Digitally-enabled crop disorder management process based on farmer empowerment for improved outcomes : a case study from Sri Lanka

We have developed a system facilitated by a mobile artefact to effectively identify crop disorder incidents and manage them using recommended control measures. This work overcomes the limitations of the existing attempts by using digital technology to empower farmers to identify crop disorders rather than replace them with automated techniques. Our approach empowers farmers by providing the information in context for them to identify crop disorders. The developed solution can identify most of the crop disorders instantaneously, irrespective of the crop or other factors that make crop disorder identification complicated. For the rest, it provides a mechanism to carry out a manual identification with the help of subject experts. The solution was deployed among paddy farmers in Sri Lanka to understand how well this could assist them in identifying and managing crop disorders. The system was able to identify 70.8% of the crop disorder incidents reported by the farmers and provided them with the relevant control measures. Farmers’ perceptions of various usability aspects of the solution revealed that the application of agrochemicals and expenses associated with agrochemicals were significantly reduced. It was also observed that the yield quality and quantity and overall revenue have increased compared to the previous seasons

Farmers as sensors : a crowdsensing platform to generate agricultural pest incidence reports

Over the years, the food produced for human consumption is lost or affected due to many factors. Among these, pest/disease incidence is one significant factor contributing to crop losses. Hence, early identification of the presence of pest/disease incidence is essential to manage crop losses. In Sri Lanka, farmers identify a pest/disease incidence by mainly relying on the input given by agricultural experts, and sometimes they rely on fellow farmers, pesticide dealers, and even on their own experience. The current approaches followed by the farmers to communicate the pest/disease symptoms to agricultural experts are not appropriate and resulted in many incorrect choices made by the farmers. In this paper, we discuss about an extension we proposed for a mobile application we developed for farmers in Sri Lanka called Govi Nena. This extension aimed to capture the conditions concerning pest/disease symptoms and climate present in the field to assist agricultural experts in the decisionmaking process. We consider each farmer as a sensor to capture information such as symptoms present in the crop, distribution of symptoms, affected parts of the plant, and growth stage of it. The enhanced version of the application was given to agricultural experts to understand their feedback in regards to this. The feedback was positive, and now, we have undertaken to deploy the application among several farmers based in Sri Lanka for testing purposes