Hyperspectral Imaging for Fresh-Cut Fruit and Vegetable Quality Assessment: Basic Concepts and Applications

During the last two decades, hyperspectral imaging (HSI) has been one of the most studied and applied techniques in the field of nondestructive monitoring systems for the fruit and vegetable supply chain. This review provides HSI technical aspects (i.e., device features) and data analysis approaches (i.e., data processing and qualitative/quantitative modeling) for fresh-cut products, focusing on the different applications which the literature offers and the possible scale-up for process monitoring. Moreover, new frontiers in the development of possible process analytical technologies of cost-effective and hand-held HSI devices are presented and discussed. Even though the performance of these new proximal sensing tools needs to be carefully evaluated, new applicative research perspectives in the development of a proximal sensing approach based on HSI sensor networks are ready to be studied and developed for finding field applications (i.e., precision agriculture, food processing, and more) and enabling faster and more convenient analysis while maintaining the accuracy and capabilities of traditional HSI systems.

Automated summary

Hyperspectral imaging (HSI) has been extensively studied and applied in nondestructive monitoring systems for fruit and vegetable supply chains. This review focuses on the technical aspects and data analysis approaches of HSI in fresh-cut products, exploring different applications and potential scale-up for process monitoring. Additionally, it discusses the development of cost-effective and hand-held HSI devices for process analytical technologies and the potential of proximal sensing approach based on HSI sensor networks in various fields.