Grape composition assessment using NIR/SWIR hyperspectral imagery acquired from a UTV
Author:
Publisher
International Society for Horticultural Science (ISHS)
Link
https://www.actahort.org/members/showpdf?booknrarnr=1395_46
Reference12 articles.
1. Machine learning for classifying and predicting grape maturity indices using absorbance and fluorescence spectra.;Armstrong;Food Chem,2023
2. On-the-go sensing of grape berry anthocyanins during commercial harvest: development and prospects.;Bramley;Aust. J. Grape Wine Res.,2011
3. Assessing spatial variability of grape skin flavonoids at the vineyard scale based on plant water status mapping.;Brillante;J Agric Food Chem,2017
4. Carbon isotope discrimination (δ13 C) of grape musts is a reliable tool for zoning and the physiological ground-truthing of sensor maps in precision viticulture.;Brillante;Front. Environ. Sci.,2020
5. Determination of anthocyanin concentration in whole grape skins using hyperspectral imaging and adaptive boosting neural networks.;Fernandes;J. Food Eng.,2011
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