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Partial least squares calibrations and batch statistical process control to monitor phenolic extraction in red wine fermentations under different maceration conditions
Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch, South Africa.
Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch, South Africa.
RISE Research Institutes of Sweden, Agrifood and Bioscience, Gothenburg, Sweden.ORCID iD: 0000-0003-2606-9455
Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch, South Africa.
2020 (English)In: Food Control, ISSN 0956-7135, E-ISSN 1873-7129, Vol. 115, article id 107303Article in journal (Refereed) Published
Abstract [en]

The extraction of phenolic compounds during maceration is of utmost importance in red winemaking. However, the monitoring of phenolic extraction is often hampered by analytical and statistical constraints. The aim of this study was to monitor phenolic extraction kinetics with the use of PLS phenolic calibrations and batch statistical process control. Eight batches of Cabernet Sauvignon and Shiraz grapes during alcoholic fermentation under different maceration conditions (pressing at 1/3rd, 2/3rd and end of fermentation) and punch down regimes (low vs. high frequency) were evaluated in the study. Cabernet Sauvignon appeared to be a more suitable cultivar for longer maceration conditions with increased tannin extraction observed. Similar trends were observed for punch down for both cultivars. The use of PLS calibrations and batch level modelling provided an enhanced interpretation and understanding of phenolic extraction during red wine fermentations.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 115, article id 107303
Keywords [en]
PLS regression, Batch statistical process control (BSPC), Batch level modelling (BLM), Red wine phenolics maceration, Cap management practices
National Category
Food Science
Research subject
Culinary Arts and Meal Science
Identifiers
URN: urn:nbn:se:oru:diva-93884DOI: 10.1016/j.foodcont.2020.107303ISI: 000531083600028Scopus ID: 2-s2.0-85083362607OAI: oai:DiVA.org:oru-93884DiVA, id: diva2:1587400
Available from: 2021-08-24 Created: 2021-08-24 Last updated: 2021-08-24Bibliographically approved

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Mihnea, Mihaela

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CiteExportLink to record
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  • apa
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