Machine Learning Approaches for Crop Suitability Assessment and Disease Prediction (International Journal of Food and Nutritional Sciences, 2019)
A sizable portion of farmers, especially in India, lack the expertise needed to choose cropsand apply fertilizer in an intelligent manner. While machine learning algorithms haveachieved significant strides in automating the identification of diseases, several problemshave prevented Deep Learning from reaching its full potential. These include the need forhigh-quality training data, processing power limitations, and the models’ restrictedgeneralizability, all of which make application of the models difficult. An accessible andopen-source web application has been created to tackle these problems and maybe improveagricultural yield