主成分分析法在挂面质构品质评价中的应用

以80种来自全国不同地区的小麦粉为试验材料,采用主成分分析法对制作的挂面的10个质构指标进行分析,对挂面品质指标进行综合评定。经主成分分析,提取了5个主成分,F1、F2、F3、F4、F5,数学评价模型有效地保留了测定指标的大部分信息(89.508%)。利用感官评分对主成分因子得分的综合评价方法进行验证,各个主成分与主成分因子总得分F分别与感官总得分呈极显著相关,这5个主成分可以作为挂面质构综合评价的指标,用来综合评价挂面品质。

Application of principal component analysis in texture quality evaluation of dried noodles

Eighty wheat flour samples from different regions of China were processed to dried noodles, and 10 texture parameters were studied by principal component analysis method for comprehensive evaluation of noodle quality. Five principal components, F1, F2, F3, F4 and F5 were selected to construct an evaluation model, which effectively retained most information (89.508%) about the indexes. The comprehensive evaluation method of the score of principal component factor was validated by sensory score. Each principal component and the total score of principal component factor F were very significantly correlated to the total sensory score of noodles, respectively. The five principal components can be used to comprehensively evaluate the texture quality of dried noodles.