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Farmers grind away in the fields to take home just an exiguous income. Now, the agriculture industry is already a burdened industry with uncertainties from all directions. One of the major issues the industry is facing is crop loss. In India, every year around 30-40 per cent crops are lost. This has adverse effects on food security of the highly populated nation. For that matter, India is the 16th hungriest country in the world. Thus, there is a need to identify, understand and overcome agronomic losses. Extreme climate events and crop diseases are the two major reasons for crop losses. While climate events are less controllable, plant disease prevention becomes an important area of interest. Detecting plant diseases at early stages using images serves as key to preclusion of severity. In this paper, we have surveyed some of the significant papers on plant disease detection using image processing. [ABSTRACT FROM AUTHOR]

India is one of the hugest rice cultivating country in the world. For thousands of years rice is a most major food, consequently every mankind depends on it directly and indirectly. But the Main hindrance in rice production is rice leaf diseases. It greatly reduces the production rate. Rice leaf diseases have specific symptoms that cannot be easily identified by usual human's eye. Using one of the image processing techniques, the rice leaf diseases are detected efficiently. In order to detect the diseased image Median Filter, K-means Clustering, GLCM and SVM classifier algorithms were proposed. Accuracy, Precision and ROC of SVM classifier were calculated as performance metrices. Around 97±2 % accuracy was achieved in this method. This paper discusses the efficient methodology for rice leaf disease detection. By using proposed method diseased leaves are identified at the early stage, which can aid farmers in preventing further damage to their crops. [ABSTRACT FROM AUTHOR]

The backbone of India and even most parts of the world is agriculture. Maintaining perishable farm produce is important to not to waste it, which will impact the economy and food starvation. This paper presents a mobile application for farmers or farm produce owners to check the ripeness of fruits and vegetables, which will be useful to make decisions on selling and fixing the price based on grading. The application provides information on different ripening stages of the fruits and vegetables. It also presents the information on crop's requirements for growth in terms of soil, nutrients, weather conditions, season, etc., as a reference manual. In this work, firstly, identification of different stages of ripening of perishable farm produce in field/cold storage using image processing is performed. Secondly, a mobile application is developed to give real-time status and notification of farm produce. The application will be updated with the images taken by CCTV or mobile cameras at definite intervals and notify the product owner well in time before rotting of the produce. The assessment of fruit quality is important for the cultivator and the consumer. Maturity detection is very important for fruit/ vegetable warehouses. This fruit maturity mobile application is named "Krishi Seva Bandhu". The results show that the detection accuracy is 90% and the mean opinion score of farmers is 85%. [ABSTRACT FROM AUTHOR]