Disease and Nutrient Deficiency Detection in Cotton Plant

Cotton is one of the most important fibre crop which plays very important role in economic and social affair of people, especially in India, but if disease like Alternaria Leaf Spot and deficiency of some major nutrients goes undetected in then it can reduce as much as 25% of total production. This will be marginally beneficial for farmers to increase the production of crop and have a better profit out of it. Among different diseases, focus has been made on 'Alternaria Leaf Spot' as it is the most dangerous and frequently found disease on cotton plants in India. Deficiencies of major nutrients like Nitrogen, Potassium, Phosphorous, Manganese, Molybdenum, Chlorine and calcium has also been detected in this research. Image processing method has been selected after complete analysis of previously used methods and techniques, and so it has been proposed in this paper. Complete working flow of the system has been proposed. Algorithms that give best results have been selected and modified when needed. Template matching and color histogram algorithms have been used for detection. Complete analysis and comparison has been made with previously used techniques. After implementing the code on large number of cotton images taken from different locations, result and conclusion has been made. Results show how this research is more useful and practically more feasible than previous researches.