Improving Farm Practices with Automation
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1 Improving Farm Practices with Automation Geospatial Applications in Mitr Phol Sugar, Thailand Saravanan Rethinam Geospatial Agriculture Specialist THAILAND Presented at GEO SMART ASIA 2017 Seminar on Agriculture and Plantation 23 Aug 2017
2 Outline 1. Sugar Industry Thailand and Mitr Phol 2. Smart technologies in Mitr Phol Mobile Mapping Crop forecasting Towards Precision Farming 3. Challenges and way forward 4. Summary
3 Thailand Sugar Industry 4th PRODUCER 2nd EXPORTER 53 Sugar Mills 1.75 million ha Sugarcane Other major crops Area in mln Ha Rice 10.2 Cassava 1.35 Corn 1.13 Rubber 2.92 Total agriculture land 20.8 mln ha
4 Mitr Phol Group 1st THAILAND ASIA 5th GLOBAL 6 Sugar mills 1 Sugarcane juice Ethanol 360,000 ha contract farming 70% area <3 ha Average yield t/ha 80% area under rainfed
5 Mitr Phol in Diversified Green Business Research & Development Sugar Product of Highest QualityFriendship with High Value Pulp & Paper Saving the Forest & the Planet for All Biomass Power Lighten the Opportunity for the Clean World Particle Board Saving the Forest & the Planet for All Liquid Fertilizer Ethanol Renewable Energy Friendly to Environment Zero waste
6 Crop Management Operations Land Survey Inputs/finance Crop estimation Cane supply and logistics Contract Agreement Crop monitoring and Advisory Harvest Planning
7 Growth of Geospatial Technologies 1 Sugarcane 2 Cane Forecast Information System 3 Management System SMART Agriculture Crop Intelligence (Smart DSS) Precision farming E- farming tools Remote Sensing GIS GPS Remote sensing Simulation model Web data system RADAR UAV Analytics Scenario Model Weather sensors Big data Analytics, Decision tools Mobile Apps
8 PHASE - I Sugarcane Information & Management System (SIMS) Finance, Cane quantum & quality online WEB GIS TABLET Cane Management &Monitoring
9 Web SIMS An User friendly DSS Individual fields are mapped Farmers, Field and crop data are collected with Tablet device User friendly reporting for decision making
10 Geo-Informatics Applications are. Estimate area and production Suitable area for expansion Faster contract agreement Applications Soil / Crop condition monitoring Productivity gap area assessment Pest and disease mapping
11 Recognitions
12 Benefits of Geo-Spatial Technologies Problems before SIMS Solutions Benefits Where is the field? Does it really exist? How much exact area? Crop estimation is inaccurate Finance outstanding rate was high Reporting takes longer time GPS based field level mapping Farmer, Farm and field data entered using mobile Real time connectivity Satellite for crop health harvest / monitoring Field mapping with accuracy more than 97% Reduce loan processing time 16 days to 3 days Online field scout saves time and reduce error Improve farmers cane yield 2-5% Efficient planning, monitoring.
13 Crop Production Forecast System Satellite Crop area Crop scout Crop condition Weather Crop management Soil property Crop Yield Simulation Models Historical statistics Trend & scenario analysis Production forecast
14 Yield Tons/ha Production Simulation Mill /14 Mill /15 Mill /14 Mill /15 0 Estimated accuracy of 93% at regional scale average in 3 years
15 Precision Farming is. Yield variability within Field Yield variability Determine within the Field factors Weather Soil property Nutrient availability Soil Moisture Variety Crop Management Benefits Optimize Yield and Profit Optimize Resource Save Environment Sustain Raw Material Action 4 Pillars Right Thing Right Time Right Amount Right Place
16 Our Frame Work of Precision Farming
17 GPS guided farm operations Land Consolidation Field lay out design changed to facilitate mechanization using GPS guided tractors (RTK + Base station) Contour planting Controlled traffic (less compaction) Reduce cost of cultivation Improves Yield
18 UAV in Large Farms Vegetation health monitoring Gap in plant population Contour planting Plant density detection Crop health Crop height NDVI Normalized Difference Vegetation Index Online Analysis with Micasense
19 Challenges ONE SIZE DOES NT FIT Smaller farms requires consolidation / co-operative farming approach to make PF cost effective Generating huge amount of field data. How to effectively integrated with other data sources for convert into valuable and actionable information Information and services just-in-time throughout Food value chain from Farm to market/ Consumer are vital
20 Collaborative approach Government Research Farmers Business.with Open innovation and collaboration
21 Summary Since 2002 Mitr Phol Group applied Geospatial technologies progressively Realized significant benefits to both farming community and business Implementing new technologies towards modern and precision farming in larger farms Challenge ahead is high tech for small farms collaborate with institutes for faster innovation and adoption
22 ACKNOWLEDGEMENT MITR PHOL Innovation and Research Centre MITR PHOL Plantation MITR PHOL Cane GIS
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