Artificial Intelligence for Pest and Disease Monitoring in Eucalyptus Plants: Systematic Literature Review
Abstract
Eucalyptus plants, renowned for their economic and environmental significance, are cultivated globally. Despite their value, these plants are vulnerable to pest and disease attacks, impacting productivity and quality. Accurate and timely monitoring is required to control pests and diseases in eucalyptus plants. The conventional method of human-based direct observation for monitoring pests and diseases in eucalyptus plants is fraught with weaknesses. Therefore, efforts are needed to enhance the effectiveness and efficiency of monitoring pests and diseases in eucalyptus plants through artificial intelligence or AI technology. AI is used to automatically detect and classify pests and diseases in eucalyptus plants using machine learning or deep learning algorithms and image processing. This study aims to provide a comprehensive review of the use of AI for detecting pests and diseases in eucalyptus plants using the Systematic Literature Review (SLR) method. Through this approach, this study identifies, evaluates, and analyzes relevant literature on the research topic from various digital sources. This study also provides an overview of the latest developments, methods used, and results achieved, as well as challenges and opportunities in the field of AI research for detecting pests and diseases in eucalyptus plants.
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