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Spatial Rice Decision Support System for Effective Rice Crop Management


Affiliations
1 Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
2 Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad - 500 059, India
 

Rice, a widely grown crop all over the world provides food security to millions of people. The average productivity of rice in India is still low due to diversified environments under which it is being cultivated. Prediction and assessment of rice yields needs simplified precision models. A spatial rice decision support system (SRDSS) was designed by integrating ClimGen climate model and Oryza2000 crop model with soil and weather layers. This DSS facilitates input model parameters and geo-referenced maps to predict rice yield at polygon/pixel level. SRDSS is useful to researchers and planners not only in estimating rice yield but also to estimate optimum crop sowing dates and management practices to achieve target yield for the selected location. Further, SRDSS will be integrated with weather sensors to generate real time advisories to farmers at each level of decision making and to plan and achieve the targets of doubling the farmer’s income by 2022.

Keywords

ARCGIS, ClimGen, Oryza2000, Rice Yield, SRDSS.
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  • Spatial Rice Decision Support System for Effective Rice Crop Management

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Authors

B. Sailaja
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
S. R. Voleti
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
D. Subrahmanyam
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
P. Raghuveer Rao
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
S. Gayatri
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India
R. Nagarjuna Kumar
Central Research Institute for Dryland Agriculture, Santoshnagar, Hyderabad - 500 059, India
Shaik N. Meera
Indian Institute of Rice Research, Rajendranagar, Hyderabad - 500 030, India

Abstract


Rice, a widely grown crop all over the world provides food security to millions of people. The average productivity of rice in India is still low due to diversified environments under which it is being cultivated. Prediction and assessment of rice yields needs simplified precision models. A spatial rice decision support system (SRDSS) was designed by integrating ClimGen climate model and Oryza2000 crop model with soil and weather layers. This DSS facilitates input model parameters and geo-referenced maps to predict rice yield at polygon/pixel level. SRDSS is useful to researchers and planners not only in estimating rice yield but also to estimate optimum crop sowing dates and management practices to achieve target yield for the selected location. Further, SRDSS will be integrated with weather sensors to generate real time advisories to farmers at each level of decision making and to plan and achieve the targets of doubling the farmer’s income by 2022.

Keywords


ARCGIS, ClimGen, Oryza2000, Rice Yield, SRDSS.

References





DOI: https://doi.org/10.18520/cs%2Fv116%2Fi3%2F412-421