Optimization of Musalais wine formula based on response surface methodology

In this study, using Musalais wine as base wine, and medicinal and edible homology plants such as black wolfberry, Cistanche deserticola, jujube and sea buckthorn as auxiliary materials, the Musalais wine with new formula was prepared by soaking the base wine with auxiliary materials. Using total flavonoids content and sensory score as response values, the formula of Musalais wine was optimized by single factor combined with response surface tests. The basic physicochemical indexes were analyzed, and the effects of different auxiliary materials on the physicochemical indexes and sensory evaluation of Musalese wine were investigated. The results showed that the optimal formula of Musalais wine was black wolfberry 8.8 g/L, C. deserticola 8.3 g/L, jujube 10.4 g/L, sea buckthorn 4.2 g/L. The total flavonoids content in the Musalais wine with new formula reached 0.61 g/L under these optimal conditions, with a sensory score of 91, and the contents of total phenols, total flavonoids, fructose and glucose were increased by 0.45 g/L, 0.29 g/L, 5.15 g/L, 7.13 g/L, respectively. All 4 auxiliary materials could increase the malic acid, fructose and glucose contents of the wine, and the addition of jujube and C. deserticola significantly increased the lactic acid content of the wine, while the addition of sea buckthorn significantly increased the total flavonoids content of the wine. The addition of auxiliary materials enhanced the organoleptic complexity of Musalais wine, and the finished wine had a good overall performance in terms of comprehensive, appearance, aroma, taste and balance.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
DOI
https://doi.org/10.11882/j.issn.0254-5071.2025.04.025
Primary Topic
Fermentation and Sensory Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of Musalais wine formula based on response surface methodology

SHILAP Revista de lepidopterología
Fermentation and Sensory Analysis
article

Optimization of Musalais wine formula based on response surface methodology

article en

Abstract

In this study, using Musalais wine as base wine, and medicinal and edible homology plants such as black wolfberry, Cistanche deserticola, jujube and sea buckthorn as auxiliary materials, the Musalais wine with new formula was prepared by soaking the base wine with auxiliary materials. Using total flavonoids content and sensory score as response values, the formula of Musalais wine was optimized by single factor combined with response surface tests. The basic physicochemical indexes were analyzed, and the effects of different auxiliary materials on the physicochemical indexes and sensory evaluation of Musalese wine were investigated. The results showed that the optimal formula of Musalais wine was black wolfberry 8.8 g/L, C. deserticola 8.3 g/L, jujube 10.4 g/L, sea buckthorn 4.2 g/L. The total flavonoids content in the Musalais wine with new formula reached 0.61 g/L under these optimal conditions, with a sensory score of 91, and the contents of total phenols, total flavonoids, fructose and glucose were increased by 0.45 g/L, 0.29 g/L, 5.15 g/L, 7.13 g/L, respectively. All 4 auxiliary materials could increase the malic acid, fructose and glucose contents of the wine, and the addition of jujube and C. deserticola significantly increased the lactic acid content of the wine, while the addition of sea buckthorn significantly increased the total flavonoids content of the wine. The addition of auxiliary materials enhanced the organoleptic complexity of Musalais wine, and the finished wine had a good overall performance in terms of comprehensive, appearance, aroma, taste and balance.

SHILAP Revista de lepidopterología
Xinjiang Agricultural University (CN)
Life below water
Openalex Percentile: Top 51%
Fermentation and Sensory Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimization of Musalais wine formula based on response surface methodology · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS