Proposed decision support system (DSS) for Indian rice crop yield predictionfor activating peroxymonosulfate in degradation of naphthol green B

Document Type

Conference Proceeding




School of Science




Originally published as:

Gandhi, N., Armstrong, L. J., & Petkar, O. (2016, July). Proposed decision support system (DSS) for Indian rice crop yield prediction. In Technological Innovations in ICT for Agriculture and Rural Development (TIAR), 2016 IEEE(pp. 13-18). IEEE.

Original article available here.


Rice crop production provides more than 40% to overall crop production in India and is essential in ensuring food security. Its production is reliant on favorable climatic conditions. Improving the ability of farmers to predict crop productivity under different climatic scenarios, can assist farmers and other stakeholders in making important decisions in terms of agronomy and crop choice. This paper proposes a decision support system prototype for rice crop yield prediction for Maharashtra state, India. A Graphical User Interface (GUI) has been created in Java using NetBeans tool and Microsoft Office Access database for the ease of farmers and decision makers. The interface allows for the selection of the range of precipitation, minimum temperature, average temperature, maximum temperature and reference crop evapotranspiration and predicts the expected class of yield viz., low, moderate or high. The ranges of the parameters were calculated by using historic data from the study area. The classes for the yield were defined as low with 0.15 to 0.60 tonnes/hectare; moderate with 0.61 to 1.10 tonnes/hectare and high with 1.11 to 3.16 tonnes/hectare. The proposed prototype could be used for a bigger dataset and wider study area to predict the crop yield. This will provide a guide to the farmer to assist in decision making on potential crop yield for particular climatic scenario.




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