Adoption of AI-Based Crop Disease Detection Systems for Precision Agriculture
Keywords:
Artificial intelligence, crop disease detection, precision agricultureAbstract
Artificial intelligence–based crop disease detection systems are increasingly used to enhance precision agriculture and reduce yield losses caused by late or inaccurate disease diagnosis. This study evaluates the effectiveness of machine-learning-driven image recognition systems for early detection of crop diseases in small and medium-scale farming systems. Field trials were conducted across multiple agricultural zones in Egypt using mobile and drone-based imaging tools. Results indicate significant improvements in disease detection accuracy, reduction in chemical pesticide usage, and measurable yield gains. The findings demonstrate the practical value of AI-enabled diagnostic tools in advancing sustainable and technologydriven agriculture.
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