Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/103714
Title: Determination of Sugar, pH, and Anthocyanin Contents in Port Wine Grape Berries through Hyperspectral Imaging: An Extensive Comparison of Linear and Non-Linear Predictive Methods
Authors: Gomes, Véronique
Rendall, Ricardo 
Reis, Marco 
Mendes-Ferreira, Ana
Melo-Pinto, Pedro
Keywords: wine grape berries; hyperspectral imaging; linear and non-linear regression methods; penalized regression; variables importance
Issue Date: 2021
Publisher: MDPI
Serial title, monograph or event: Applied Sciences (Switzerland)
Volume: 11
Issue: 21
Abstract: This paper presents an extended comparison study between 16 different linear and nonlinear regression methods to predict the sugar, pH, and anthocyanin contents of grapes through hyperspectral imaging (HIS). Despite the numerous studies on this subject that can be found in the literature, they often rely on the application of one or a very limited set of predictive methods. The literature on multivariate regression methods is quite extensive, so the analytical domain explored is too narrow to guarantee that the best solution has been found. Therefore, we developed an integrated linear and non-linear predictive analytics comparison framework (L&NL-PAC), fully integrated with five preprocessing techniques and five different classes of regression methods, for an effective and robust comparison of all alternatives through a robust Monte Carlo double cross-validation stratified data splitting scheme. L&NLPAC allowed for the identification of the most promising preprocessing approaches, best regression methods, and wavelengths most contributing to explaining the variability of each enological parameter for the target dataset, providing important insights for the development of precision viticulture technology, based on the HSI of grape. Overall, the results suggest that the combination of the Savitzky􀀀Golay first derivative and ridge regression can be a good choice for the prediction of the three enological parameters.
URI: https://hdl.handle.net/10316/103714
ISSN: 2076-3417
DOI: 10.3390/app112110319
Rights: openAccess
Appears in Collections:I&D CIEPQPF - Artigos em Revistas Internacionais

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