia in diabetic rats. Preven-tive Nutrition and Food Science 22(4): 277-284.

Tripathi BK, Srivastava AK. (2006). Diabetes mellitus: Complications and therapeutics. Medical Science Monitor 12(7): RA130-147.

Unuofin JO, Lebelo SL. (2020). Antioxidant effects and mechanisms of medicinal plants and their bioactive compounds for the prevention and treatment of type 2 diabetes: An Updated Review. Oxidative Medicine Cellular Longevity 2020: 1-36 (Article 1356893).

Waly MI, Ali A, Essa MM, Al-Shuaibi Y, Al-Farsi YM. (2010). The global burden of type 2 diabetes: A re-view. International Journal of Biological Medical Re-search 1(4): 326-329.

Waly MI, Guizani N, Suresh S, Rahman MS. (2015). Ginger extract attenuates preliminary steps of strep-tozotocin-mediated oxidative stress in diabetic rats. International Journal of Nutrition, Pharmacology, Neurological Diseases 5: 151-158.

World Health Organization. (2009). The Use of Herbal Medicines in Primary Health Care, Technical report, 2009, pp1-66. https://apps.who.int (accessed 2 Janu-ary 2020).

ReseaRch aRticle

Journal of Agricultural and Marine Sciences 2021, 26(2): 64–71DOI: 10.24200/jams.vol26iss2pp64-71Received 30 Oct 2020Accepted 12 April 2021

Mohammad Zakir Hossain2*( ) [email protected], Col-lege of Economics and Political Science, Sultan Qaboos Univer-sity, Muscat, Oman.

Introduction

Bangladesh is an agro-based developing country and striving hard for rapid development of its economy. Agriculture is the mainstay of Bangla-

desh economy and it contributes about 16.3% of the gross domestic product (GDP) (BBS, 2014). Potato ranks fourth in the world (325.3 million tons). The potato pro-duction (8.0 million tons) is among all the vegetables in respect of area coverage and production; and it contrib-utes 55% of the total vegetable production in Bangladesh (BBS, 2009). It is one of the leading vegetable crops to fulfill the demand of carbohydrate in Bangladesh. Onion is one of the most important spice crops and currently it is cultivated in 0.128 million hectares of land and around

1.1 million metric tons are produced with average yield of 8.25 tons/ha. Potato contains 62% water, 29.8% carbo-hydrates, 6.3% protein, 0.1% mineral, 0.4% fibers and vi-tamin C. Among the bulb spices, garlic ranks the third in terms of planting area (37072 hectares) and production (164392 metric tons) and its cultivation covered 7% of the total area used for spices. The average yield of garlic is 4.43 metric tons per hectare (BBS, 2010). Considering the price scenario, proper understanding of agricultural price mechanism and their forecasts can help the farm-ers in many ways such as: (i) plan and decide about the production portfolio, (ii) develop marketing strategy to improve profits, (iii) traders to know the market trends and, (iv) Government to augment economic develop-ments in the nation.

The policy makers of the country needs an accurate early information about the status of different crops such as onion, garlic and potato. Therefore, accurate

نموذج النمو والتنبؤ بأسعار بعض المنتجات الزراعية في بنغلاديش محمد عبدلله المأمون، محمد زاكر حسين، شيخ محمد سايم وخوندكر محمد مصطفيز رحمان

Abstract. The aim of this paper was to explore the appropriate deterministic time series model using the latest selec-tion criteria considering the price pattern of onion, garlic and potato products in Bangladesh (January 2000 to Decem-ber 2016). It appeared from our analysis that the time series data for the prices of potato was first order homogenous stationary but onion and garlic were found to be the second order stationary. Four different forecasting models namely, linear trend model, quadratic trend model, exponential growth model, and S-curve trend model were used to find the best fitted model for the prices of above mentioned products in the Bangladesh. Three accuracy measures such as mean absolute percentage error (MAPE), mean absolute deviation (MAD) and mean squared deviation (MSD) were used for the selection of the best fitted model based on lowest value of forecasting error. Lowest values of these errors indicated a best fitted model. After choosing the best growth model by the latest model selection criteria, prices of selected agri-cultural commodities were forecasted using the following time-series analysis methods: Simple Exponential Method, Double Exponential Method using the time period from January 2017 to December 2021. The findings of this study would be useful for policy makers, researchers, businessmen as well as producers in order to forecast future prices of these commodities.

Keywords: Agricultural commodity prices, Forecasting, Growth models, Time series models, Model selection criteria, Accuracy measures.

الملخــص:كان الهــدف مــن هــذه الورقــة هــو استكشــاف نمــوذج السلاســل الزمنيــة الحتميــة المناســبة باســتخدام أحــدث معايــر الاختيــار مــع الأخــذ في الاعتبــار نمــط أســعار البصــل والثــوم ومنتجــات البطاطــس في بنغلاديــش )ينايــر 2000 إلى ديســمبر 2016(. اتضــح مــن التحليــل أن بيــانات السلاســل الزمنيــة لأســعار البطاطــس كانــت ثابتــة ومتجانســة مــن الدرجــة الأولى بينمــا اســعار البصــل والثــوم كانــت ثابتــة الدرجــة الثانيــة. تم اســتخدام أربعــة نمــاذج مختلفــة للتنبــؤ وهــي نمــوذج الاتجــاه الخطــي ونمــوذج الاتجــاه التربيعــي ونمــوذج النمــو الأســي ونمــوذج الاتجــاه منحــى S للعثــور علــى أفضــل نمــوذج ملائــم لأســعار المنتجــات المذكــورة أعــلاه في بنغلاديــش. تم اســتخدام ثلاثــة مقاييــس دقــة مثــل متوســط النســبة المئويــة للخطــأ المطلــق )MAPE( ، والانحــراف المطلــق )MAD( والانحــراف التربيعــي المتوســط )MSD( لاختيــار أفضــل نمــوذج مناســب بنــاء علــى أدنى قيمــة لخطــأ التنبــؤ. أقــل قيــم لهــذه الأخطــاء تشــر إلى أفضــل نمــوذج ملائــم. بعــد اختيــار أفضــل نمــوذج نمــو وفقــا لأحــدث معايــر اختيــار النمــوذج ، تم التنبــؤ بأســعار ســلع زراعيــة مختــارة باســتخدام طــرق تحليــل السلاســل الزمنيــة التاليــة: الطريقــة الأســية البســيطة ، الطريقــة الأســية المزدوجــة في الفــترة الزمنيــة مــن ينايــر 2017 حــى ديســمبر 2021. نتائــج هــذه الدراســة ســتكون مفيــدة لواضعــي السياســات والباحثــين ورجــال الأعمــال وكذلــك المنتجــين مــن أجــل التنبــؤ بالأســعار المســتقبلية لهــذه الســلع.

الكلمات المفتاحية: أسعار السلع الزراعية، التنبؤ، نماذج النمو، نماذج السلاسل الزمنية، معاير اختيار النموذج، مقاييس الدقة.


Mohammad Abdullah Al Mamun1, Mohammad Zakir Hossain2*, Sheikh Mohammad Sayem3, and Khondaker Md. Mostafizur Rahman4

65Research Article

Al Mamun, Hossain, Sayem, Rahman

forecasting prices of agricultural products support the policy makers and planners to make policy decision re-garding supply, demand and import/export of potato in the country. A number of work have been done by researchers on the forecasting prices and production of rice, wheat, maize, sugarcane and different types of puls-es. However, negligible work have been reported on the three important food products, e.g., onion, garlic and potato in Bangladesh. A number of forecasting mod-els for projecting the agricultural crops and vegetables have been used earlier. Hassan et al. (2013) worked on forecasting coarse rice in Bangladesh using determin-istic trend models (e.g. linear, quadratic and cubic) and it revealed that cubic model was the best fitted model for projecting agricultural grain on the basis of model selection criteria namely, R2 (coefficient of determina-tion), (adjusted coefficient of determination), RMSE (root mean squared error), AIC (Akaike information criterion), BIC (Bayesian information criterion), MAE (mean absolute error) and MAPE (mean absolute per-centage error). Rahman et al. (2013) determined best fitted growth model on forecasting of pulse production in Bangladesh. They used growth model and it revealed that the cubic model was found to be the best model for pigeon pea, chickpea and field pea pulse production. Akhter (2013) conducted a research on forecasting of rice production in Bangladesh and it revealed that both the quadratic linear and cubic models were proved to be the equally better fitted models for rice production in Bangladesh. A very common practice to estimate the growth rate of rice production using accuracy model namely, exponential or compound model (Akhter and Jaim, 2002; Barua and Alam, 2000; Jabber and Jones, 1997). Karim et al. (2010) had worked on the forecasting of wheat production in Bangladesh. Furthermore, Abid et al. (2018) had completed a research on exponential growth model for forecasting of growing area and pro-duction of potato crops in Pakistan. In fact, it is neces-sary to estimate the growth model that best fits the time series data before performing growth analysis.

From the multiple literature review on forecasting determination models, it showed that research work have been completed on forecasting of onion, garlic and potato production in daily/month/yearly production data set basis using multiple determination time series model. Wholesale price of rice, spice crops including masur, gram, kheshari, field pea, black gram and mung bean had been completed using accuracy model es-timation (Rahman et al., 2013). But there is negligible work on forecasting prices of three important commod-ities namely, onion, garlic and potato in the context of Bangladesh. Due to the escalation of prices of vegeta-bles and spice crops, price determination is difficult to maintain equilibrium position of demand and supply in competitive market. Government is always anxious about how to determine price equilibrium in order to make the seller and buyer equally benefited; and produc-

er can earn maximum profits for their products. In this context, early forecasting about the probable prices of vegetables and spice crops could help the policy makers to predict the probable prices of their desired product. Forecasting is very important in decision making cases at all levels in different economic sectors; particularly in agriculture sector. In this sector, the policies and deci-sions are characterized by risks and uncertainty largely due to varied yields, and relatively low price elasticity of demand. To reveal the price pattern and to make the best forecast prices of the selected products, appropri-ate time series models based on the observed data are necessary. Deterministic type of time series models, often called growth models, such as linear, quadrat-ic, cubic, exponential, compound, inverse, power, and S-shaped are very quick to estimate, inexpensive and easy to understand. Therefore, these models are wide-ly used to estimate the growth rate of time series data. Before performing growth analysis it is necessary to identify the growth model that best fits the time series data. In this paper, an attempt is made to identify the best models for the three selected agricultural com-modity prices in Bangladesh using the latest available criteria, such as MAPE, MAD (Mean Absolute Devi-ation), and MSD (Mean Squared Deviation) (Gujarati, 2016). In this paper, another attempt is made to describe the growth scenario in order to forecasts of the prices of these three important commodities in Bangladesh.

Data and MethodologyThe present study was conducted using secondary time series data on the prices of three commodities namely, potato, onion and garlic in Bangladesh (January 2000 to December 2016). The monthly data of the wholesale prices of the three commodities (Tk. per quintal) from the year January 2000 to December 2016 were collect-ed from Department of Agricultural Marketing (DAM), Food Planning and Monitoring Unit (FPMU) under the Ministry of Food System Management Division. These secondary data were used to analyze and achieve the specific objectives of this study.

In this study, the growth models were used to describe the behavior of variable changing with respect to time. Integrated variable exhibited a systematic variation or trend. If the trends are completely predictable, it is called as deterministic trend. The specification of a determin-istic trend can be functional form of time. The mathe-matical form of deterministic trend can be as follows:

y = α + β t (1)

It is important to note that this type of model is called deterministic in which no reference is made to the source and nature of the underlying random-ness in the series. Forecasts obtained by this partic-ular model can often be usefully combined with oth-



er forecasts in order to get overall superior forecasts.

Analytic Techniques Four different forecasting models (i.e., linear trend mod-el, quadratic trend model, exponential growth model, and S-curve model) were used to find the best fitted model for area and production of potato, onion and gar-lic in Bangladesh (Khan et al., 2014). The following fore-casting models were used:Liner Trend Model:

Y = α + β t + ϵ (2)

Quadratic Trend Model:

Y = a + b t + ct 2 + ϵ (3) Exponential Growth Model:

Y = d[ex p(f t ϵ)] (4) S-Curve Model (Pearl-Reed logistic trend model):

Y = (5)

where, Y is the time series considered, t represents time taking integer values starting from 1, ϵ is the regres-sion residual, α, β, a,b,c, d, f, g, k, l, m are the coefficients of the models.

Criteria Used for Model SelectionIn the case of two or more competing models for con-ducting the diagnostic checks, the best model is selected by using the criteria such as MAPE, MAD and MSD. The definition and some related materials are briefly giv-en in the following sections.

Exponential SmoothingExponential Smoothing Methods (ESM) are a family of forecasting models. They use weighted averages of past observations to forecast new values. This method was initially developed by Robert G. Brown and further de-veloped by the forecasting inventory control systems. Exponential Smoothing is a forecasting method that the observed time series data are weighted unequally. Two types of exponential smoothing models are widely used namely, Simple Exponential Smoothing (SES) and Dou-ble Exponential Smoothing (DES). Simple Exponential Smoothing, SES for short, is a time series forecasting method for univariate data without a trend or seasonali-ty. It requires a single parameter, called α, also called the smoothing factor or smoothing coefficient. This param-eter controls the rate at which the influence of the obser-vations at prior time steps decay exponentially. The value of α is often set to a value between 0 and 1. Large values mean that the model pays attention mainly to the most

recent past observations, whereas smaller values mean more of the history is taken into account when making a prediction. A value close to 1 indicates fast learning (that means, only the most recent values influence the fore-casts), whereas a value close to 0 indicates slow learning (past observations have a large influence on forecasts). Formula for Simple Exponential Smoothing is:

(6)

where pt+1 is the forecast prices at time t+1; Pt is the actual price at time t; (obervered); p t is the forecast of Pt; and 0<α<1 is the smoothing parameter. Double Ex-ponential Smoothing is an extension to Exponential Smoothing that explicitly adds support for trends in the univariate time series. Double Exponential Smoothing (DES) computes a trend forecasting equation by apply-ing a special weighting function and emphasizing on the most recent time periods. This method supports the trends that change in two ways: an additive and a mul-tiplicative, depending on whether the trend is linear or exponential, respectively. The DES makes use of the fol-lowing formulas:

(7)

(8)

(9)

In the DES method, the most decisive parameters are smoothing constants α and γ both of which belong between 0 and 1. The forecasts generated by Holt’s lin-ear method display a constant trend (increasing or de-creasing) indecently into the future. Mean Square Error (MSE) has the same unit of measurement as the square of the quantity being estimated. It is defined as:

(10)

where, n is the sample size, k is the total number of estimable parameters and ût is the difference between the observed and estimated values. The model with minimum MSE is assumed to describe the data series more adequately. Root Mean Square Error (RMSE) is defined as:

(11)

where, n is the sample size and k is the total number

67Research Article


of estimable parameters and ût is the difference between the observed and estimated values. The model with min-imum RMSE is assumed to describe the data series more adequately. Mean Absolute Deviation (MAD) is an av-erage of absolute deviations of individual observations from the central value of a series. It is defined as:

(12)

where ut =xt-x , which stands for the deviations of the individual observations from the mean, and abso-lute means that the signs of the deviations whether posi-tive or negative are ignored. Mean Absolute Percent Error (MAPE), the fourth model selection criterion is defined as:

(13)

where n is the number of observations, Yt is the ob-served value and ut is the difference between the ob-served and estimated values.

Results and Discussion

Stationary TestSince the data series was found to be non-normal, Aug-mented Dickey Fuller (ADF) test was conducted to make the series stationary. The results indicated that the series was made stationary at 1st order difference and 2nd order difference with p-value of 0.01, 0.05, 0.10 levels of signif-icance. The trend component of the data was removed in order to make it suitable for price forecasting.

Model Selection Criteria Model selection is an important part of any statistical analysis. The models considered for this study were es-timated for the monthly wholesale prices of potato in Bangladesh during January 2000 to December 2016. All the model selection criteria were used in this study to identify the best fitted model for forecasting purpose and also for explaining the growth patterns of the com-modities. Interpretation of the model selection criteria is considered based on the lowest value of MAPE, MAD, and MSD.

Diagnostic Measures for the Selection of the Best Fitted ModelFrom Table 1, it is clearly appeared that for onion, the values of MAPE, MAD and MSD are 28, 656, 1023026, respectively; for garlic, the values of MAPE, MAD and MSD are 32, 1751, and 7845835, respectively; and for potato, the values of MAPE, MAD and MSD are 31, 353, and 211023, respectively, all of which are smaller for ex-

ponential model as compared to other growth models. Therefore, the exponential growth model was found to be the best fitted model for the trend analysis on the prices of these three agricultural products. It is on the basis of smaller values of accuracy and thus this model is being selected as a best model for forecasting. From Figure 1 we see that the graphs of actual prices and pre-dicted prices for three selected commodities are slightly fluctuated at time. As the actual values and predicted values showing similar seasonal cyclical pattern, there-fore it clearly indicates that the exponential model is more suitable for forecasting.

The Figure 2 is constructed between actual prices and predicted prices of onion, potato and garlic. In com-parison to the actual prices and predicted prices for on-ion, the prices of onion are accounted for Tk. 1344/100 kg to Tk. <2000/100 kg (Jan-2000 to May-2005), Tk. 1214/100 kg to Tk. 8000/100 kg (June-2005 to Jan-2014), Tk. <2000/100 kg to Tk. 6000/100 kg (Feb-2014 to Jan-2016). In the comparison to the actual prices and pre-dicted prices for garlic, the prices of garlic are accounted for Tk. 5000/100 kg to Tk.10000/100 kg (Jan-2000 to April-2007), Tk. <5000/100 kg to >10000/100 kg (May-2007 to Jan-2010), Tk. <20000/100 kg to Tk.15000/100 kg (Feb-2000-Dec-2016). In comparison to the actual prices and predicted prices of potato, the prices of po-tato are accounted for Tk.1000/100 kg to Tk.2000/100 kg (Jan-2000 to sep-2006), Tk. <2000/100 kg to Tk. <3000/100 kg (Oct-2006 to Sep-2009), Tk. 2000/100 kg to Tk. 3000/100 kg (Oct-2009 to Dec-2015), Tk.1000/100 kg to Tk. 2000/100 kg (Jan-2016 to Dec-2016). The comparison of actual prices and predicted prices show similar value and the seasonal cyclical pattern is shown upturn and downturn with time. Since actual price and predicted price are shown similar value, it is ready to better forecasting.

In Figure 3, we constructed a line graph for com-paring the predicted prices and residuals for accuracy of forecasting for our selected three agricultural com-modities. Residual values mean the difference between the predicted values and observed values. In residual, if the prices of three commodities are equal to zero, this line is actually the best fitted line. In the predicted pric-es and residual for onion, the prices of onion is equal to zero or close to zero. The predicted prices is shown upturn and downturn pattern which accounted for Tk. 1344/100 kg to Tk. <4000/100 kg (Jan-2000 to Nov-2005), Tk. <2000/100 kg to Tk.8000/100 kg (Dec-2005 to Jan-2014), respectively. Similarly, the predicted prices of garlic and potato are shown upturn and downturn in a graph where residual is equal to zero or close to zero. Thus it is clear that we are estimating best fitted model for forecasting using data set from January 2000 to De-cember 2016.

In Figure 4, forecasted prices (Jan-2017 to Dec 2021) of our selected three agricultural products have been es-timated based on the actual prices of commodities from



Table 1. : Criteria for best fitted model prices of the Agricultural products (Onion, Garlic and Potato) with comparison accuracy measurements among trend models.

Model Fitted Trend Equation Accuracy Measures

Onion

MAPE MAD MSD

Linear Y= 981 + 13.19 t 31 668 986716

Quadratic Y= 1006 + 12.46 t + 0.0035 t2 31 668 986594

Exponential Y = 1129.92 × (1.00588t) 28 656 1023026

S Curve Y = (105)/[24.4701 + 8.0844×(0.988668t)] 27 649 1080658

Trend Fitted Trend Equation Accuracy Measures

Garlic

MAPE MAD MSD

Linear Y = 2256 + 29.36 t 38 1862 7555079

Quadratic Y= 2495 + 22.4 t + 0.0340 t2 37 1852 7543983

Exponential Y= 2619.46 × (1.00539t) 32 1751 7845835

S Curve Y = (105)/[18.2718 + 33.2841×(0.975665t)] 33 1887 9078596

Trend Fitted Trend Equation Accuracy MeasuresMAPE MAD MSD

Potato

Linear Y= 582.6 + 6.417 t 33 355 204289

Quadratic Y = 596.1 + 6.02 t + 0.0019 t2 33 355 204253

Exponential Y = 629.132 × (1.00552t) 31 353 211023

S Curve Y = (104)/[7.10205 + 18.4221×(0.971589t)] 32 378 238562

Data Source: Department of Agricultural Marketing (DAM) during 2000 to 2016

Figure 1: Trend analysis model for regarding the prices of agricultural products, from January 2000 to December 2016 Figure 1. Trend analysis model for regarding the prices of agricultural products, from January 2000 to December 2016.

69Research Article


Comparison of Actual Price VS Predicted Price using Exponential Smoothing model

Figure 2: Cross-section line graph for the measure of comparison the price between actual wholesale price and predicted wholesale price (Tk. /100kg) for onion, garlic and potato, January 2000 to December 2016.

Figure 2. Cross-section line graph for the measure of comparison the price between actual wholesale price and predicted wholesale price (Tk/100kg) for onion, garlic and potato, January 2000 to December 2016.

Residual Analysis on Predicted Values VS Residuals using Exponential Smoothing model

Figure 3: Comparison between the predicted prices and residuals for three selected agricultural products from January 2000 to December 2016 Figure 3. Comparison between the predicted prices and residuals for three selected agricultural products

from January 2000 to December 2016.



January 2000 to December 2016. The forecasted prices are clearly shown upturn and downturn pattern like as the previous seasonal cyclical pattern graph. Therefore, we can conclude that accurate forecasting has been com-pleted using data accuracy measurement and estimation process through comparison between actual price and predicted price and also predicted price and residual.

ConclusionThis study showed that exponential growth model was

appropriate for forecasting future estimates of the prices of three agricultural products in Bangladesh based on the lowest values of the forecasting errors. The forecast values of the three selected agricultural products clearly showed the increasing trend. Therefore, forecasting pric-es of these three crops could enable the policy makers and government to take wiser steps for attaining price equilibrium to maintain the demand and supply in the market. Furthermore, based on these forecasting price information, both the seller and buyer of these prod-ucts could be equally benefitted and the producers are expected to earn maximum profits from their products.

ReferencesAbid SN, Jamal MZ, Zahid S. (2018): Exponential growth

model for forecasting of area and production of pota-to crop in Pakistan. Pakistan Journal of Agricultural Research 31(1): 24-28.

Akhter MW, Jaim MH. (2002). Changes in the ma-jor food grains production in Bangladesh and their sources during the period from 1979/80 to 1998/99. The Bangladesh Journal of Agricultural Economics 25(1): 1-16.

Akhter R. (2013). Forecasting of rice production in Ban-gladesh. Research Journal of Agriculture and Forestry Sciences 1(7): 15-17.

Barua P, Alam S. (2000). Growth, price instability and flexibility of major crops in Bangladesh. The Ban-gladesh Journal of Agricultural Economics 23(1&2): 103-114.

BBS. (2009). Bangladesh Bureau of Statistics, Statistical Yearbook of Bangladesh-2002. Statistics Division, Ministry of Planning, Government of the People`s Republic of Bangladesh, Dhaka.



Gujarati DN. (2016). The Analysis of Time series: An introduction. 6th edition, Chapman and Hall/CRC Press, Boca Raton, FL, US.

Forecast Analysis using Exponential Smoothing model

Figure 4: Forecasted prices of three agricultural products (Potato, Onion and Garlic) in Bangladesh, From January 2017 to December 2021 Figure 4. Forecasted prices of three agricultural products (Potato, Onion and Garlic) in Bangladesh,

From January 2017 to December 2021.

71Research Article


Hassan MF, Islam MA, Imam MF, Sayem SM. (2013). Forecasting coarse rice prices in Bangladesh, Depart-ment of Agricultural Statistics, Bangladesh Agricul-tural University. Agriculture 22(1&2): 193 – 201.

Jabber MA, Jones RP. (1997). The Growth of MV rice production and adoption in Bangladesh. The Bangla-desh Journal of Agricultural Economics 20(2): 1-19.

Karim M, Awal M, Akter M. (2010). Forecasting of wheat production in Bangladesh. Bangladesh Journal of Agricultural Research 35(1): 17-28.

Khan AS, Masood, MA. 2014. Trend analysis and fore-casting of maize area and production in Khyber Pa-khtunkhwa, Pakistan. European Academic Research 2(4): 4653-4664.

Rahman NMF, Rahman MM, Baten, MA. (2013). Mod-eling for growth and forecasting of pulse production in Bangladesh. Research Journal of Applied Sciences, Engineering and Technology 5(24): 5578-5587.

Rahman, NMF, Aziz, MA, Rahman MM, Mohammad M. (2013). Modeling on Grass Pea and Mung Bean Pulse Production in Bangladesh Using ARIMA Mod-el. IOSR Journal of Agriculture and Veterinary Sci-ence 6(1): 20-31.


Guidelines for authors

The Journal of Agricultural and Marine Sciences (JAMS) is an open access international peer-reviewed journal that publishes original fundamental and applied research articles in a wide variety of disciplines of the agricultural and marine sciences. The journal provides a forum for specialists and practitioners and brings together quality papers dealing with agricultural economics, natural resource economics, animal and veterinary sciences, bio-resources, biotechnologies, soil sciences, water management, agricultural engineering, fisheries, marine sci-ences, food science, human nutrition, plant production, plant protection, rural environment, coastal zone management and oceanography. All issues of the Journal of Agricultural and Ma-rine Sciences are freely available online and do not carry any publication charges.

Types of manuscript publishedManuscripts submitted for publication in the Journal of Agricul-tural and Marine Sciences must be based on original work and have not been published, accepted for publication or submitted for publication elsewhere. The journal accepts the following types of manuscripts:1. Editorials (by invitation only)2. Reviews (Review papers not exceeding 6000 words or 14 print-ed pages including figures, with prior approval from the Editor in Chief )3. Research Articles (Original research not exceeding 6000 words or 14 printed pages including figures)4. Notes (Original research papers not exceeding 3000 words or 6 printed pages including figures and bibliography)5. Perspectives (short papers, not exceeding 3000 words or 6 pages, that present an opinion or a novel interpretation of existing ideas)6. Snapshots (single page paper focusing on a high quality illustra-tion, and a very short —5 references— bibliography).

SubmissionNew manuscripts should be submitted online through the jour-nal management system (https://journals.squ.edu.om/index.php/jams). Note that authors who are not yet registered with the journal management system, need to first create an identity by register-ing on the journal website(https://journals.squ.edu.om/index.php/jams). Once registered, corresponding authors can login with their chosen username and password.To facilitate the preparation of manuscripts that correspond to the Journal structure, the Editorial boards has prepared a series of tem-plates in Microsoft Word and Apple Pages. They can be download-ed from the main submission page : https://journals.squ.edu.om/index.php/jams/about/submissions#authorGuidelines.

We also provide export style files for Endnotes (.ens) and Zotero, Papers and other bibliographic software that use the .csl citation format files. These as well as a pdf version of this documents can be downloaded from both the Journal Submission page (https://journals.squ.edu.om/index.php/jams/about/submissions#au-thorGuidelines).

Reviewing policy The Journal of Agricultural and Marine Sciences uses a blind re-view process in which the peer reviewers’ names are not disclosed to the authors, although the reviewer can make himself known should he choose to do so. Before submitting the papers for re-view the editors will evaluate the manuscript suitability for the journal (language, readership, format), insure the completeness of the submission and make an initial “plagiarism” assessment of the

manuscript. If suitable for the journal, the editors will choose 2-3 reviewers among researchers working in a similar field and listed in the jour-nal database. The selection of reviewers is based on several factors: expertise, reputation, specific recommendations of the author or of a reviewer, and our own previous experience of a reviewer’s char-acteristics. The editors will request a minimum of two independent reviews but can if necessary request additional evaluations, par-ticularly if 2 reviewers have severely contradictory opinions on a particular submission.Following the reviews, the section editor will place the manuscript among 4 categories:1. Accepted with minor modifications; the paper requires mostly editorial and typographic modifications).2. Accepted conditionally to a revision of the papers following the recommendations and specific comments or concerns of the re-viewers (the reviewers found incomplete or unclear statements that needs to be revised; some of the results may need to be rein-terpreted or some figures redrawn; part of the discussion may need some additional work). The acceptance remains conditional until the editor is satisfied with the revision. 3. Acceptable but only after after a second round of reviews (the pa-per cannot be accepted without a thorough revision of its structure or significant changes in its presentation. The author will receive all comments from the first set of reviewers and requested to resubmit the paper with the suggested modifications and amendments. 4. Not acceptable. There are major flaws in the experimental de-sign, sampling protocol or analytical protocol that preclude a sound analysis or if the reviewers found significant overlap with published results.The editor will then inform the corresponding author of his edi-torial decision and convey the comments and suggestions of the reviewers to which the author has to respond normally within 2-4 weeks. Authors may contact the editor through the journal email system if they require an extension.After reception of a revised manuscript, it may be subjected to an additional round of review, particularly if the manuscript was originally placed in the “acceptable” category. The final decision of acceptance or rejection lies with the Editor in Chief in coordination with the whole editorial board and the Sultan Qaboos University Academic Publication Board.All communications between authors, editors and reviewers are made using the Editorial Management System at: http://journals.sfu.ca/squjams/index.php/squjams/index

AuthorshipAuthorship must be based on all of the following criteria: (1) sub-stantial contribution to the conception and design of the study, data acquisition, analysis and interpretation of the data; (2) draft-ing the article or revising it critically and; (3) final approval of the version of the manuscript to be published. Contributors who do not meet all 3 of these criteria should be listed in the acknowledge-ments section of the manuscript. The corresponding author is re-sponsible for taking all necessary coordinating actions for revising the manuscript, receiving authorization from other authors, etc.

Scientific misconductAccording to standard practices in scientific journals, SQU Journal of Agricultural and Marine Sciences follows the recommendations of Council of Science Editors (www.councilscienceeditors.org) and define misconduct as: 1. Data Corruption: falsifying data, inventing data, ignoring part

Guidelines for Authors

73Guide for Authors

of the data purposefully, or any form of omission, suppression or distortion of data.2. Plagiarism: using published or unpublished texts, ideas or thoughts of another writer without acknowledgements and pre-senting them as one’s own. Plagiarism includes duplicate publica-tions or submissions in the same or in another language. The jour-nal will follow COPE guidelines to identify and manage cases of plagiarism or text recycling.3. Authorship misconduct: Exclusion of involved researchers, or inclusion of researchers who have not contributed significantly to the work (see section on authors), or publication without the con-sent of all authors.4. Ethical misconducts: Failure to follow legal requirements in acquiring the necessary permission to sample, collect, export or import specimens, collect data, use chemicals or obtain ethical permits in the country of the author’s institution.SQU Journal of Agricultural and Marine Sciences takes all forms of misconduct very seriously. It follows the Committee for Pub-lication Ethics (COPE) recommendations and guidelines (publi-cationethics.org/resources/guidelines). Final decisions regarding scientific misconducts are taken by the Editor in Chief.

Types of articles The journal accepts several types of articles and recommends the following submission length and subsections

Editorials (by invitation only)Editorials should not exceed 2000 words and a maximum of 25 ref-erences.

ReviewsReviews should not exceed 6000 words and 14 pages and approxi-mately 100 References. Authors who would like to submit a review are requested to send to the Editor in chief ([email protected]) a one page letter of intention outlining the focus and scope of the projected review before submitting their review online. The abstract of a review paper, although structured, does not have to follow the “5 section template”.

Research Articles (original research not exceeding 6000 words)

Research papers should not exceed 6000 words or 14 pages and 50 references. They should be divided into the following 6 sections: Abstract, Introduction, Materials and Methods, Results, Discus-sion and References. Additional sections such as Acknowledge-ments, Conclusions or Recommendations can also be included. Although merging results and discussion is possible, it is not a structure encouraged by the editorial board.

Notes (original research not exceeding 6 printed pages)Notes are short original research articles. They should not exceed 3000 words and 30 references or 6 printed pages. They should have the same overall structure as Research Articles including a struc-tured abstract.

Perspectives (short papers, not exceeding 3000 words) Perspective papers are short papers that present an opinion or nov-el interpretation of existing ideas or data. They may also present an historical perspective on one of the themes of the journal. These manuscripts should follow a structure and a logical sequence of sections related to the content and purpose of the paper.

Snapshots A Snapshot manuscript is a single page paper focusing on a high quality illustration. The paper itself should not exceed one page and lists only a maximum of 3 references. Snapshot papers illustrate the common say “One picture is worth a thousand words”. The topic

of the paper should be based on a high quality photographic evi-dence of rare organisms, new records, unusual observation, severe pathology, etc. These submissions, because of their short nature, do not have abstracts. The illustration needs to have an accompanying legend.

Language and translations The journal publishes papers in the English language with trans-lation into Arabic of the title, authors and abstract of all papers. Arabic speaking authors are invited to provide the editorial board with an Arabic translation of the title and abstract. For non-Arabic speakers, the board will provide a translation. British English spelling, usage, and punctuation are used through-out the journal. Papers accepted for publication will be edited by the Journal editorial office for conciseness, clarity, grammar, spell-ing and style. Should the editing be extensive and possibly alter the intended meaning of the author(s), queries will be sent by email to the corresponding author requesting clarifications.

StyleThe Journal follows the overall evolution of the scientific language. When preparing manuscripts please avoid jargon and long or com-plex sentences but aim at clear, concise and simple grammatical structures. The editorial board encourages the use of the active voice when it is appropriate.

AbstractThe Editorial board strongly suggests the use of a “structured ab-stract” not exceeding 300 words. These abstracts, although com-posed of a single paragraph, include 5 sections that summarize the content of the paper: introduction, objectives, methodology, results and conclusion. Each section is introduced by a heading fol-lowed by a colon and a series of sentences.

Preparation of the manuscript All papers will be typeset by the editorial team of the journal at publication time. Therefore, the editorial board requests the au-thors to follow a clear and simple format for their manuscript thereby facilitating the reviewing and editorial process. Templates for Microsoft Word™ and Apple Pages™ are provided to assist au-thors in preparing their manuscripts.The editorial board recommends the use of a classic typeface (Times, Helvetica, Garamond, Myriad-Pro, …) with 12 point size and at least 14-16 points leading (line spacing) for the text of the manuscript with minimum formatting as most of layout and ty-pographical formats will be applied at the typesetting stage. The manuscript page size should be A4 or US Letter and the editorial board recommends that a margin of at least 3 cm be included on all sides of the paper.To facilitate the reviewing process, the text of the submission should have line numbers in the left hand margin restarting at 1 on each page and a page number in the footer of the document. Use standard typographic conventions for the text presentation: italic typeface for species names (not underline), bold face for vectors, true superscript and subscripts when necessary. Emphasis is better marked through italic rather than bold face.

TypographyThe journal uses standard typographic convention throughout. The editorial board recommends that you follow these in the prepara-tion of the manuscript.Italic should be used throughout for the Latin name of species (please do not use underlined text). Emphasis can be placed on some elements of text using bold face.Abbreviations: Avoid non-standard abbreviations whenever pos-sible, particularly in headings and subheading. If, for the sake of


Guidelines for authors

conciseness, the author wishes to use abbreviations, define each abbreviation when they first appear in each section of the man-uscript. Standard abbreviation such as RNA, DNA, ATP, ADP, EDTA… do not need to be defined as most readers will be familiar with them. Others such as PAH (Polycyclic Aromatic Hydrocar-bon) or ICP (Inductively Coupled Plasma) should be defined as most reader may not be familiar with their meaning.Units: Always use the International System of Units (SI) for all units. For large or small units use the standard multiplier prefix for the units (k for 1000, M for 1000000, m for 1/1000 and µ for 10-6). Prefer whenever possible negative exponents to slash: kg·m-2 rather than kg/m2. To separate units, use either a mid-line point (· =ASCII code 183 – Unicode U+00B7) or a non-breaking space. The abbreviated symbols (k, kg, s, P, W, etc. ) should be used whenever possible and combined with Arabic numbers (5 kg, 2 m2, 5.2 MP, 6.78 MW·h). The only exception is when a number is grammatical-ly placed at the beginning of the sentence. A non-breaking space (Unicode U+00A0 ) should be used between the number and its units to insure that they stay together in the final document. The SI unit of time is s (second), h stands for hora, min for minuta, d for dies (day) and a for annum (year).When necessary, non-SI units can be added between parenthesis to allow comparison with older literature or traditional systems of measurements. This includes usual units, such as surface of farm-ing units (faddan, acres, ares, hectares), or traditional depth units (fathoms, brasses, Ba’,…) or distance (nautical miles, miles) or other non SI units (gallons, inch, foot, bushels, etc. ).

IllustrationsIllustrations should be numbered consecutively and submitted as individual files, not embedded in the article file. To insure com-patibility, the journal accepts the following file format: JPEG, TIFF, PNG, PDF, EPS and SVG. Although the journal is normally pub-lished in black and white, color illustrations can be used when color is clearly necessary to convey the intended message. Although the authors can suggest the inclusion of color figures in the paper, the final decision to include them or not is left to the editorial board. The editorial team will strive to provide the best possible graph-ic output from the material submitted by the authors and may in some cases decide to redraw some figures to improve readability. They may also request better quality photographs or color figures if necessary. Typically black and white line figures should have a res-olution of at least 600 dpi (at the final printed size) and color figures or photographs 300 dpi (at the final printed size) but should not exceed 10 MB. For line graphics, vector based file formats (SVG, PDF, EPS) are preferred as they are resolution independent. Each illustration should have at the bottom of the page a brief iden-tifier such as the name of the first author, the word Figure and the sequential number of the figure. (Al-Oufi, Figure 7 for instance). The full captions of all figures should be presented in numerical order on a separate page at the end of the text manuscript.In the figure use Helvetica as the standard typeface for all text (axis, legend, axis legend, equations, labels, etc.) and ensure that all text remain legible even after size reduction for final printing. Figures will be printed either as a single column (7 cm wide) or double column (14 cm) figureMacro-photographs, micro-photograhs, SEM photographs, an-atomical drawings, morphological illustrations, should have an appropriately labeled scale bar. Avoid multiplication factors (x100, x10000) as these will change with the rescaling of the figure when printed.

TablesTables should be presented in a clear manner and designed to fit on the width of a page. Exceptionally wide tables may be typeset, side-ways, along the height of a printed page. All unnecessary decimals should be removed. Tables should be included at the end of the

manuscript on separate pages and the legend/caption of each table should be placed on the same page and above the table.

Equations and numbersEquations should be placed on separate lines and numbered se-quentially at the end of the line. They should be typeset using an equation editor. If this is not possible scan or photograph a clear handwritten version of the equation which will be typeset by the editorial team.The Journal uses the modern scientific number styles recommend-ed by the Council of Science Editors. This styles uses digit numbers (1, 2,4.5, 7, etc.) for all numeric representations, even single digit ones. The main exceptions are when a digit starts a sentence, or when the single digit number is part of an idiomatic expression such as in “one or both”, a “zero-tolerance policy”, a “one-to-one interview”, “one has to agree that”…

References SQU Journal of Agricultural and Marine Sciences uses a variation of the Author-Date style of references developed by the Council of Science Editors (CSE). Output style files for Endnote and CSL (Citation Style Language) are available for download on the Journal Submission Management Web Page:https://journals.squ.edu.om/index.php/jams/about/submis-sions#authorGuidelines

In-text citationsCitation in the text should be either Name (date) or (Name date) depending on whether the authors of the cited paper have a gram-matical function in the sentence or not. Note the absence of punc-tuation between the author and the date. When several references are grouped in a single inline citation, the different references are separated by a semi-colon (; ).

Jones et al. (2007) listed 4 main types of …According to Jones et al. (2007), the main reason for….The prevalence of coral parasites was considerably lower than

that reported in Tanzanian coral reefs (Mwaniki, 1996).Different papers that share the same in-text citation format (same authors and same year of publication) are identified by a small let-ter (a, b, c) following the date of publication. When used in a single citation, the author’s name is not repeated.

The ticks collected on camels were not different from that found on goats (Bobade, 2004a) or sheep (Bobade, 2004b).

There were no differences in the species of ticks collected on different farm animals (Bobade, 2004a; 2004b)…

The family name of the first author is always used. For publications with 2 authors, the 2 family names with the conjunction “and” are used followed by the year of publication. For more than 2 authors, the abbreviation et al. (Latin et alii – and others) is used to replace all but the first author’s name.

Jones et al. (2007) listed 4 main types of soft coral communi-ties…

Al-Barwani and Jones (2005) found 3 genetically distinct popu-lations of mussels…

The Omani clownfish has a distribution restricted to 400 km along the Arabian Sea coast of Oman (Simpson et al. 2014).

End of text referencesThe bibliographic information for all cited references in the articles are listed at the end of the papers under the heading “References”. The list of references is sorted first following the alphabetical order of the authors and if necessary, by the date of publication. Please follow the examples shown below, including punctuation. The Journal names follow a “Title case” capitalization—all words are capitalized except for articles (a, an, the); for prepositions (against, of, in, to), for conjunctions (and, for, not, or)—and should NOT be abbreviated. Titles of articles, books, on the other hand follow a

75Guide for Authors

sentence case capitalization (i.e. words are capitalized according to the grammar of the language of publication): the first word, the first word that follow a colon or a semi colon, names of geographic lo-cations, or proper nouns, etc. For articles published in non-English languages, provide the original title if the language uses roman characters or a translation of the title for other languages (Arabic for instance) and add the name of language between 2 periods at the end of the reference.For online references, follow the overall same standard as for print publication, but include a date of access and if possible a DOI num-ber. Volume and issues, if available, follow directly the Title of the Journal with the issue number between parenthesis. Page num-bers follow a colon and are separated by an hyphen. For books, the total page number is used with the abbreviation “pp.” whereas for sections of books, the abbreviation is “p.” followed by the range of pages of the section (p. 25-44). All references ends with a period.

Journal reference with 1 authorAdams NA. (2001). UV radiation evokes negative phototaxis

and covering behavior in the sea urchin Strongylocentrotus droebachiensis. Marine Ecology Progress Series 213: 87-95.

Journal reference with 2 authorsZhou M, Huntley ME. (1997). Population dynamics theory of

plankton based on biomass spectra. Marine Ecology Prog-ress Series 159: 61-73.

Journal reference with more than 2 authorsSchlacher TA, Thompson l, Price S. (2007). Vehicles versus

conservation of invertebrates on sandy beaches: Mortalities inflicted by off-road vehicles on ghost crabs. Marine Ecology 28: 354-367.

Whole book Parsons TR, Maita Y, Lalli CM. (1984). A manual of chemical and

biological methods for seawater analysis. New York: Pergam-on Press. 173 pp.

Book chapter from an edited bookBrooks HA, Probert TH. (1984). Let’s ask GMDH what effect the

environment has on fisheries. In: Farlow SJ, editor. Self-orga-nizing methods in modeling. Gmdh type algorithms. New York and Basel: Marcel Dekker, Inc. p.169-178.

ReportStransky C. (2001). Preliminary results of a shape analysis of

redfish otoliths: Comparison of areas and species. Northwest Atlantic Fisheries Organization. NAFO SCR No. 4382.

ThesisAl-Masroori HS. (2002). Trap ghost fishing problem in the area

between Muscat and Barka (Sultanate of Oman); an evalu-ation study [MSc.]. [Muscat]: Sultan Qaboos University. 112 pp.

Article not in EnglishSamimi NS. (2004). Soft-corals and gorgonians of the Iranian

shore of the Straight of Hormuz. Iranian Journal of Oceanog-raphy 7(2): 45-49. Farsi.

Conference proceedingsCampbell AC. (1988). The echinoderm fauna of Dhofar (southern

Oman) excluding holothuroids. In: Burke RD, Mladenov PV, Lambert P, editors. Proceedings of the Sixth International Echinoderm Conference; 23-28 August 1987; Victoria, Cana-da: Balkema. p. 369-378.

Submission checklist 1. The current submission has not been previously published nor is it currently submitted to another journal for consideration.2. The submission text files are in Microsoft Office (.doc, .docx), OpenOffice (.odt), RTF (rtf ) or Apple Pages (.pages) document file format.3. The text of the document uses a 12-point standard font with a 14-16 point leading (space between lines) on A4 or US-Letter format pages with page numbers and line numbers. Manuscript conforms to the journal recommended styles, length and number of sections.4. The Abstract of the paper follows the structured format de-scribed in the guide for authors and includes a single paragraph (<300 words) with 5 inline headings (Introduction, Objectives, Method, Results and Conclusions) and keywords for the manu-script are provided.5. Photography (or photographic plates) are submitted in the jpeg (.jpg) file format at 300 dots per inch (dpi) with 80% compression quality or better. Line drawings and other figures should be prefer-ably submitted as vector graphics such as pdf, eps or svg files. Al-ternatively, high resolution (600dpi) image format are acceptable (PNG, TIFF, GIF).6. All tables including (legend, description and footnotes) and all figure captions are part of the submission main text file. 7. The text adheres to the stylistic and bibliographic requirements outlined in this document which can also be found in About the Journal on the Journal web site.8. The manuscript has been “spell-checked” and “gram-mar-checked”.

Supplementary material JAMS accepts electronic supplementary material to support pub-lished manuscripts. These may include high-resolution images, sound-tracks, datasets and will be published online along with the electronic version of the published paper. Data should be provided in one of the supported format (pdf, doc, docx, otd, rtf, pages, jpeg, png, tiff, svg…) for printable documents and standard formats for non-printable documents (AIFF, MP4, MP3, etc.).

CopyrightsThe content of the journal is licenced under the Creative Common (CC BY ND) licensing schemes the details of which can be found at https://creativecommons.org/licenses/by-nd/4.0/legalcode.

Contact details

The Editor-in-ChiefJAMS Editorial OfficeCollege of Agricultural and Marine SciencesSultan Qaboos UniversityP.O. box 34, Postal Code 123Al-Khod, MuscatSultanate of OmanTel: (968) 2141 1257

Submission at https://journals.squ.edu.om/index.php/jamsEmail: [email protected] email: [email protected]

1 مراجعةعلىالتجفيفالشمسيللأسماكنسرينس.المحروقية،عبدالرحيمم.الإسماعيلي

تطبيقاتنظمالمعلوماتالجغرافيةوالإستشعارعنبعدفيالزراعةالمحمية:مراجعة10 أسماءم.الميمني،عبدالرحيمم.الإسماعيلي،ياسينشرعبي

استعراضالاكتشافاتالجديدةلفيروساتالبيجوموفيروسفيعمان24 محمدشفيقشاهدوعبداللهبنمحمدالسعدي

ورقة مراجعة

توصيفالتنوعالجينيللغزالالبريبمحافظةظفار35أحمدجشعول،علياءالأنصاري،وليدالمرزوقي،عثمانالقعيسي،منصورالجهضميومحمدالعبري

الخصائصالفيزيائيةوالكيميائيةلجودةصنفينمنفاكهةالرمانيزرعانعلىارتفاعاتمختلفةفيجبالالحجرفيعمان42باسمالكلباني,راشداليحيائي,عبداللهالسعدي,الغاليةالمعمري

الانتشارالمصليلعدوىالمثـقبيةالإيفانسيةبينالإبلوحيدةالسنامفيمحافظةشمالالشرقية،سلطنةعمان51أملحمدالخروصية،الشفيعابراهيمالشفيع،كمالعلى،راشدالسنيدي،ناديةبنيعرابة،فاطمةالسيفية،يحيىالمعولي

الخصائصالمحتملةالمضادةلمرضالسكريلاثنينمنالنباتاتالبريةالعمانية:السيداف56)Oxalis corniculata(الحميضو)Pteropyrum scoparium(

إيمانالقلهاتيومصطفىواليوليوثةالصبحيوزاهرالعطابي

نموذجالنمووالتنبؤبأسعاربعضالمنتجاتالزراعيةفيبنغلاديش72محمدعبدللهالمأمون،محمدزاكرحسين،شيخمحمدسايموخوندكرمحمدمصطفيزرحمان

ورقة أبحاث

المحتويات

مجلة العلومالزراعية والبحرية

• مراجعة•على•التجفيف•الشمسي•للأسماك• تطبيقات•نظم•المعلومات•الجغرافية•و•الإستشعار•عن•بعد•في•الزراعة•المحمية:•مراجعة• استعراض•الاكتشافات•الجديدة•لفيروسات•البيجوموفيروس•في•عمان• توصيف•التنوع•الجيني•للغزال•البري•بمحافظة•ظفار• الخصائص•الفيزيائية•والكيميائية•لجودة•صنفين•من•فاكهة•الرمان•يزرعان•على•ارتفاعات•مختلفة•في•جبال•الحجر•في•عمان• الانتشار•المصلي•لعدوى•المثـقبية•الإيفانسية•بين•الإبل•وحيدة•السنام•في•محافظة•شمال•الشرقية،•سلطنة•عمان• Pteropyrum(•الخصائص•المحتملة•المضادة•لمرض•السكري•لاثنين•من•النباتات•البرية•العمانية:•السيداف

)Oxalis corniculata(•و•الحميض•)scoparium• نموذج•النمو•والتنبؤ•بأسعار•بعض•المنتجات•الزراعية•في•بنغلاديش

الـمحتويات

جامعة السلطان قابوس - سلطنة عمان

www.squ.edu.om/agr/JAMS

المجلد 26 , العدد 2 ,2021م

JAMS - journals.squ.edu.om

Documents

Transcript of JAMS - journals.squ.edu.om