Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration
dc.contributor.author | Santana, Tamara | |
dc.contributor.author | Moreno, Jorge | |
dc.contributor.author | Petzold, Guillermo | |
dc.contributor.author | Santana Hermida, Roberto ![]() | |
dc.contributor.author | Sáez Trautmann, Guido | |
dc.date.accessioned | 2021-01-12T12:00:12Z | |
dc.date.available | 2021-01-12T12:00:12Z | |
dc.date.issued | 2020-12-21 | |
dc.identifier.citation | Applied Sciences 10(24) : (2020) // Article ID 9130 | es_ES |
dc.identifier.issn | 2076-3417, | |
dc.identifier.uri | http://hdl.handle.net/10810/49686 | |
dc.description.abstract | Centrifugation is a technique applied to assist in the freeze concentration of fruit juices and solutions. The aim of this work was to study the influence of the time–temperature parameters on the centrifugation process as a technique applied to assist in the first cycle of the freeze concentration of blueberry juice. A completely randomized 4 × 3 factorial design was performed using temperature and time as the factors, and the response variables included the percentage of concentrate, efficiency and solutes recovered. The results were evaluated using multiple linear regression, random forest regression, and Gaussian processes. The solid content in the concentrate doubled compared to the initial sample (18 °Brix) and approached 60% in the first cycle of blueberry juice freeze concentration. The combination of factors affected the percentage of the concentrate and solutes recovered, and the optimum of concentration was obtained at 15 °C with a centrifugation time of 20 min. Gaussian processes are suggested as suitable machine learning techniques for modelling the quantitative effect of the relevant factors in the centrifugation process. | es_ES |
dc.description.sponsorship | Jorge Moreno and Ricardo Simpson are grateful for the financial support provided by FONDECYT 1160761. Roberto Santana acknowledges support by the Spanish Ministry of Science and Innovation (projects TIN2016-78365-R and PID2019-104966GB-I00), and the Basque Government (projects KK-2020/00049 and IT1244-19, and ELKARTEK program). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MCIU/TIN2016-78365-R | es_ES |
dc.relation | info:eu-repo/grantAgreement/MCIU/PID2019-104966GB-I00) | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | freeze concentration | es_ES |
dc.subject | centrifugation | es_ES |
dc.subject | time–temperature factors | es_ES |
dc.title | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2020-12-24T15:56:43Z | |
dc.rights.holder | 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2076-3417/10/24/9130/htm | es_ES |
dc.identifier.doi | 10.3390/app10249130 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala |
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Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).