Li Shuai, Li Tao, Han Yueran, Yan Pei, Li Guohui, Ren Tingting, Yan Ming, Lu Jun, Qiu Shuyi
College of Liquor and Food Engineering, Key Laboratory of Fermentation Engineering and Biological Pharmacy of Guizhou Province, Guizhou University, Guiyang, Guizhou 550025, China.
Key Laboratory of Fermentation Engineering and Biological Pharmacy of Guizhou Province, China.
Food Chem X. 2024 Oct 5;24:101877. doi: 10.1016/j.fochx.2024.101877. eCollection 2024 Dec 30.
The quality grade of base directly determines the final quality of sauce-flavor . However, traditional methods for assessing these grades often rely on subjective experience, lacking objectivity and accuracy. This study used GC-FID, combined with quantitative descriptive analysis (QDA) and odor activity value (OAV), to identify 27 key flavor compounds, including acetic acid, propionic acid, ethyl oleate, and isoamyl alcohol etc., as crucial contributors to quality grade differences. Sixteen bacterial biomarkers, including and etc., and 7 fungal biomarkers, including and etc., were identified as key microorganisms influencing these differences. Additionally, reducing sugar content in significantly impacted base quality. Finally, 11 machine learning classification models and 9 prediction models were evaluated, leading to the selection of the optimal model for accurate quality grade classification and prediction. This study provides a foundation for improving the evaluation system of sauce-flavor and ensuring consistent quality.
基酒的质量等级直接决定了酱香型白酒的最终品质。然而，传统的这些等级评估方法往往依赖主观经验，缺乏客观性和准确性。本研究采用气相色谱-氢火焰离子化检测器（GC-FID），结合定量描述分析（QDA）和气味活性值（OAV），鉴定出27种关键风味化合物，包括乙酸、丙酸、油酸乙酯和异戊醇等，它们是造成质量等级差异的关键因素。鉴定出16种细菌生物标志物，包括[具体细菌名称1]和[具体细菌名称2]等，以及7种真菌生物标志物，包括[具体真菌名称1]和[具体真菌名称2]等，它们是影响这些差异的关键微生物。此外，[基酒名称]中还原糖含量对基酒质量有显著影响。最后，评估了11种机器学习分类模型和9种预测模型，从而选出了用于准确质量等级分类和预测的最优模型。本研究为完善酱香型白酒评价体系和确保质量一致性提供了依据。
