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

This paper presents an extended comparison study between 16 different linear and non-linear 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 ofte...

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Autores principales:	Véronique Gomes, Ricardo Rendall, Marco Seabra Reis, Ana Mendes-Ferreira, Pedro Melo-Pinto
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	wine grape berries hyperspectral imaging linear and non-linear regression methods penalized regression variables importance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/f270a53ee95945fca13e56d34b961c5b
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spelling	oai:doaj.org-article:f270a53ee95945fca13e56d34b961c5b2021-11-11T15:20:37ZDetermination of Sugar, pH, and Anthocyanin Contents in Port Wine Grape Berries through Hyperspectral Imaging: An Extensive Comparison of Linear and Non-Linear Predictive Methods10.3390/app1121103192076-3417https://doaj.org/article/f270a53ee95945fca13e56d34b961c5b2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10319https://doaj.org/toc/2076-3417This paper presents an extended comparison study between 16 different linear and non-linear 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.Véronique GomesRicardo RendallMarco Seabra ReisAna Mendes-FerreiraPedro Melo-PintoMDPI AGarticlewine grape berrieshyperspectral imaginglinear and non-linear regression methodspenalized regressionvariables importanceTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10319, p 10319 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	wine grape berries hyperspectral imaging linear and non-linear regression methods penalized regression variables importance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	wine grape berries hyperspectral imaging linear and non-linear regression methods penalized regression variables importance Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Véronique Gomes Ricardo Rendall Marco Seabra Reis Ana Mendes-Ferreira Pedro Melo-Pinto 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
description	This paper presents an extended comparison study between 16 different linear and non-linear 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.
format	article
author	Véronique Gomes Ricardo Rendall Marco Seabra Reis Ana Mendes-Ferreira Pedro Melo-Pinto
author_facet	Véronique Gomes Ricardo Rendall Marco Seabra Reis Ana Mendes-Ferreira Pedro Melo-Pinto
author_sort	Véronique Gomes
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
title_short	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
title_full	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
title_fullStr	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
title_full_unstemmed	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
title_sort	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
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f270a53ee95945fca13e56d34b961c5b
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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

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