A Comprehensive Survey of Classification Algorithms for Formulating Crop Yield Prediction Using Data Mining Techniques

Abstract

As we are aware that agriculture is one of the occupations that have a high impact on the countries economy and hence the crop productivity plays a major role. According to the latest survey, today agriculture contributes 17 percent of our countries GDP and about 60 percent of the peoples in the county are dependent on agriculture for their daily needs. The farmers are the backbone of the country; they play a vital role in feeding the entire population of the world. Farming is a beautiful relation between the farmer and the soil; the process of farming is an art that involves various techniques and practices, the productivity of the crop depends on various factors that include soil fertility, weather condition, harvesting period and the practices the farmer follow. In the current situation, the farmers are struggling to get an expected yield from the crop because of various reasons that include large climatic changes and lack of guidance. The objective of this study is to collect the historical data of agriculture, analyze them to predict the crop yield. With the advancement in today’s technology, it is possible to provide suggestion to the farmer regarding the crop selection and the practices to get expected crop yield. One such technique that is gaining more popularity in the field of agriculture is data mining. Data mining uses the large historical data sets to create a new pattern to obtain the knowledge that helps in suggesting the farmers on selecting the crops depending on various available parameters and also helps in estimating the production of the crops.