Crop Prediction Using Machine Learning

  • Kevin Tom Thomas, Varsha S, Merin Mary Saji, Lisha Varghese, Er. Jinu Thomas


Agriculture is one of the most essential and widely practiced occupations in India and it has a vital role in the development of our country. Around 60 percent of the total land in the country is used for agriculture to meet the needs of 1.2 billion people, so improving crop production is therefore seen as a significant aspect of agriculture. Basically if we have a piece of land, we need to know what kind of crop can be grown in this area. Agriculture depends on the various soil properties. Production of crops is a difficult task since it involves various factors like soil type, temperature, humidity etc. If it is possible to find the crop before sowing it, it would be of great help to the farmers and the other people involved to make appropriate decisions on the storage and business side. The proposed project would solve agricultural problems by monitoring the agricultural area on the basis of soil properties and recommending the most appropriate crop to farmers, thereby helping them to significantly increase productivity and reduce loss. Our project is a recommendation system which makes use of different machine learning techniques such that it recommends the suitable crops based on the input soil parameters. This system thus reduces the financial losses faced by the farmers caused by planting the wrong crops and also it helps the farmers to find new types of crops that can be cultivated in their area.