Quality evaluation of fruits and vegetables is a vital factor in maintaining qualities of food and ensures consumer satisfaction. Freshness is an essential asset of fruit and vegetable quality that impacts the physical health and motivation of consumers. This paper presents a transformative approach to revolutionizing quality evaluation in fruits and vegetables by applying image processing and machine learning algorithms, specifically utilizing the GrabCut algorithm for background subtraction, The traditional subjective methods of assessing product quality are replaced with objective and data-driven techniques. Through case studies, the efficacy of this approach is demonstrated, showcasing its potential to enhance quality assessment precision and efficiency. This innovative fusion of image processing and machine learning presented a promising avenue to redefine industry standards, ensuring higher consumer satisfaction and reduced wastage through consistent and reliable quality evaluation.