Using Machine Learning to Identify Diseases and Perform Sorting in Apple Fruit

Fruit diseases play a major role in global agriculture, leading to substantial crop losses and influencing food production and economic stability. By leveraging advanced machine learning techniques, the approach developed in this experimental work contributes to modernizing fruits and vegetables sorting operations in food processing, crop management practices thus promoting agricultural sustainability.

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• 1 In this age of Industry 4.0 the fruit sorting is an important part in the food processing wherein this work plays a vital role.
• 2 In this study, a solution for the detection and classification of apple fruit diseases is proposed and experimentally validated.
• 3 Deep learning models offer promise for automating disease identification using fruit images, but encounter obstacles such as therequirement for extensive training data, computational complexity, and the risk of overfitting.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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