摘要
为快速、无损判别乳制品脂氧化程度,提出了利用乳制品三维荧光光谱的氧化水平进行判别的方法。该方法用平行因子分析对荧光矩阵进行分解,用载荷向量组确定脂氧化过程中的光敏成分,用不同成分得分向量对样本进行聚类,并建立了不同氧化水平样本的偏最小二乘判别模型。实验采集不同存储环境下氧化程度各异的酸奶样本,找出了核黄素等荧光团在脂氧化过程中的变化规律,选取得分向量建立偏最小二乘判别模型对不同存储阶段氧化程度各异的样本判别分类,其特异度和灵敏度达88.9%以上,验证了该法对评判乳制品脂氧化水平的有效性。
A discrimination method was developed for the rapid and non-destructive identification of fat oxidation in different dairy products by three-dimensional fluorescence spectroscopy.The fluorescence data matrix was decomposed by parallel factor analysis(PARAFAC) and the photosensitive oxidation elements were found from load vectors.After clustering of different samples using score vectors within components,the method of partial least squares discrimination model for different levels of oxidation was established.The yogurt samples with varying degrees of oxidation were collected from different storage environments,in which the lipid oxidation processes of riboflavin and other fluorophores were obtained.The partial least-squares discrimination model of the different storage stages and oxidation levels was established by score vectors.The model specificity and sensitivity of classification were higher than 88.9%,which validated the method in judging the lipid oxidation level of dairy product.
出处
《分析测试学报》
CAS
CSCD
北大核心
2012年第2期230-233,共4页
Journal of Instrumental Analysis
基金
国家自然科学基金项目(51075280)
浙江省重大科技专项和优先主题计划项目(2010C11060)
浙江省自然科学基金项目(Y4110235)
上海市研究生教育创新计划项目
关键词
三维荧光
乳制品
脂氧化
判别方法
平行因子分析
three-dimensional fluorescence
dairy product
fat oxidation
discrimination method
parallel factor analysis(PARAFAC)