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Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

机译:主成分分析(PCA)作为发酵食品的感官评估工具的应用。

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The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R2 = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability. copyright Association of Food Scientists & Technologists (India) 2011.
机译:该工作的目的是使用定量描述分析(QDA)方法来描述掺入乳酸培养物制成的发酵食品的感官特性。选择并培训小组成员以评估各种属性,特别是诸如牛乳凝乳和豆浆凝乳,idli,酸菜和益生菌冰淇淋等发酵食品的颜色和外观,身体质地,风味,总体可接受性和酸度。主成分分析(PCA)确定了六个重要的主成分,这些成分占感官属性数据方差的90%以上。使用多个最小二乘回归( R 2 = 0.8),将总产品质量建模为主要成分的函数。通过方差分析(ANOVA)对PCA的结果进行统计分析。这些发现证明了定量描述分析在识别和测量对消费者可接受性很重要的发酵食品属性方面的实用性。印度食品科学家和技术人员协会版权所有2011。

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