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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Principais autores:	Giuseppe Altieri, Sabina Laveglia, Mahdi Rashvand, Francesco Genovese, Attilio Matera, Alba Nicoletta Mininni, Maria Calabritto, Giovanni Carlo Di Renzo
格式:	Artigo
語言:	Inglês
出版:	MDPI AG 2025-06-01
叢編:	Applied Sciences
主題:	portable near-infrared spectroscopy harvest quality prediction fruit ripening classification machine learning model
在線閱讀:	https://www.mdpi.com/2076-3417/15/11/6233
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