Applying data mining techniques for better wheat crop management in gujarat state

Abstract

Agriculture data are highly expanded in provisions of nature, interdependencies and resources. The crop production primarily depends on weather conditions, diseases and pests, planning of harvest operation, geographical and biological factors etc. For balanced and sustainable development of agriculture these resources and factors need to be calculated, monitored and examined so that proper policy implication could be drawn. Agriculture data are increasing day by day. Since decades large amount of data are available in area of agriculture. Around 75% of the country s populations depend on the agro-based products or agriculture so we can say that agriculture is the backbone of the Indian economy. The agriculture production mainly depends on the climate conditions and highly influenced by the different environmental variables. Other parameters which affect the agriculture growth and productions are geographical and biological aspects, diseases and pesticides, planning of sowing and harvest process, etc. In current scenario, to monitor and maintain the agriculture resources it is necessary to have the stable and sustainable development of agriculture. newlineFor generating proper policy implication it s necessary to store the large amount of data in a normalized database. Data mining techniques are very much useful to extract the meaningful patterns from the available data. Many researchers and scientists already worked with the agriculture datasets and the research process is still continuing. The main objective of this research study is to apply the data mining techniques to wheat crop datasets to manage uncertainty and seasonal crop production and its forecast. Data mining techniques can also be helpful in many other aspects of agriculture.