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投稿时间：2015-05-08
投稿时间：2015-05-08
中文摘要: 测定各类燕窝和掺假样品的氨基酸组成，通过主成分分析构建白燕窝鉴别的综合评价模型，运用多变量统计分析方法，初步建立燕窝掺假模型，并进行验证。结果表明，前两个主成分提取了原来18个指标87.75%的信息；利用综合评价模型计算出各类样品的主成分得分，燕窝样品在主成分得分图中分布的位置较集中，掺假燕窝样品则较分散；以掺假物质含量作为自变量，综合评价得分作为因变量，进行线性回归分析，单一物质掺假的线性模型和混合掺假线性模型的线性系数R2＞0.98。模型验证误差平均值为3.25%，说明氨基酸指纹图谱指纹谱图鉴别法是一种有效且可靠性高的鉴别白燕窝的方法。
Abstract:The amino acid composition of edible bird's nest（EBN）and adulterate EBN were analyzed by using an automatic amino.Principal component analysis（PCA）was applied to establish an evaluative model.Multivariate statistical methods were used to establish an adulteration model of EBN and verify.The results showed that prin 1 and prin 2 reflect 87.75%information of 18 indexes.Every sample was evaluated by PCA mathematical evaluative model and the PCA scores of EBNs were relative concentration than adulterate EBN.The parameters of adulteration content were analyzed as independent variables，and evaluative scores as the dependent variable for linear regression analysis.The final model were R2＞0.98.The determined values and the predicted values of the tested samples were fitted well with an average error of 3.25%.Therefore，the amino acids composition fingerprint could be used to distinguish adulterate bird's nest based on changes in content or proportion.
keywords: edible bird's nest adulteration multiple linear regression principal components analysis （PCA） modeling
文章编号：201611031 中图分类号： 文献标志码：
基金项目:广东省科技计划项目（2012B040302015）
| 作者 | 单位 |
| 庄俊钰1，2，许佩勤1，2，林丹2，3，钟舒洁1，2 | 广东省食品质量监督检验站，广东广州510308；2.广东省食品工业研究所，广东广州510308；3.广东省食品工业公共实验室，广东广州510308 |
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