Enhancing Crop Yield through Weed Density Estimation and Management: A Comprehensive Review

Weeds are significant adversaries to crop productivity, competing for vital resources and causing yield losses. Effective weed management is pivotal to attain optimized crop production. This review focuses on the assessment of weed density and its correlation with yield losses, aiming to enhance agricultural practices and productivity. Various methodologies, including remote sensing, image processing, machine learning algorithms, and data analytics, are explored for precise estimation of weed density. Integration of these technologies within the framework of precision agriculture allows for real-time monitoring and targeted weed control strategies. Understanding weed-crop interactions, considering factors such as weed species and environmental conditions, is vital for tailored management approaches. The synthesis of advanced technologies and data-driven insights enables efficient weed management, fostering sustainable agricultural practices. Continued research and innovation in this domain are crucial to refine and develop precise methods, ultimately promoting sustainable and maximized crop yields in modern agriculture.