摘要
运用GC-Flash型电子鼻技术替代人工感官品评,针对同山烧进行酒龄定量研究。结合主成分分析、判别因子分析法和偏最小二乘法建立同山烧酒龄判别模型。结果表明,偏最小二乘法模型(PLS)对所选传统工艺酿制同山烧酒龄预测结果线性好,准确度高。但对不同发酵工艺及产源(原料)的同山烧需要单独建立酒龄判别模型。
In the study, quantitative study of the age of Tongshan durra wine was carried out by use of GC-flash electronic nose technique instead of artificial sensory evaluation, and then all the data were analyzed by multivariate data processing based on principal component analysis （PCA）, discriminant factor analysis （DFA） and partial least squares （PLS） to establish the discrimination model of Tongshan durra wine age. The results suggested that such model was feasible with high accuracy in practice. However, different discrimination model should be established for other Tongshan durra wine made by different fermenting technology or by different raw materials.
出处
《酿酒科技》
北大核心
2014年第3期50-52,共3页
Liquor-Making Science & Technology
基金
绍兴市质量技术监督局科研计划项目(201203)
关键词
白酒
电子鼻
同山烧
酒龄
模型
Baijiu（liquor）
electronic nose
Tongshan durra wine
age
discrimination model
