基于多元统计方法进行水牛乳掺水定量鉴别

采用常规方法测定不同掺水体积比例的水牛乳掺伪样的7 个主要品质指标，并基于这些指标参数采用单因素方差分析、主成分分析和多元逐步线性回归法，对不同掺水量的水牛乳进行定量鉴别，旨在寻求一种能有效监控水牛乳掺水的快速定量鉴别方法。利用单因素方差分析不同掺伪样的7 个重要理化指标的差异性，分析结果表明，水牛乳掺水的最低检出限为7%。主成分分析中，第1主成分贡献率达到85.464%，已包含样本的大部分信息，主成分1得分与掺水量存在显著的线性关系。通过多元逐步线性回归法建立了4 个定量模型方程，其相关系数R2分别为0.965、0.982、0.986、0.989，平均绝对误差分别为－0.23%、－2.40%、0.23%、1.28%，可实现水牛乳掺水的定量鉴别。

Quantitative Identification of Added Water in Buffalo Milk Based on Multi Statistical Analysis

Seven main quality indicators of buffalo milk added with different volume ratios of water were measured by
conventional methods based on one-way analysis of variance analysis (ANOVA), principle component analysis (PCA),
and multiple linear regression for quantitative identification of added water in buffalo milk. One-way ANOVA was used to
determine the significant differences in the main quality indicators of different samples with added water to obtain a limit of
detection (LOD) of 7%. According to the PCA, the contribution rate of the first PC was 85.464%, and it included most of the
sample information. There was a significant linear relationship between the scores of the first PC and the content of added
water. Four quantitative model equations were built by multiple linear regression, with correlation coefficients (R2) of 0.965,
0.982, 0.986 and 0.989 and mean absolute errors of −0.23%, −2.40%, 0.23% and 1.28%, respectively, which could be used
for quantitative identification of added water in buffalo milk.