Transforming weed management in sustainable agriculture with artificial intelligence: A systematic literature review towards weed identification and deep learning

Precision Agriculture Identification
DOI: 10.1016/j.cropro.2023.106522 Publication Date: 2023-11-14T20:29:41Z
ABSTRACT
In the face of increasing agricultural demands and environmental concerns, effective management weeds presents a pressing challenge in modern agriculture. Weeds not only compete with crops for resources but also pose threats to food safety sustainability through indiscriminate use herbicides, which can lead contamination herbicide-resistant weed populations. Artificial Intelligence (AI) has ushered paradigm shift agriculture, particularly domain management. AI's utilization this extends beyond mere innovation, offering precise eco-friendly solutions identification control weeds, thereby addressing critical challenges. This article aims examine application AI context detection impact deep learning techniques sector. Through an assessment research articles, study identifies factors influencing adoption implementation These criteria encompass (food safety, increased effectiveness, eco-friendliness herbicides reduction), (capture technology, training datasets, models, outcomes accuracy), ancillary technologies (IoT, UAV, field robots, herbicides), related methods (economic, social, technological, environmental). Of 5821 documents found, 99 full-text articles were assessed, 68 included study. The review highlights role enhancing by reducing herbicide residues, effectiveness strategies, promoting judicious use. It underscores importance capture accuracy metrics implementation, emphasizing their synergy revolutionizing practices. Ancillary technologies, such as IoT, UAVs, AI-enhanced complement capabilities, holistic data-driven approaches control. Additionally, influences economic, dimensions Last least, digital literacy emerges crucial enabler, empowering stakeholders navigate effectively contribute sustainable transformation practices
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