| Literature DB >> 26998173 |
Liu Zhong-Hua1, Guo Jie1.
Abstract
Purple potatoes were used as raw material to study the purple potato wine production process and antioxidant activity. This paper analyzed different fermentation time, fermentation temperature, yeast inoculum, initial pH, the initial sugar content on alcohol and anthocyanin contents of purple potato wine by single factor experiments and response surface methodology(RSM). The results showed that the optimum fermentation conditions of purple potato wine were as follows: fermentation temperature was 26(o)C, yeast inoculum was 0.15%, fermentation time was 7 d, initial pH was 3.0 and initial sugar content was 11 %. Under these conditions the alcohol and anthocyanin contents of purple potato wine could reach 10.55%/Vol and 6.42 μg/mL, respectively. The purple potato wine was purple, bright in colour, pleasant fragrance and pure taste. Prepared purple potato wine had the ability of reducing Fe(3+) and scavenging superoxide anion radicals, which meant that purple potato wine had certain antioxidant activity.Entities:
Keywords: Antioxidant activity; purple potato wine; response surface methodology.
Year: 2015 PMID: 26998173 PMCID: PMC4774381 DOI: 10.2174/1874120701509010282
Source DB: PubMed Journal: Open Biomed Eng J ISSN: 1874-1207
Factors and levels of RSM.
| Levels | Factors | ||
|---|---|---|---|
| A Initial pH | B Yeast Inoculum / % | C Fermentation Temperature/ oC | |
| -1 | 2.5 | 0.1 | 22 |
| 0 | 3.0 | 0.15 | 26 |
| +1 | 3.5 | 0.2 | 30 |
Scheme and Results of RSM.
| Experiment Number | A | B | C | Alcohol Content(%/Vol) |
|---|---|---|---|---|
| 1 | 0.00 | 0.00 | 0.00 | 9.942 |
| 2 | 0.00 | 0.00 | 0.00 | 10.091 |
| 3 | 1.00 | 0.00 | -1.00 | 5.545 |
| 4 | 0.00 | 1.00 | -1.00 | 6.786 |
| 5 | 0.00 | 0.00 | 0.00 | 9.884 |
| 6 | 0.00 | 0.00 | 0.00 | 9.765 |
| 7 | 0.00 | 0.00 | 0.00 | 10.346 |
| 8 | 1.00 | 0.00 | 1.00 | 3.542 |
| 9 | 1.00 | 1.00 | 0.00 | 8.600 |
| 10 | 1.00 | -1.00 | 0.00 | 6.653 |
| 11 | -1.00 | -1.00 | 0.00 | 7.894 |
| 12 | -1.00 | 1.00 | 0.00 | 5.433 |
| 13 | 0.00 | -1.00 | -1.00 | 6.785 |
| 14 | -1.00 | 0.00 | 1.00 | 6.854 |
| 15 | 0.00 | -1.00 | 1.00 | 4.865 |
| 16 | 0.00 | 1.00 | 1.00 | 4.875 |
| 17 | -1.00 | 0.00 | -1.00 | 4.879 |
ANOVA for the regression response surfuce model.
| Source | df | Sum of Squares | Mean Square | F value | P value | Significance |
|---|---|---|---|---|---|---|
| Model | 9 | 73.59 | 8.18 | 6.69 | 0.0016 | ** |
| A | 1 | 0.065 | 0.065 | 1.11 | 0.7640 | |
| B | 1 | 0.032 | 0.032 | 0.34 | 0.8336 | |
| C | 1 | 1.86 | 1.86 | 1.48 | 0.1382 | |
| A2 | 1 | 12.77 | 12.77 | 19.21 | 0.0032 | ** |
| B2 | 1 | 5.27 | 5.27 | 7.93 | 0.0259 | * |
| C2 | 1 | 39.40 | 39.40 | 59.24 | 0.0001 | ** |
| AB | 1 | 4.86 | 4.86 | 7.30 | 0.0305 | * |
| AC | 1 | 3.96 | 3.96 | 5.95 | 0.0448 | * |
| BC | 1 | 0.00002 | 0.00002 | 0.00003 | 0.9958 | |
| Residual | 7 | 4.66 | 0.67 | |||
| Lack of Fit | 3 | 4.46 | 1.49 | 29.72 | 0.0034 | * |
| Pure Error | 4 | 0.20 | 0.050 | |||
| Cor Total | 16 | 78.24 |
“**” (P 0.01) was highly significant; “*” (P 0.05) was significant.