Data Mining In Agriculture

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Abstract: Data mining is used to extract the information from the large dataset and used to predict patterns and behavior of an application. Data mining plays a chief role in the fields of e-commerce, healthcare sector, and agricultural sector. Agriculture is the prime occupation in India. Crop productivity mainly depends on weather conditions. Data mining is used in agriculture to predict crop productivity, water management, crop disease management, pesticide recommendation by using different algorithms. Image processing techniques are also widely used to identify crop diseases using images of affected crops. The purpose of this survey is to study data mining and image processing techniques used in crop disease prediction and identification. Keywords— Disease, Weather conditions, Prediction, Data mining, Image processing. I. INTRODUCTION…show more content…
about 70% of people are engaged in this activity Weather conditions play a vital role in the agricultural sector. The impact of changing climatic conditions like temperature, humidity and rainfall is crucial in the growth of crop diseases. It is necessary to prevent the crop diseases in order to enhance the crop production. Earlier the monitoring and analysis of crop diseases were carried out manually by an expert person in that field. The crop disease detection can be done using various data mining and image processing techniques. Data mining is the process of obtaining knowledge from vast data using various data mining algorithms. Predictive analysis is one of the important part of data mining. Image processing helps in agricultural sector for determining the crop diseases and for pesticide
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