Artificial Intelligence in Crop Disease Detection: Improving Early Diagnosis and Yield Protection
Keywords:
Artificial intelligence, crop disease detectionAbstract
Crop diseases pose significant threats to agricultural productivity and food security worldwide. Recent advances in artificial intelligence (AI) have enabled automated and accurate disease detection through image analysis and predictive modeling. This study evaluates the effectiveness of AI-based disease detection systems in identifying early-stage crop infections and reducing yield losses. Using field image datasets and machine learning models, the results demonstrate substantial improvements in diagnostic accuracy and crop protection outcomes compared to conventional inspection methods
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