Implementation of Conventional and Smart Weed Management Strategies in Sustainable Agricultural Production

ABSTRACT Conventional weed management is known for the use of selective herbicides, tackling issues of herbicide‐resistant weeds, and endeavors to reduce reliance on herbicides, such as employing biological control of weeds and incorporating allelopathy. These strategies are integrated with traditional and other conventional weed management techniques. New challenges in agricultural production, such as declining population involved in agriculture, global warming, and climate changes make conventional weed management inadequate. Rapid advancements over the past decade in artificial intelligence (AI), unmanned aerial vehicles (UAVs), cameras, and sensors, necessitate the development and implementation of smart weed management (SWM) approaches for the 21st century. Wise weed management practices can control weeds and reduce emissions of methane (CH 4 ), carbon dioxide (CO 2 ), and nitrogen dioxide (NO 2 ). Minimizing the use of herbicides in tandem with the application of smart technologies, like weed mapping and identifying spatial variability of weeds using proximal and remote sensors, multispectral and RGB cameras, can effectively manage weeds while also reducing labor costs. The SWM strategies also encompass the integrated use of organic herbicides, bioherbicidal products, and the judicious application of both organic fertilizers and inorganic fertilizers for weed management. Some approaches, such as alternate wetting and drying (AWD), can contribute to both SWM and carbon credits to farmers. The utilization of computing power, weed control robotics, and big data, combined with the education of the next generation of weed scientists and efforts to shift growers' attitudes and behaviors in weed management, may vary among countries. It requires active collaboration between agricultural extensionists and policymakers.