Post on 10-May-2020
Malaysian National PaddyPrecision Farming Project
Outlines
INTRODUCTION
PRECISION FARMING
RESEARCH ON PF OF RICE
PADDY SOIL VARIABILITY
PADDY WATER MANAGEMENT
CONCLUSION
INTRODUCTION
• The precision farming project for rice was started and implemented in Block C, Sawah Sempadan, Tanjung Karang, Selangor Malaysia.
• This was one of the biggest pilot projects for Precision Farming Studies.
• This7-year (2001-2007) project was initiated by Malaysian remote sensing agency (MACRES) together with agriculture-related agencies and Universiti Putra malaysia (UPM)
1. Ensuring the ability of nations to meet their national food security needs with a declining natural resources especially, land and water
2. How to boost annual rice production from 545 m.t to 700 m.t to feed an additional 1.3 billion rice consumers by 2025.
3. How to do so using less water and land. Currently Water Productivity Index is between 0.2-0.3 kg/m3 or 1 kg rice for every 3000 to 5000 litres of fresh water.
Is it possible to go for WPI=1.0 or 1 kg/1000 litres?
CHALLENGES INVOLVING RICE CULTIVATION IN ASIAAsia is home for 56% of humanity and 70% of the world’s 1.3 billion poor.Annual increase in population is 51 millionAsia produces and consumes 92% of the world’s rice
MADA
Besut (KETARA)IADP-PP
Kerian-Sg. Manik
Northwest Selangor Project
8 MAJOR GRANARY AREAS IN MALAYSIA
Seberang Perak
(96,405 ha)
(9,941 ha)
(29,989 ha)
(8,701 ha)
(18,195 ha)
KADA (31,440 ha)Kemasin-Semerak
(10,629 ha)
(5,164 ha)
Total acreage: 210,464 ha
Cycle of Precision Farming for Paddy
PF
Soil sampling
Soil map
Fertilizer application map
Yield measurement Yield map
Harvesting
Soil chemical analysis
Basal dressing application
Plant growth analysis
Topdressing application
Fertilizerapplication map
2 2 2 2 2 2 2 22 2 2 2 2 2 2 22 2 2 4 4 2 2 22 2 2 4 4 2 2 22 2 4 4 4 4 2 22 2 4 4 4 4 2 22 2 2 2 2 2 2 22 2 2 2 2 2 2 2
Plant growth map
Variable rate application
NATIONAL PROGRAM PRECISION FARMING FOR RICE Components and Participants
(1) a) Soil mapping - DOA
b) Soil Fertility Mapping - ECa UPM
(2) Yield mapping(Yield Sensor, GPS)
UPM, DOA
(8)GIS Analysis
and DSSUPM, MACRES
(5)Water Management
DID, UPM
(4)Remote Sensing
(Satellite and Airborne)MACRES
(9)Variable Rate Treatment
Application UPM
(7)Nutrient
ManagementMARDI, MACRES
(6)Integrated Pest
Management(Early warning system)
DOA
PRECISION
FARMING
NATIONAL PROGRAM
(3)Advanced Rice
TechnologyMARDI
(10)Farm ManagersDOA, IADP NWS
Project Area
•The project was conducted at Sawah Sempadan underTanjung Karang Rice Irrigation Scheme in Malaysia.
•The area is managed by IADA Barat Laut Selangor,Malaysia.
• Sawah Sempadan compartment consists of 1,468 lots with the total area at about 2,300 hectares, divided into 24 blocks.
•Block C in Sawah Sempadan compartment had 86 individual farmers and was chosen as the main study area.
STUDY AREA
The plots involved in the study are plot number 3117, 3121, 3168, 3172, 3176, 3151, 3155 and 3221. The Bernam river is the only source for irrigation supply in the Sawah Sempadan.
CHO
Eight selected plots of Block C in Sawah Sempadan,Tanjung Karang Selangor
Yield Mapping
Kriging or InverseSquared
Interpolation
Classification, contouring &
colouring
Calibration & Correction Representation and expert interpretation
Filtering and calibration
DGPS
Yield Sensor Latitude,
Longitude, Yield
Field data
Yield Map
Soil Variability Mapping
Soil Sampling
Electrical Conductivity
Lot X Y pH in H2O (uS/cm) % O.M % Carbon % Nitrogen (ppm)
Air Dry
3450 356426 382061 5.5 42 10.5 6.09 0.58 110.62576 359400 381712 5.2 49 7.11 4.12 0.43 46.42217 359906 380961 5.3 61 10.54 6.12 0.62 103.72133 360633 382066 5.2 54 6.85 3.97 0.38 23.82501 359500 383003 5.1 433 9.41 5.46 0.43 71.92114 360251 382597 5.1 54 10.48 6.08 0.51 502359 358806 380332 5.4 65 5.54 3.21 0.41 147.92879 357328 380417 5.6 63 5.54 3.21 0.41 413913 355850 382859 5.6 89 9.25 5.37 0.25 27.53403 356403 381295 5.4 47 5.04 2.92 0.3 13.63378 357138 381325 5.4 160 9.97 5.78 0.51 5.092955 358423 382128 5.2 276 7.54 4.38 0.33 65.42789 357709 381771 5.3 272 4.72 2.74 0.27 36.22284 359606 380024 5.4 69 5.76 3.34 0.32 34.13150 5 75 8.74 5.07 0.35 42.93943 5.1 335 6.13 3.56 0.34 632109 360829 382374 5.2 122 10.44 6.06 0.53 45.13736 5.2 66 3.41 1.98 0.21 15.6
INTERPOLATION
CALIBRATIONpHCECN,P,K, etc…
Water Management
SCADA SYSTEM
Variable Rate Treatment
Action MapHerbicides
Action MapFertilizer
Action MapInsecticides
Action MapWater Management
C1
C2
0102030405060708090
100
0 10 20 30 40 50 60 70 80 90 100
% sand
% c
lay
clay
siltyclay
siltyclay loam
silt loam
silt
loamsandy loam loamy
sand sand
sandy clay loam
sandy clay
clay loam
Textural Class of Paddy Soils at TAKRIS
Soil sampling locations
GIS MODELING
Statistical Analysis
Modeling
Action MapAction MapAction MapAction Map
Field Information
SCOPES•The research focused on the development of Spatial Decision Support System (SDSS) for efficient management of paddy farms.
•The targeted users of the system are the farmers representatives and the farm managers.
•The system was designed and developed only for paddy crop.
•Fertilizer recommendation maps were produced and derived from the soil data collected by the soil fertility mapping components and the nutrient management components
OUTCOMES
The outcomes of this research is the Paddy GIS program which contains the following modules such as: -
•Mapping modules•Water Management module•Pests and diseases module•Rice check module (farming activities)•Soil Plant Analysis Development (SPAD) meter module•Fertilizer management module•Record management module
OUTCOMES
The list of fertilizer recommendation maps produced by the program are:-
•Maps of Nitrogen (N), Phosphorus (P) and Potassium (K) From Soil Sample
•Maps of Nitrogen (N), Phosphorus (P) and Potassium (K) From EC Mapping
•Maps of Nitrogen from SPAD data
• Soil data collected from EC groups• Fertilizers algorithm Variable Rate
Technology Group• Yield data collected from harvester• Yield record collected from Integrated
Agriculture Development Area• Pest and disease records collected from crop
protection and Plant Quarantine Division, Department of Agriculture Malaysia
• Data from SPAD reading• Rice Irrigation Management Information
System (RIMIS) program
LIST OF INPUT DATA
DATA SOURCES
The sources of data used to access the nutrient contents
Data from various sources produces different maps. For example, data from soil sampling and soil EC are able to produce N, P and K fertilizer maps while data from SPAD only able to produce N fertilizer map.
Data sources and its data output
Variable Rate Technology Chlorophyll Meter
(SPAD) Reading
Rice Irrigation Management Information System (RIMIS) program
ADVANTAGES
♦ Paddy planting and related activities schedule♦ Fertilization schedule♦ Variable application map for fertilizer♦ Module for farmers♦ Module for managers♦ Special Bahasa Malaysia interface for farmers♦ Water management module♦ Pests management module♦ Diseases management module♦ Yield management module
COMPONENT OF PADDY GIS
There are three main components in the development of Paddy GIS program. The components of the Paddy GIS program are
• GIS
• Graphical User Interface (GUI)
• Database.
COMPONENT OF PADDY GIS
Main components in Paddy GIS program
COMPONENTS OF PADDY GIS •The program used Microsoft Access database which is a Database Management System (DBMS) software to store yield, pest and diseases records in the database.
• GIS data are displayed in the computer based system. Users able to produces the digital and hardcopy maps of fertilizer recommendation input, printed maps and updates the pest,diseases, and yield records in the database
• GUI to enable the user to access the program in an easy manner.
STEPS ON DEVELOPMENT OF PADDY GIS
The development of Paddy GIS involved the following steps : -
•User Analysis study
•Data collection
•Database design and development
•Development of User Interface
•Development of fertilizer application maps
•Installation of Paddy GIS program
•Training
System architecture
• Program written in Visual Basic Development Environment
• Required the Spatial Analysis Extension
• Involved the programming in Visual Basic for Applications in ArcGIS development environment
• Used Microsoft Access as Database Management System (DBMS)
• Installed at the Integrated Agriculture Development Area (IADA) Barat Laut Selangor, Kuala SelangorSelangor
ABOUT THE PADDY GIS 1.5
PADDY GIS USERS
This program was designed to be used for many users including irrigation engineers of “BPSP”, manager (“Pengurus”) at Barat Laut Selangor and groups of farmers representatives.
IMPLEMENTATION
PADDY GIS MAIN MENU
Paddy GIS program is able to produce the fertilizer maps and provide decision tools for water management at the paddy field.
SAMPLE INTERFACE OF PRECISIONFARMER PROGRAM VERSION 1.5
SYSTEM USERS
MAIN MENU
WORK SCHEDULE
FERTERLIZER RECOMMENDATION INTERFACE
INTERPOLATION INTERFACE
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGEN (N) , PHOSPHORUS (P) POTASSIUM (K)
DATA SOURCE : FROM VERIES MACHINE, EC READING
SEASON : SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGEN (N)
DATA SOURCE : FROM CHLOROPHYLL METER
SEASON : 21-25 DAYS AFTER SEEDING SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGEN (N)
DATA SOURCE : FROM CHLOROPHYLL METER
SEASON : 35-40 DAYS AFTER SEEDING SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGEN (N)
DATA SOURCE : FROM CHLOROPHYLL METER
SEASON : 50-54 DAYS AFTER SEEDING SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGEN (N)
DATA SOURCE : FROM CHLOROPHYLL METER
SEASON : 64-68 DAYS AFTER SEEDING SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF NITROGREN (N)
DATA SOURCE : FROM SOIL SAMPLING
SEASON : SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF PHOSPHORUS (P)
DATA SOURCE : FROM SOILSAMPLING
SEASON : SEASON 1/2007.
PLOT NUMBER : 3221
MAP NAME :FERTILIZER RECOMMENDATION MAP OF POTASSIUM (K)
DATA SOURCE : FROM SOILSAMPLING
SEASON : SEASON 1/2007.
PLOT NUMBER : 3221
DICUSSION
• Maps for N, P and K can be generated using three data sources which are data from SPAD meter, data from soil sampling and data recorded using Veris EC sensor.
• Nitrogen is supplied usually four times after the crop is planted in the paddy field. The reading to measure the Nitrogen contents in the leaf is taken using the SPAD meter. From the data taken by SPAD meter, maps for Nitrogen fertilizer application are generated by the Paddy GIS system
• Veris EC sensor also able to supply the data source for maps generation of N, P and K.
CONCLUSION
This research has shown how the principles of precision farming can be translated into practical use by the farmers. The ability to produce and use fertilizer recommendation maps will certainly optimize on the fertilizer inputs and maximize the yield of the precision farming.
Acknowledgements
Special thanks to Remote Sensing Malaysia, Department of Agriculture, IADA Barat Laut Selangor, BPSP, DID, MARDI, member of the Spatial Research group (SRG) and the members of the Precision Farming Engineering Research and Development (PREFERD) group at the Department of Biological and Agricultural Engineering and ITMA, UPM for their collaboration and cooperation.