CROP DISEASE SOLUTION BY EXPERT AND MACHINE LEARNING
Ritesh Vilas Amrutkar, Suraj Narayan Kanthale, Abhishek Shivaji Ghute ,
Amol Ratan Borse, Mr. M.N.Jadhav(Guide)
Department of Computer Technology
K.K Wagh Polytechnic, Nashik, India 422009
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Abstract - Considering the population growth rate of recent years, a doubling of the current worldwide crop productivity is expected to be needed by 2050.Diseases are a major obstacle to achieving this productivity outcome. Therefore, it is very important to develop efficient methods for the automatic detection, identification, and prediction of pests and diseases in agricultural crops. To perform such automation, Machine Learning (ML) techniques can be used to derive knowledge and relationships from the data that is being worked on. This paper presents a literature review on ML techniques used in the agricultural sector, focusing on the tasks of classification, detection, and prediction of diseases and pests, with an emphasis on tomato crops. This survey aims to contribute to the development of smart farming and precision agriculture by promoting the development of techniques that will allow farmers to decrease the use of pesticides and chemicals while preserving and improving their crop quality and production.The technology based modern agriculture industries are today‟s requirement in every part of agriculture . In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn‟t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provides solution by using image processing techniques. We have used Android Studio to develop the system. The crops diseases solution system is compared the image of affected crops with database of Crops Diseases Detection and Solution system. If Diseases Detection and Solution system detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
Key Words: Plant Diseases, Precision Farming, Machine Learning; Smart Farming, Crop Disease.
