ANALYZING THE RESEARCH ON HOW THE ORGANIC FOOD SECTOR HAS INTEGRATED AI INTO ITS PRODUCT DEVELOPMENT PROCESSES

Abstract

This study investigates the application of computer vision and artificial intelligence (AI) technologies in assessing the quality of organic food, with a particular focus on their impacts on production, marketing, and sustainability. The review is structured around three main themes: the role of AI in the food sector, the use of computer vision for food quality evaluation, and the broader digital transformation driven by AI. Through a comprehensive literature review, this study explores how image processing techniques can enhance the accuracy, impartiality, and efficiency of organic food quality assessments. The findings show that AI and computer vision significantly improve the reliability of visual quality indicators, reducing human error and enhancing efficiency in quality control processes. Furthermore, these technologies offer potential benefits for customer service and cost reduction in operations. However, challenges such as high implementation costs and limited scalability, particularly for small-scale organic farms, continue to hinder widespread adoption. This study underscores the need for further research aimed at developing scalable and cost-effective AI solutions that are accessible to smaller producers. The integration of AI in the organic food supply chain holds significant promise for improving sustainability and resource efficiency, making it a critical area for future research.