Portable NIR Spectroscopy Combined with Machine Learning for Kiwi Ripeness Classification: An Approach to Precision Farming

This study aims to evaluate and classify the ripening stages of yellow-fleshed kiwifruit by integrating spectral and physicochemical data collected from the pre-harvest phase through 60 days of storage. A portable near-infrared (NIR) spectrometer (900–1700 nm) was used to develop predictive models f...

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Auteurs principaux:	Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand, Francesco Genovese, Attilio Matera, Alba Nicoletta Mininni, Maria Calabritto, Giovanni Carlo Di Renzo
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-06-01
Collection:	Applied Sciences
Sujets:	portable near-infrared spectroscopy harvest quality prediction fruit ripening classification machine learning model
Accès en ligne:	https://www.mdpi.com/2076-3417/15/11/6233
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