Abstract
Blueberry is a fruit consumed fresh and as an ingredient in formulations such as jam, juice, and wine. Wine is a widely consumed beverage and produced from different berries and fruits. Blueberry wine contains bio-compounds that could have a beneficial effect on health. Therefore, this study aimed to optimize blueberry wine by two response variables (total soluble solids and fermentation time) to obtain the highest alcohol percentage, pH, and lightness. In order to optimize the fermentation process, a central composite design was used. The optimized blueberry wine was obtained at total soluble solids of 25°Brix and fermentation time of 16 d. The optimized blueberry characteristics estimated were: alcohol percentage of 11.91%, pH of 2.98, and lightness (L*) of 26.22, and the optimized blueberry characteristics experimental were: alcohol percentage of 11.93±0.02%, pH of 2.97±0.01, and L* of 25.42±1.80. The optimized blueberry wine had a total phenolic content of 360.27±18.09 mg of gallic acid equivalents L-1, total anthocyanin content of 46.27±3.66 mg cyanidin-3 glucoside L-1, antioxidant capacity by ABTS and DDPH assays of 1,539.8±92.18 and 1,688.07±57.57 mM Trolox equivalent L-1, respectively. The results suggest that optimized blueberry wine can be considered a drink with potential health applications.
Highlights
Wine is an ancestral product that has been transformed and studied over time; this drink has a significant social and economic impact due to its wide distribution and consumption throughout the world (Albergamo et al, 2020; Tsegay, Sathyanarayana, & Lemma, 2018)
It has been reported that a good predictive model should have an adjusted R2 ≥ 0.80, a significance level of p < 0.05, coefficients of variance (CV) values ≤ 10%, and lack of fit test > 0.1; all these parameters could be used to decide the satisfaction of the modeling (Milán-Carrillo et al, 2012)
Our results showed that alcohol percentages were significantly dependent on linear terms of total soluble solids [TSS, p < 0.01] and fermentation time [t, p < 0.01)], and on quadratic terms of TSS and t [(TSS)2, p < 0.01, (t)2, p < 0.017]
Summary
Wine is an ancestral product that has been transformed and studied over time; this drink has a significant social and economic impact due to its wide distribution and consumption throughout the world (Albergamo et al, 2020; Tsegay, Sathyanarayana, & Lemma, 2018). Its bittersweet taste and dark-blue color are appealing to the consumer; being consumed fresh and in jams, juices, and wine (Michalska & Łysiak, 2015; Zhang, Li, & Gao, 2016). These berries are a good source of phenolic compounds like anthocyanins, flavonols and chlorogenic acid, which are linked to beneficial health effects on noncommunicable diseases as neurodegenerative diseases, cardiovascular disorders, and cancer (Cutler, Gholami, Chua, Kuberan, & Babu, 2018; Routray & Orsat, 2011; Seeram et al, 2006; Zhang et al, 2016)
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