Hyperspectral Imaging for Fresh-Cut Fruit and Vegetable Quality Assessment: Basic Concepts and Applications
Articolo
Data di Pubblicazione:
2023
Citazione:
Hyperspectral Imaging for Fresh-Cut Fruit and Vegetable Quality Assessment: Basic Concepts and Applications / S. Vignati, A. Tugnolo, V. Giovenzana, A. Pampuri, A. Casson, R. Guidetti, R. Beghi. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 13:17(2023 Aug), pp. 9740.1-9740.27. [10.3390/app13179740]
Abstract:
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.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
proximal sensing; image processing; sensors; machine learning; pre- and postharvest; agri-food sector
Elenco autori:
S. Vignati, A. Tugnolo, V. Giovenzana, A. Pampuri, A. Casson, R. Guidetti, R. Beghi
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