From farm to market: Research progress and application prospects of artificial intelligence in the frozen fruits and vegetables supply chain

Abstract

Background

Frozen fruits and vegetables (F&V) are a vital food category but face multiple challenges in supply chain management. Traditional methods of quality control, from farm to market, are often inefficient, costly, and slow, with challenges in timely detection and traceability. As artificial intelligence (AI) technology advances, it offers innovative solutions to these issues. This review explores the application of AI in enhancing the frozen F&V supply chain.

Scope and approach

This paper reviews AI technologies such as machine learning, deep learning, and neural networks across the entire frozen F&V supply chain. It examines AI's roles in planting, harvesting, quality management, freezing, thawing, cold chain transportation, and sales forecasting. The review also discusses potential AI integrations with blockchain, IoT, and digital twin technologies, addressing future challenges and presenting new insights for AI in food supply chains.

Key findings and conclusions

AI uses data from machine vision, image processing, and sensors to monitor and predict key quality indicators in F&V. By integrating AI with blockchain and IoT, limitations such as security and centralization can be mitigated, enhancing data analysis and modeling. AI's application supports sustainability, optimizes resource allocation, bridges the information gap in sales, and helps producers and operators. This review highlights AI's broader potential in food supply chains and its transformative impact on industry practices.