Application note: crop-loss assessment monitor – A multi-model and multi-stage decision support system

Real-time knowledge about crop growth conditions is critical to make decisions about risk management and food security planning. Several crop forecasting decision support systems (DSSs) are available which use crop models, remote sensing, weather derivatives or statistical modelling. The results from such DSS are conditioned to the goodness of the model used and the assumptions made. This paper describes a web-based DSS– Crop-loss Assessment Monitor (CAM) for real-time crop growth monitoring, loss estimation, and insurance analytics using different methods at multiple times during the crop growth for rice, wheat, maize, soybean, pearl millet, sorghum, and groundnut. The core of CAM comprises of a set of databases and system-analysis components. Its modular design allows customization for different countries and policy scenarios. The potential of CAM in monitoring crop yield losses is illustrated for soybean crop in India.

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Bibliographic Details
Main Authors: Aggarwal, P.K., Shirsath, P.B., Vyas, S., Arumugam, P., Goroshi, S., Aravind, S., Nagpal, M., Chanana, M.
Format: Article biblioteca
Language:English
Published: Elsevier 2020
Subjects:YIELD LOSSES, CROP INSURANCE, CROP MONITORING, ASSESSMENT,
Online Access:https://hdl.handle.net/10883/20940
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Summary:Real-time knowledge about crop growth conditions is critical to make decisions about risk management and food security planning. Several crop forecasting decision support systems (DSSs) are available which use crop models, remote sensing, weather derivatives or statistical modelling. The results from such DSS are conditioned to the goodness of the model used and the assumptions made. This paper describes a web-based DSS– Crop-loss Assessment Monitor (CAM) for real-time crop growth monitoring, loss estimation, and insurance analytics using different methods at multiple times during the crop growth for rice, wheat, maize, soybean, pearl millet, sorghum, and groundnut. The core of CAM comprises of a set of databases and system-analysis components. Its modular design allows customization for different countries and policy scenarios. The potential of CAM in monitoring crop yield losses is illustrated for soybean crop in India.