Application of Bioinformatics in Agricultural Pest Management: An Overview of the Evolving Technologies

Human beings need some fundamental requirements to live, including food, drink, air, and shelter. Ever since the dawn of civilisation, they’ve been a source of contention among people. However, despite the rapid advancement of technology and the abundance of comforts available in today’s society, some basic needs have remained the same. This “fight for existence” continues to this day and will continue indefinitely. Pests and diseases often threaten the food crops lead to loss of production, availability of food which in turn affects the global economy. Modern molecular biology, microarrays, nanotechnology, and other advanced analytical techniques are helping to better understand the target pests and diseases. To cope with agricultural pests, as well as diseases that may be fatal, pest management techniques are being developed and modified in recent years. Current data suggest that further important plant protection tools would be introduced soon which could reduce the reliance on just insecticides to solve this issue. Computational biology, as an integrated subject, is increasingly finding its way into the development of pest control strategies. Fundamental data analysis in the research and development sector, as well as effective mass communication and information dissemination technologies, is used to establish direct connections with farmers and other grassroots people. Because of its enormous size, this stream has been found very essential and helpful in every respect. Bioinformatics is used in several pest control methods, either directly or indirectly, in this article few examples like pesticide design and screening, pesticide production optimisation, and pesticide toxicity prediction for a variety of chemicals have been discussed. We are moving in a new direction in pest control due to the current state of things as well as its popularity and applicability. In today’s climate, pest control requires more interdisciplinary contributions than ever before. As a consequence, the noble cause of food grain preservation before and after harvest should be addressed to feed a bigger population with less economic loss and to reduce sickness and high mortality rates. With the advent of data analytics, technology has become more prevalent in agriculture. One of the main challenges in using technology in agriculture is determining the effectiveness of big data analytics algorithms and their application methods.