4.7 Article

Systematic approach for the development of fruit wines from industrially processed fruit concentrates, including optimization of fermentation parameters, chemical characterization and sensory evaluation

期刊

LWT-FOOD SCIENCE AND TECHNOLOGY
卷 62, 期 2, 页码 1043-1052

出版社

ELSEVIER
DOI: 10.1016/j.lwt.2015.02.020

关键词

Alcoholic fermentation; Mathematical modelling; Antioxidant activity; Chemical-sensory correlation

资金

  1. FruitVinegarDRINK QREN Project [23209]
  2. Project BioInd Biotechnology and Bioengineering for improved Industrial and Agro-Food processes [NORTE-07-0124-FEDER-000028]
  3. Programa Operacional Regional do Norte (ON.2 - O Novo Norte)
  4. QREN
  5. FEDER
  6. FCT Strategic Project [Pest-OE/EQB/LA0023/2013]

向作者/读者索取更多资源

This work presents an optimized approach alongside with the mathematical models describing the production of fruit wines, using fruit concentrates as an alternative to attain the desired ethanol yields and enhance organoleptic and functional properties. Box-Behnken design was used for modeling and optimization of ethanol yield and productivity in banana, orange, cherry and mango concentrates fermentations. Optimization allowed ethanol yields of 72.3 +/- 2.08 g.L-1 in orange, 101 +/- 1.78 g.L-1 in mango, 66.1 +/- 4.02 g.L-1 in cherry and 98.2 +/- 7.88 g.L-1 in banana with maximal productivities of 0.4 +/- 0.0 g.L(-1.)h(-1), 1.0 +/- 0.1 g.L(-1)h(-1), 1.7 +/- 0.2 g.L-1.h(-1) and 1.0 +/- 0.1 g.L-1.h(-1), respectively. Evaluation of total antioxidant activity by FRAP demonstrated fruit wines potential for the development of foods and formulations with functional properties, attaining 22.6 +/- 0.46 mmol.L-1 for orange, 7.14 +/- 0.77 mmol.L-1 for mango, 28.0 +/- 1.84 mmol.L-1 for cherry and 9.54 +/- 0.89 mmol.L-1 for banana wines. Characterization of aroma active compounds was performed by GC-MS and sensory evaluation by trained panelists. All fruit wines had good acceptance with cherry wine presenting the highest overall preference, followed by orange, mango and banana wines. Correlation between chemical and sensory properties was established with PLSR2 between analytical and sensory data, which allowed an insight of chemical composition impact in consumer perceived quality. (C) 2015 Elsevier Ltd. All rights reserved.

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