{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T13:33:50Z","timestamp":1771076030300,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["PD\/BD\/128272\/2017"],"award-info":[{"award-number":["PD\/BD\/128272\/2017"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>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&amp;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&amp;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\u2212Golay first derivative and ridge regression can be a good choice for the prediction of the three enological parameters.<\/jats:p>","DOI":"10.3390\/app112110319","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T17:59:38Z","timestamp":1635962378000},"page":"10319","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"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"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1281-4760","authenticated-orcid":false,"given":"V\u00e9ronique","family":"Gomes","sequence":"first","affiliation":[{"name":"CITAB\u2014Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Inov4Agro\u2014Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"}]},{"given":"Ricardo","family":"Rendall","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, University Coimbra, CIEPQPF, Rua S\u00edlvio Lima, P\u00f3lo II\u2014Pinhal de Marrocos, 3030-790 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4997-8865","authenticated-orcid":false,"given":"Marco Seabra","family":"Reis","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, University Coimbra, CIEPQPF, Rua S\u00edlvio Lima, P\u00f3lo II\u2014Pinhal de Marrocos, 3030-790 Coimbra, Portugal"}]},{"given":"Ana","family":"Mendes-Ferreira","sequence":"additional","affiliation":[{"name":"CITAB\u2014Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Inov4Agro\u2014Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"WM&B\u2014Laboratory of Wine Microbiology & Biotechnology, Department of Biology and Environment, Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"BioISI\u2014Biosystems & Integrative Sciences Institute, Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8257-0143","authenticated-orcid":false,"given":"Pedro","family":"Melo-Pinto","sequence":"additional","affiliation":[{"name":"CITAB\u2014Centre for the Research and Technology of Agro-Environmental and Biological Sciences, Inov4Agro\u2014Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"Departamento de Engenharias, Escola de Ci\u00eancias e Tecnologia, Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.trac.2013.09.007","article-title":"Recent advances in emerging imaging techniques for non-destructive detection of food quality and safety","volume":"52","author":"Chen","year":"2013","journal-title":"TrAC\u2014Trends Anal. 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