Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/24/9130 |
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| author | Tamara Santana Jorge Moreno Guillermo Petzold Roberto Santana Guido Sáez-Trautmann |
| author_facet | Tamara Santana Jorge Moreno Guillermo Petzold Roberto Santana Guido Sáez-Trautmann |
| author_sort | Tamara Santana |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T13:53:45Z |
| format | Article |
| id | doaj.art-d70d18743cdb4cdba1cdce10fffe1556 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T13:53:45Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d70d18743cdb4cdba1cdce10fffe15562023-11-21T01:51:09ZengMDPI AGApplied Sciences2076-34172020-12-011024913010.3390/app10249130Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze ConcentrationTamara Santana0Jorge Moreno1Guillermo Petzold2Roberto Santana3Guido Sáez-Trautmann4Food Engineering Department, Universidad del Bío-Bío, Casilla 447, Chillán 3349001, ChileFood Engineering Department, Universidad del Bío-Bío, Casilla 447, Chillán 3349001, ChileFood Engineering Department, Universidad del Bío-Bío, Casilla 447, Chillán 3349001, ChileDepartment of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 Donostia-San Sebastian, SpainFood Engineering Department, Universidad del Bío-Bío, Casilla 447, Chillán 3349001, ChileCentrifugation 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.https://www.mdpi.com/2076-3417/10/24/9130freeze concentrationcentrifugationtime–temperature factors |
| spellingShingle | Tamara Santana Jorge Moreno Guillermo Petzold Roberto Santana Guido Sáez-Trautmann Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration Applied Sciences freeze concentration centrifugation time–temperature factors |
| title | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration |
| title_full | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration |
| title_fullStr | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration |
| title_full_unstemmed | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration |
| title_short | Evaluation of the Temperature and Time in Centrifugation-Assisted Freeze Concentration |
| title_sort | evaluation of the temperature and time in centrifugation assisted freeze concentration |
| topic | freeze concentration centrifugation time–temperature factors |
| url | https://www.mdpi.com/2076-3417/10/24/9130 |
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