Post on 09-Jul-2020
CHAPTER - III
RESEARCH METHODOLOGY
In this chapter, elucidate the research methods and procedures
followed in this study. The methodology was grouped and presented
under the following sub-heads.
3.1. Research design of the study
3.2. Selection and description of the crops
3.3. Selection of the study area
3.4. Description of the study area
3.5. Selection of respondents
3.6. Selection of variables and their measurement
3.7. Method of data collection
3.8. Statistical tools applied
3.1. Research design of the study
“Research design is the arrangement of conditions for collection
and analysis of data in a manner that aims to combine relevance to the
research purpose with economy procedure”.
For the study ex-post-factor research design was followed. To put it
in Kerlinger (1978) words, ex-post-factor research is a systematic
empirical enquiry in which the scientists do not have direct control of
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influencing ‘independent’ variables because their manifestations have
already occurred or because they are inherently not manipulable.
Influence about relationship among variables are made without direct
invention but from concomitant variation of independent (Influencing)
and dependent (consequent) variables.
3.2. Selection and description of the crops
Tamil Nadu is known for collection and cultivation of a wide range
of medicinal plants under different natural eco-systems. However, a few
species arc under commercial cultivation. For instance, senna,
periwinkle, glory lily, coleus, gall nut, annatto, aloe, keezhanelli, safed
musli and aswagandha are cultivated in isolated places throughout Tamil
Nadu. The cultivated species are having very good market domestically
and internationally.
This study is restricted to analysis of various aspects of
commercialisation of two medicinal plants, viz., senna and glory lily. They
were selected for the study because they were grown under different
natural and management conditions. Further, they have very bright
export potential in the context of increasing significance of medicinal
plants.
Glory lily is widely seen in wild. It is commonly known as Sukra
Pushpika / Garbhagatini / Langalika /Agni-sikha / Kalihari (Sanskrit),
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and Karihari / Kariari / Kalihari / Languli (Hindi) (The Indian Materia
Medica). It is called with different names like Senkanthal mazhar or
Kanvali kizhangu or Kalappai kizhangu in Tamil Nadu. This flower is also
the state flower of Tamil Nadu.
The alkaloids such as colchicine, gloriosine and superbine are
important for various applications. The colchicine content is used as
polyploidising agent in cytological studies. The discovery of colchicine in
glory lily led to domestication of this crop at large scale. Besides, the
various products of glory lily are used in treating gout, snakebite,
scorpion sting, abortion, leprosy, skin diseases, piles, and arthritis
(Kennedy et al, 2000).
The colchicine and colchicoside extracted from Colchicum
autumnale L. could also be extracted from Gloriosa superba. These
alkaloids were strong in demand (Gupta et al, 1971). Gloriosa superba L.
became a potential source of colchicines and colchicoside in
pharmaceutical industries for they are present in appreciable quantity in
its seeds (Bellet and Gaiganult, 1985).
In this context, glory lily was first commercially cultivated in Tamil
Nadu in 1985. The Italian company Indena India Pvt. Ltd. based in Milan
sponsored large cultivation of the plants in Tamil Nadu. An initial
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buyback agreement was made, but only with the traders based in
Virudhunagar district. Once the Milan experiment became known, buyers
from other countries came to Madurai and Virdhunagar (www.
nandhiniherbs. com).
Glory lily is a native of tropical Asia and Africa. It is found in India,
Madagascar, Sri Lanka, Indonesia and on the adjacent islands. It is found
throughout tropical India, from northwest Himalayas to Assam and
Deccan peninsula, extending upto an elevation of 2,120 m
(www.nandhiniherbs.com).
Glory lily is commercially cultivated in Tamil Nadu, Karnataka and
Andhra Pradesh. However, Tamil Nadu state leads in production and
export of Gloriosa seeds in India. In Tamil Nadu, it is grown in Erode,
Dindigul, Athur, Salem and Madurai covering an area of about 1000 ha.
The annual production of seed is about 400 tonnes, and about Rs.80
million worth of seeds are exported to other countries especially Italy and
USA (Rajamani and Selvaraj, 2003-04).
The product is exported in the form of seed and colchicines
content. The major importing countries are Italy, Netherlands, German,
Mexico, Japan, Egypt, Taiwan, France, South Korea, Malaysia,
Switzerland, United Kingdom and USA. The export price of seed
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registered sharp decline during 2001-2002. whereas colchicines remained
more or less same (www.nandhiniherbs.com).
Senna (Cassia angustifolia) is popularly known as Trinelveli senna
or Avuri. It is known as Markandi in Sanskrit and Sonamuki in Hindi. It
is considered as the best natural laxative in the whole plant kingdom. The
alkaloid, namely sennoside is responsible for laxative properties of senna.
The senna tea is very famous in European countries. The leaves of this
plant are used in the preparation of Ayurvedic, Unani and Allopathic
medicines. It is known to be used in treating the diseases like typhoid,
jaundice, cholera and fever (Kennedy et al, 2000).
Senna is a native of Yemen and Hadramanut province of Saudi
Arabia. Sporadic distribution was reported in parts of Sind (Pakistan),
Mundra and Kutch districts of western Gujarat. Senna was introduced
first in Tirunelveli district of Tamil Nadu during the mid -eighties of the
19lh century and hence the Indian produce is called Tinnaiveli Senna
(Arumugam, 1996).
It is cultivated in southern parts of Tamil Nadu covering districts
like Tirunelveli, Tuticorin, Virudhunagar, Ramanathapuram and Madurai
for more than 100 years. It is also being cultivated in Anand and
Kachchh (Gujarat), Cuddapah (Andhra Pradesh), Bikaner and jodhpur
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(Rajasthan) and Pune (Maharashtra).
There are two types of senna in the international market, namely
Alexandrian Senna' from Sudan, and 'Tinnaiveli Senna' from India.
Tinnaiveli Senna is further classified into three groups namely, Nadu,
Idainadu and Sathur senna depending upon the region from which it is
grown. Nadu type is cultivated in Tirunelveli and Tenkalani region. It is
considered the best quality and exported mainly to Japan. Idainadu is of
second in quality and cultivated in Tirunelveli -Kovilpatty belt. Sathur is
of third in quality and grown in the regions of Tuticorin -Madurai. The
leaves and pods are harvested from Sathur type, whereas only leaves
from Nadu and Idainadu type.
Tamil Nadu holds leading position in the production and export of
senna leaves and pods to the world market with an estimated production
of 5000 tonnes of senna leaves and pods earning Rs. 45 million every
year. The crop is cultivated in about 6000 hectares. Almost more than
three fourth of the senna produced is exported. The major export market
for senna is USA and UK and the major competitor of senna production
for India is Sudan and Africa.
3.3. Selection of the study area
The state of Tamil Nadu was selected for the present investigation.
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The selected medicinal plants, senna and glory lily, are grown in this
state in large geographical area. Besides, Tamil Nadu is one of the leading
states taking up commercial cultivation of medicinal plants. The
introduction of new crops for cultivation is also underway in the recent
years.
Dindigul and Tuticorin districts were selected purposively for
conducting the survey with respect to glory lily and senna, respectively.
The glory lily is mainly cultivated in Dindigul, Erode and Salem districts
of Tamil Nadu. The Dindigul district has larger area under commercial
cultivation of glory lily and is expanding the area in the recent years.
Because of this process, the buyers from all over India have established
their purchasing counters in this area. In view of this, Dindigul district
was selected purposively for the analysis of production and marketing of
glory lily.
The purposive sampling technique was used to select one block in
the Dindigul district. It consists of 14 blocks namely, Dindigul, Nilakottai,
Vedasandur, Natham, Kodaikanal, Palani, Oddanchatram,
Reddiarchatram, Sanarpatti, Thoppampatty, Vatalakundu,
Guziliamparai, Vadamadurai and Athoor. Oddanchatram was selected
from among the blocks, as it has the largest area under glory lily
cultivation. Paraivalasu, Ambilikai, Kallimandayam, Rotupudur and
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Kappalpatty having large area under glory lily were the five selected
villages in Oddanchatram block.
The senna is cultivated in semi-arid area of Tirunelvelli, Tulicorin,
Ramanathapuram, Madurai, and Virdhunagar districts in the southern
region of Tamil Nadu. Among all, Tuticorin district has large area, well-
established marketing structure and port facilities for export of senna.
So, it was considered suitable for carrying out this study covering varying
aspects related to production to marketing of senna.
Purposive sampling technique was used to select one block in the
Tuticorin district. Tuticorin consists of 12 blocks namely, Pudur,
Ottapidaram, Vilattikulam, Kayattar, Kovilpatti, Tuticorin, Karungulam,
Srivaikuntam. Alwarthirunagari, Tiruchendur, Udangudi and
Sattankulam. Srivaikuntam was chosen to survey farmers cultivating
senna. Five villages namely, Kasilingapuram, Chinnathakurichi. Alanda,
Savlaperi and Deivaseyalpuram were selected randomly.
3.4. Description of the study area
(i) Dindigul:
Dindigul district is bound by Erode, Coimbatore, Karur and Trichy
districts on the North, by Sivaganga and Tiruchi District on the East, by
Madurai district on the South and by Theni and Coimbatore Districts and
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Kerala State on the West. It comprises of 3 Revenue Divisions, 7 Taluks
and 14 Panchayat Unions. For a long time, . This district is privileged to
have one of the 'Six Celebrated Kill Abodes of “Lord Muruga” at Palani
Hills. Kodaikkanal, a popular summer resort, located at an altitude of
2133 meters in the Western Ghats is the ‘Princess of Hill Stations’.
Dindigul is placed prominently in the agricultural map of Tamil
Nadu. The major crops are paddy, sorghum, sugarcane, cotton,
groundnut, fruits and vegetables. The district is known for a wide range
of vegetables like onion, tomato, brinjal, cauliflower, and drumstick.
Dindigul city is an important wholesale market for onion, and
groundnut. Oddanchatram is a noted market centre for vegetables. It is
also famous for the export of butter, which is manufactured in the
nearby villages using cream separators.
(ii) Tuticorin
Tuticorin district is situated in the extreme south-eastern corner of
Tamil Nadu state. It is bounded on the north by the districts of
Tirunelveli, Virudhunagar and Ramanathapuram, on the east and south-
east by Gulf of Mannar and on the west and south-west by the district of
Tirunelveli. It is known for trade and commerce since ancient times. The
economic development of the district sustained by Tuticorin port and
dependent industries around it. Tuticorin port, one of the major ports in
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India, handles a variety of commodities and contributes to coastal trade
and economy of the hinterland.
Table - 1. Geographical profile of the study area
S. No Characteristics Dindigul Tuticorin
1. Geographical position 10°18' - 10°24' N
77°15'-78°01' E
10°05'- 10°09’ N
77°30' - 78°20’ E
2. Climate Semi-arid Tropical and Semi-arid
3. Temperature 31-38°C 33-39°C
4. Rainfall
North east monsoon 30.6 cm 31.8 cm
South west monsoon 19.8 cm 22.8 cm
5. Land utilization pattern (1000's ha)
Geographical area (hectares) 626.7(100%) 459.1 (100%)
Forest 138.9(22.16%) 11.0(2.4%)
Barren uncultivable Land 36.2 (5.8%) 19.9(4.3%)
Non-agricultural Land 65.0(10.4%) 68.6(15.0%)
Cultivable waste Land 8.8(1.4%) 20.2 (4.4%)
Permanent pastures and other grazing Land
6.9(1.1%) 5.1 (1.1%)
Others 150.2(24.0%) 146.0(31.8%)
Net sown area 220.6(35.2%) 188.3(42.0%)
6. Irrigated area
Net irrigated area 81,882 ha 75,636 ha
Gross irrigated area 89,232 ha 83,532 ha
7. Average land holding 1.12 ha 2.1ha
8. Population 19,18,960 14,55,920
9. Population density 386 349
10. Literacy 71% 74%
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Small Industries Promotion Council of Tamil Nadu (SIPCOT)
Industrial Complex, an industrial hub, is located at about 10 km from
Tuticorin port. The industrial and commercial units in SIPCOT Complex
deal with marine based products, copper, chemicals, and warehousing.
Besides, a few companies exporting senna are also located within the
industrial complex. The agricultural economy of this district is largely
dependent on fishing and agricultural crops. Agriculture largely depends
upon the southeast monsoon.
3.5 Selection of respondents
Table - 2. Village Wise Selection of Respondents
S. No
Crop District Block Village
Total no. of
farmers in
villages
Selected farmers
from villages
1. Glory lily
Dindigul Oddanchatram (i) Paraivalasu 72 20
(ii) Ambilikai 65 20
(iii) Kallimandayam 100 20
(iv) Rotupudur 52 20
(v) Kappalpatty 64 20
2. Senna Tuticorin Srivaikuntam (i) Kasilingapuram 60 20
(ii) Chinnatha kurichi
72 20
(iii) Alanda 82 20
(iv) Savlaperi 62 20
(v) Deivaseyal puram
59 20
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(i). Selection of respondents
Random sampling technique was used to select the respondents
cultivating medicinal plants in the study area. Two hundred respondents
were selected randomly from the selected villages. Finally, the sample
constituted 100 respondents each for both the crops. The percentage
analysis used for simple composition.
(ii). Selection of extension personnel
The extension personnel in the Department of Horticulture were
considered as population for this study. Horticultural Officers (HOs) and
Assistant Extension Officers (AEOs) were selected for the study. In the
Office of Assistant Director of Horticulture in Tuticorin, all HOs and AEOs
available during data collection comprised the sample. HOs and AEOs
having knowledge about glory lily were selected for the study of glory lily.
(iii). Selection of market intermediaries
The market intermediaries in the study area were sampled. As far
as senna is concerned, simple random sampling technique was used to
select exporters and commission agents in Tuticorin city, whereas all the
exporters and brokers in Oddanchatram and Moolanur towns were
selected for the study of glory lily.
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3.6. Selection of variables and their measurement
Taking into consideration of the scope and objectives of the study,
initially 26 independent variables were identified on perusal of literature
and on consultation with scientists. Out of these 26 variables, 12
independent variables which have relevancy to the study were finally
selected.
3.6.1. Operationalization and measurement of independent variables
Independent variables relevant to the study were selected based on
the judges opinion. The reference sheet sent to judges is in Appendix-III.
Based on judges opinion, fifteen independent variables were selected for
the study. The operationalization and quantification of independent
variables are given below.
3.6.1.1. Age
Age was operationalized as the number of completed years of the
respondent at the time of inquiry and the chronological age was taken as
the measure. The respondents were classified into three categories
according to their age as developed by Trivedi (1963) and adopted by
Sudhakar (2007).
S. No Category Age group
1. Young Upto 35 years
2. Middle 36 to 45 years
3. Old Above 45 years
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3.6.1.2. Educational status
Educational status in this study was operationalised as the ability
of the respondent to read and write or the extent of formal education
possessed by the respondent at the time of enquiry. The scoring
procedure developed by Mansingh (1993) and adopted by Renjini (2000)
was used to measure the educational status of the respondents.
S. No Level of Education Score
1. Illiterate 1
2. Can read only 2
3. Can read and write 3
4. Primary school education 4
5. Middle school education 5
6. High school education 6
7. Higher secondary education 7
8. Collegiate education 8
3.6.1.3. Occupational status
Occupational status was operationalised as the extent to which
respondents were agriculturally occupied. The scoring procedure adopted
by Anandaraja (2002) was followed. According to him one who devoted
his/her full attention on farming alone would be able to pay much
undivided attention to his/her profession than those who had other
occupations besides farming. Hence, the following scoring procedure was
adopted.
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Occupation Score
Farming as a sole profession 4
Farming + Agricultural labourer 3
Farming + Business 2
Farming + Services (Salaried person) 1
3.6.1.4. Farm size
This refers to the extent of land cultivated by an individual at the
time of enquiry. The area was directly taken as a measure and
categorized into three, by using, the following procedure as adopted by
Srinivasan (1999).
S. No Category Area Score
1. Marginal farmer Less than 2.5 acres 1
2. Small farmer Between 2.5-5 acres 2
3. Big farmer More than 5 acres 3
3.6.1.5. Area under medicinal plant cultivation
This is referred to as the number of acres of land that the
respondent allocated especially for the cultivation for Aonla / Coleus/
Sweetflag / Aloe Vera at the time of inquiry. The total area under
medicinal plants cultivation was taken as such. Each acre under
medicinal plant was assigned with a score of two and the area with less
than one acre had a score of one. The scoring procedure followed by
Prabhakar (2000) was used in this study. Accordingly the respondents
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were classified into low, medium and high category using cumulative
frequency method.
3.6.1.6. Social participation
It refers to the participation of an individual farmer in different
formal organizations. The social participation was measured using socio-
political scale developed by Murali (1997) the scale was slightly modified
for the present study as below.
S. No Items Score
1. Member in the past 1
2. Office bearer in the past 2
3. Member at present 3
4. Member at present and office bearer in the past
4
5. Office bearer at present 5
3.6.1.7. Extension agency contact
This variable was measured in terms of frequency and the purpose
of contacting the different extension agents by the respondents. Each
score obtained by an individual and the frequency was multiplied with
the score of purpose of contact for every item and the scores were
summed up to arrive at a total score of contact with extension agency of
an individual. The scoring procedure followed by Sriram (1997) was used
with suitable modifications to suit the present investigation.
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S. No Frequency of
contact Score Purpose Score
1. Regular 3 Agriculture
2
2. Rare 2
3. Never 1 Non-agriculture 1
To classify the respondents into three categories of low, medium
and high cumulative frequency method was used.
3.6.1.8. Mass media exposure
The degree to which different sources of mass media utilized by the
respondents was measured based on the frequency of exposure and the
purpose of use as followed by Kalimuthu (2001) with slight modification.
For this, a number of mass media sources like newspaper, radio,
television, Internet, etc. constituted this variable. The degree of exposure
of respondents was recorded in a three-point continuum. Further the
purpose of use was also rated in a three-point continuum.
Frequency of exposure Score
Never 1
Occasionally 2
Frequently 3
Purpose of use
Entertainment 1
News 2
Agriculture 3
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3.6.1.9. Risk orientation
Risk orientation was operationalised as the degree to which the
respondent was oriented towards risk and uncertainty and has courage
to face the problems in adopting new ideas. The scale developed by Supe
(1969) and adopted by Purushothaman (2003) was followed. The scale
consisted of six statements of which, the first and fifth were negative and
the rest were positive.
Response Strongly Agree
Agree Undecided Disagree Strongly Disagree
Score for positive
statements 7 5 4 3 1
Score for negative
statements 1 3 4 5 7
The scores obtained for each of the statements were summed up to
get the individual respondent's risk orientation score. The range of score
in this scale was from 6 to 42. Based on the scores obtained, the
respondents were classified into low, medium and high using cumulative
frequency.
3.6.1.10. Scientific orientation
Scientific orientation was operationalised as the degree to which a
farmer was oriented towards the use of scientific methods in farming. The
scale developed by Supe (1969) and followed by Amirreddy (2003) was
used.
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The scale consisted of six statements of which, the second one was
negative. The rest of them were positive. The response for each statement
was rated over a five point continuum which ranged from strongly agree
to strongly disagree.
Response Strongly Agree
Agree Undecided Disagree Strongly Disagree
Score for positive
statements 7 5 4 3 1
Score for negative
statements 1 3 4 5 7
The maximum score an individual could get on this scale was forty-
two and minimum was six. The score for all statements were added upto
arrive at the total scientific orientation score of an individual. The
respondents were then classified into low, medium and high groups
based on the cumulative frequency method.
3.6.1.11. Cosmopolitness
In the study, cosmopolitness was operationally defined as the
tendency of the farmer to be in contact with outside world bared on the
belief that all the needs of an individual can not be satisfied within his
own community. The procedure followed by Purusothaman (2003) was
used to measure the extent of cosmopolitness the two dimensions of the
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variable measured were:
a) The frequency of visit to the nearest town in a month.
b) The purpose of visit to the town.
a) The frequency of visit to the nearest town in a month.
S. No Frequency Score
1. Twice or more a week 6
2. Once in a week 5
3. Once a in fortnight 4
4. Once a in month 3
5. Very rarely 2
6. Never 1
b) The purpose of visit to the town.
S. No Purpose of Visit Score
1. All Visits relating to Agriculture 6
2. Some what relating to Agriculture 5
3. Personal or domestic matters 4
4. Entertainment 3
5. All other purpose 2
6. No specific purpose 1
The total score of cosmopoliteness for each respondent was
calculated by adding the above two dimensions of comopoliteness.
3.6.12. Export potentiality
This variable was operationalised with the help of a series of
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question on export, export potential of the medicinal plants, price in the
world market. All the questions were in the form of objective type
designed to the test the knowledge of the farmer about the export
potential of the medicinal plant.
3.6.2. Dependent Variables
3.6.2.1. Knowledge level of medicinal plant growers
Knowledge is generally understood as an ultimate acquaintance of
an individual with facts. Bloom et at., (1956) defined knowledge as those
behaviour and test situation, which emphasize remembering either by
recognition or recall of ideas, materials and phenomena.
In the present investigation, knowledge denotes the farmer's
understanding of different medicinal plant cultivation techniques. To
measure this variable a teacher made test was followed.
The test included the main important technologies related to
medicinal plant cultivation. There were 20 objective type questions for
the farmers in this knowledge test for glory lily and senna at the rate of
10 questions for each crop. The test questions were selected from the text
book "production technologies for medicinal and aromatic crops" by
Farooqi et al. (1997) and also in consultation with horticultural
scientists.
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Each item of knowledge test was dichotomized into 'correct" and
"incorrect" response. Every correct response was assigned two score,
while the incorrect response received one score. The total score obtained
by the respondent on the knowledge test formed the respondent's
knowledge score. The maximum possible score one could obtain was
twenty for glory lily and twenty for seena. Knowledge index for each
respondent was calculated using the formula developed by Bhaskaran
and Praveena (1982).
KI = P
K x 100
Where KI denotes the knowledge index
K denotes the knowledge score by the respondent
P denotes the possible maximum score for all the medicinal plant
technologies
3.6.2.2. Extent of adoption of recommended medicinal plants
cultivation practices by the respondents
Rogers (1983) defined adoption as a decision to make use of an
innovation as the best course of action available.
In this study extent of adoption is operationalised as the extent to
which particular recommended practices on glory lily and senna
cultivation were adopted by an individual correctly without any distortion
of message.
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In order to study the extent of adoption of glory lily and senna
cultivation practices by the respondents nine major glory lily cultivation
practices and six major senna cultivation practices were selected in
consultation with the extension officials, researchers and based on the
available literature. The each respondent was asked about his adoption
or non-adoption against each item. The respondents were also asked to
mention the reasons for non-adoption.
A score of two was given for adoption and non-adoption was given
one score. The scores for all these items were added-up for each
respondent and his adoption score was arrived at. The formula for
adoption index adopted by Venkatakumar (1997) was followed in this
study.
Adoption index =
Percentage analysis was also worked out to study the practicewise
adoption of medicinal plant growers.
3.6.3. Constraints faced by the medicinal plant growers
In this study, the constraints were divided under two heads, viz.
production constraints and marketing constraints. Based on the
responses, percentage analysis was carried out to rank the constraints.
Respondent’s total score
Total possible score X 100
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3.7. Methods of data collection
Interview schedule is the tool having a set of questions, which are
used to gather data from the respondents by an interviewer in a face to
face situation. A well-structured interview schedule was prepared in
English taking into consideration the various objectives of the study.
Necessary precautions were taken to ensure that the questions in the
schedule were unambiguous, concise, complete and comprehensive.
Besides, the schedule was pre-tested in a non-sample area and
necessary modifications were carried out before the final administration.
The schedule is given in Appendix V. Preliminary visits were made to get
the basic data regarding the study area. Rapport was developed with the
respondents through informal discussion. Data were collected by
personal interview with the respondents in their farms and homes.
3.8. Statistical tools used
The data collected were analysed using (i) percentage analysis (ii)
cumulative frequency method and (iii) zero order correlation co-efficient
and (iv) multiple regression analysis.
3.8.1. Percentage analysis
Simple percentage analysis was employed to make simple
comparisons wherever necessary.
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3.8.2. Cumulative frequency method
The method was used to classify the variables into three categories
viz., low, medium and high by dividing the difference between the
maximum and minimum scores of a variable into three equal classes.
Where,
K = Median between lower limit of the class in which 11 occurs and
the upper limit of previous class
Li = Boundary values namely 11 and 12
Ċ = Square root of cumulative frequency upto classes in which
Li, lies
F = Square root of the frequency of the class in which the
median lies
H = Interval of the class
i) Below the L1 = Low
ii) Between the L1 and L2 value = Medium
iii) Above L2 value = High
3.8.3 Zero-order correlation co-efficient
Correlation was used to determine the relationship of the
independent variables with each of the dependent variable.
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This tool was used to find whether any significant relationship
existed between the Independent and dependent variables; the formula
used was
Where
n = sample size
xy = correlation coefficient
x = Independent variables
y = Dependent variables
Σxy = Sum of products of x and y
Σy = Sum of value of y
Σx = Sum of value of x
Σx2 = Sum of square of ′x′ values
Σy2 = Sum of square of ′y′ values
(Σx)2 = Square of sum of ′x′ values
(Σy)2 = Square of sum of ′y′ values
3.8.4 Multiple regression analysis
To find out the functional relationship between independent and
the dependent variables, multiple regression analysis was used.
The following is the general formula of multiple regression
equation.
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y = a+b1x1+b2x2+…………… + bnxn
Where,
Y = Dependent variable
A = intercept
x1 to xn = Independent variables
b1 to +bn = Partial regression co-efficient.
By adopting the methodology explained above, the data were
collected, coded, tabulated, analysed and interpreted.