白酒中微量组分较多,在核磁共振(nuclear magnetic resonance,NMR)氢谱中,各微量组分之间信号重叠严重,采用特定特征组分进行分析无法实现白酒中有机酸和醛类的准确定量;为解决核磁共振波谱中白酒微量组分信号重叠无法定量的难点,该研究以1H NMR技术作为检测手段,结合偏最小二乘回归(partial least squares regression,PLSR)算法,建立白酒中6种有机酸(乙酸、丙酸、丁酸、戊酸、己酸和异戊酸)和3种醛类(乙醛、乙缩醛和异戊醛)的PLSR定量分析模型。该模型的R2为0.93～0.99,预测标准偏差< 0.7,范围误差比≥ 3.7,表明模型拟合效果好、预测精度较高。其NMR PLSR模型预测结果与气相色谱法结果误差在±8%以内,满足方法可行性对比分析验证要求。研究结果表明,NMR PLSR定量模型可用于白酒中以上6种有机酸和3种醛类的准确测定,为建立非目标1H NMR指纹图谱技术在白酒真实性鉴别中的应用奠定基础,也为应对其他食品中微量组分(酯类、糖类、氨基酸等)存在信号重叠难以定量检测的情况提供解决办法。
吉鑫
,
樊双喜
,
李宜聪
,
钟其顶
,
陆玮
,
李安军
,
刘国英
,
黄艳
,
胡心行
,
叶方平
. 白酒中有机酸和醛类的偏最小二乘回归法定量分析模型[J]. 食品与发酵工业, 2020
, 46(14)
: 204
-210
.
DOI: 10.13995/j.cnki.11-1802/ts.023839
There are many minor components in Baijiu. Due to the severely overlapping signal peaks in 1H NMR spectrum, the specific characteristic components analysis method cannot achieve accurate quantification of organic acids and aldehydes in Baijiu. In order to solve the problem of overlapping signal peaks of Baijiu in 1H NMR spectrum, a partial least squares regression (PLSR) model for quantitative analysis of 6 organic acids (acetic acid, propionic acid, butyric acid, valeric acid, hexanoic acid, and isovaleric acid) and 3 aldehydes (acetaldehyde, acetal, and isovaleraldehyde) in Baijiu was established using 1H NMR technology as the detection method, combining with PLSR prediction algorithm. The coefficient of determination of the PLSR model for quantitative analysis ranged from 0.93 to 0.99, the standard deviation of prediction (RMSEP) < 0.7, and the range error ratio (RPD)≥3.7. It showed that the model had good fitting effect and high prediction accuracy. Compared the results of NMR PLSR model with those of gas chromatography, the error was within ± 8%, which met the verification requirements of method feasibility comparison analysis. The results showed that the NMR PLSR model for quantitative prediction could be used for the accurate determination of 6 organic acids and 3 aldehydes in Baijiu, which laid the foundation for the application of non-targeted 1H NMR fingerprint technology in the authenticity identification of Baijiu, and provided solutions to the problem that it is difficult to quantify the signal overlap of minor components (esters, carbohydrates, amino acid, etc.) in other foods.
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