Artificial intelligence and machine learning in weed management in field crops: A review

Abstract

Weed management is a critical challenge in modern agriculture, significantly affecting crop yields and farm profitability. Traditional weed control methods, such as manual weeding and chemical herbicides, have limitations, including high labour costs, environmental concerns, and the evolution of herbicide-resistant weed species. Recent advancements in artificial intelligence (AI) and machine learning (ML) offer innovative solutions for efficient and sustainable weed management. This review explores the applications of AI and ML in weed identification, classification, herbicide optimization, autonomous weeding systems, and decision support tools. The paper also discusses the challenges and future prospects of integrating these technologies into field crop management.