Data Analysis and Prediction Using Big Data Analytics in Agriculture

Abstract

Big data analytics analyzes large sized data to discover useful and hidden patterns along with correlations/associations and other beneficial insights. Even though rapid developments in technology have taken place, and traditional agriculture practices are being followed in several countries (especially developing countries). In this regard, big data analytics possesses the capability to positively transform the agricultural domain. The agriculturists are heavily dependent on traditional practices to select suitable crop to grow and how to grow the crop in efficient and productive way. These traditional methods usually comprise of walking in fields, choosing soil samples for soil moisture analysis, and detecting plant diseases by observing the leaves manually. It is in fact significant for the agriculturists (especially farmers) to understand the importance of technology for gathering crop information in large quantities for transforming the collected data into meaningful knowledge. Integrating big data with the agricultural domain can bring about radical changes in how agriculture is being done currently. The technique of growing crops effectively can be well understood by the appropriate utilization of big data analytics. The three extensive areas which are transforming agriculture are accurate crop forecasts, precision farming, and generating high-quality seeds. This chapter is composed of four sections. The first section provides an overview of analytics on big data in agriculture. This is followed by the second section which will highlight the different big data techniques in agriculture. The third section describes two case studies that apply techniques for big data analysis in the agricultural domain. The fourth section analyzes the various research areas related to agriculture that can be explored by the academicians and researchers. The summary of the chapter is provided at the end.