Classification of microbial defects in milk using a dynamic headspace gas chromatograph and computer-aided data processing. 1. Principal component similarity analysis.

Horimoto Y; Lee K; Nakai S

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Classification of microbial defects in milk using a dynamic headspace gas chromatograph and computer-aided data processing. 1. Principal component similarity analysis.

机译：使用动态顶空气相色谱仪和计算机辅助数据处理对牛奶中的微生物缺陷进行分类。 1.主成分相似度分析。

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The objective of this study was to distinguish between abnormal milk (containing off-flavours) and normal milk (without off-flavours) using a low-cost headspace gas chromatograph and principal component similarity analysis. UHT milk was inoculated with Pseudomonas fragi, P. fluorescens, Bacillus subtilis, Enterobacter aerogenes, Lactococcus lactis, and a mixed culture (P. fragi:E. aerogenes:L. lactis 1:1:1) to approximately 4.0 log10 c.f.u./ml. The samples were stored at 4deg C for 10 days for P. fragi and P. fluorescens and at 30deg C for 24 h for the remaining bacteria. A new multivariate analysis technique, principal component similarity analysis, was capable of distinguishing milk samples inoculated with P. fragi, P. fluorescens, L. lactis, E. aerogenes, and a mixed culture from uninoculated samples.

机译：这项研究的目的是使用低成本的顶空气相色谱仪和主成分相似性分析来区分正常牛奶（含有异味）和普通牛奶（不含异味）。 UHT牛奶接种了脆弱的假单胞菌，荧光假单胞菌，枯草芽孢杆菌，产气肠杆菌，乳酸乳球菌和混合培养物（脆弱的假单胞菌：产气大肠杆菌：乳酸乳球菌1：1：1）至大约4.0 log10 cfu / ml 。对于脆弱小球菌和荧光假单胞菌，样品在4℃下保存10天，对于其余细菌，样品在30℃下保存24小时。一种新的多元分析技术，即主成分相似性分析，能够从未接种的样品中区分出接种了脆弱性假单胞菌，荧光假单胞菌，乳酸乳球菌，产气大肠杆菌和混合培养物的牛奶样品。

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《Journal of Agricultural and Food Chemistry》 |1997年第3期|共10页
作者
Horimoto Y; Lee K; Nakai S;
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正文语种 eng
中图分类农业化学;营养卫生、食品卫生;农业科学;
关键词
ultivariate analysis; classification; data processing; defects; milk; analytical methods; gas chromatography; UHT milk; milk flavour; microbial flora; differentiation;

机译：多元分析;分类;数据处理;缺陷;牛奶;分析方法;气相色谱法;超高温灭菌牛奶;牛奶风味;微生物菌群;分化;

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1. Classification of microbial defects in milk using a dynamic headspace gas chromatograph and computer-aided data processing. 1. Principal component similarity analysis. [J] . Horimoto Y, Lee K, Nakai S Journal of Agricultural and Food Chemistry . 1997,第3期

机译：使用动态顶空气相色谱仪和计算机辅助数据处理对牛奶中的微生物缺陷进行分类。 1.主成分相似度分析。
2. Gene expression data classification with Kernel principal component analysis. [J] . Liu Z, Chen D, Bensmail H Journal of biomedicine & biotechnology . 2005,第2期

机译：使用内核主成分分析对基因表达数据进行分类。
3. Gene expression data classification with Kernel principal component analysis. [J] . Liu Z, Chen D, Bensmail H Journal of biomedicine & biotechnology . 2005,第2期

机译：使用内核主成分分析对基因表达数据进行分类。
4. Digging Deeper into Mass Spectral Imaging Data through the Hierarchical Application of Principal Component Analysis. [C] . Yousef El Aalamat, Nico Verbeeck, Evelyne Lerut, American Society for Mass Spectrometry Conference on Mass Spectrometry and Allied Topics . 2012

机译：通过主成分分析的分层应用挖掘到质谱成像数据。
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6. Harmonic and anharmonic aspects in the dynamics of BPTI: a normal mode analysis and principal component analysis. [O] . S. Hayward, A. Kitao, N. Go 1994

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7. Determination of Hexanal in Rice Using an Automated Dynamic Headspace Sampler Coupled to a Gas Chromatograph–Mass Spectrometer [O] . Yiru Wang, Jaeho Ha 2012

机译：使用自动动态顶空采样器耦合到气相色谱谱仪 - 质谱仪测定水稻中肾水稻的测定

Classification of microbial defects in milk using a dynamic headspace gas chromatograph and computer-aided data processing. 1. Principal component similarity analysis.

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