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AUTHOR(S): Sagir Ibrahim, Aisha Ibrahim Gide
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ABSTRACT Cotton is a commercial and fiber crop that generates profit for agronomists. Cotton crops are harmed by excessive water use, soil degradation, and the use of harmful pesticides and fertilizers. Cotton diseases and sucking pests are the two biggest threats to the crop's rapid growth. In this study, an overview of previous researches has been carried out utilizing machine learning and its advanced learning techniques, as well as image pre-processing and segmentation techniques, to detect and classify various diseases and pests. To identify the specific cotton diseases and pests under study, as well as overall performance based on the various metrics used. Our findings shows that machine learning and its advanced learning techniques outperform traditional image processing techniques in terms of exactness and other viable methodologies. |
KEYWORDS Cotton Pests and Diseases, Soil Degradation, Machine Learning, Agronomists, Image Pre-processing, Segmentation Techniques |
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Cite this paper Sagir Ibrahim, Aisha Ibrahim Gide. (2025) Pests and Diseases Detection of Cotton Crops Using Artificial Intelligence based Techniques: A Review. International Journal of Agricultural Science, 10, 19-26 |
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