AI for Crop Improvement

Abstract

The introduction of high-performance genomic technologies into plant science has resulted in the generation of huge volumes of genomic information. Moreover, for biologists to deal with such complex, voluminous dataand infer some significant findings in order to improve crop quality and quantity has presented a big challenge to them. The advent of Artificial Intelligence (AI), Machine learning (ML) and Deep Learning (DL), facilitated automated tools for more efficient and better analysis of the data. Another crucial process that needs to be automated in field farming is the timely and precise diagnosis of crop diseases which plays a vital role in the prevention of productivity loss and reduced quantity of agricultural products. ML provides a solution to solve these problems by automatic field crop inspection. Recently, DL techniques have been widely applied for processing images to obtain enhanced accuracy. This chapter describes the need of AI in Agri-Genomics; it also includes various contemporary AI solutions for the Crop Improvement process and presents the proposed AI-based Crop Improvement Model (AI-CIM).