Bio-Inspired Algorithms in Agriculture: A Review with Emphasis on Plant Disease Detection

Abstract

In India agriculture plays a significant role due to their population growth and food demands also increased. Traditional strategies used by farmers are not quit enough to meet this demand. So farmers have to increase their use of toxic substances to destroy the soil. This affects the agriculture land a lot and at last the land has no fertility. Hence, the need arises to enhance the crop yield. In order to increase the yield, to prevent the crop disease is more important. Plant disease is more critical threat in agriculture. In order to handle the issues brought through growing in populations, Machine Learning (ML) and Deep Learning (DL) have become more incorporated into agriculture. The most common problems in agriculture like, Climate Change (CC), Plant Diseases (PD), Pesticide Control (PC), Weed Management (WM) and Irrigation Management (IM). Bio-Inspired Algorithms often give promising solution for disease detection and enhancing the accuracy. This paper focuses on current agricultural challenges and emphasis the use of intelligent systems in disease detection.