Bioinformatics in Agriculture and Ecology Using Few-Shots Learning From Field to Conservation

The integration of bioinformatics with contemporary machine-learning algorithms is transforming sustainable practices and conservation activities in biology and agriculture. Plant disease identification is an area where few-shot learning (FSL) excels because of data scarcity. This study applies FSL to computational biology to tackle agricultural and environmental concerns. Bioinformatics has a significant influence on sustainable farming and research, according to the report. The chapter introduces few-shot learning, and shows how it may address the lack of labelled data in several disciplines. Case studies, including explanations, demonstrate the manner in which the FSL method is widely used in ecological surveillance, environmental programs, and crop supervisors. The essay discusses ethical issues around machine learning in ecological systems and agriculture, emphasizing open and responsible data methods.