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Machine Learning Algorithms for Predictive Pest Modeling
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Author(s): Muhammad Umair Sial (Department of Entomology, University of Agriculture, Faisalabad, Pakistan), Rashad Rasool Khan (Department of Entomology, University of Agriculture, Faisalabad, Pakistan), Rizwan Ahmed (Department of Entomology, University of Agriculture, Faisalabad, Pakistan), Zain ul Abdin (Department of Entomology, University of Agriculture, Faisalabad, Pakistan)and Umm E. Ummara (Department of Zoology, Wildlife and Fisheries, University of Agriculture, Faisalabad, Pakistan)
Copyright: 2024
Pages: 22
Source title:
Revolutionizing Pest Management for Sustainable Agriculture
Source Author(s)/Editor(s): Muhammad Zia Ul Haq (Department of Agronomy, University of Agriculture, Faisalabad, Pakistan)and Iftikhar Ali (Department of Agronomy, University of Agriculture, Faisalabad, Pakistan)
DOI: 10.4018/979-8-3693-3061-6.ch014
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Abstract
Effective management of crop pests is crucial due to their detrimental impact on productivity. Therefore, it is imperative to prioritize early detection and prevention strategies. Machine learning methodology is being employed to forecast crop pests by utilizing data from different modalities. The utilization of machine learning applications is significantly influencing the worldwide economy through the alteration of data processing techniques and decision-making processes. It devises effective techniques for automatically detecting, identifying, and forecasting pests and diseases in agricultural crops. The objective of this chapter is to enhance the advancement of smart farming and precision agriculture by advocating for the development of techniques that enable farmers to enhance the quality and yield of their crops.
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