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Differentiation of soy sauce by pattern recognition analysis of mid- and near-IR spectra

机译:用近红外光谱模式识别分析酱油的分化

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摘要

For certificating the authenticity of soy sauce, mid- and near-IR spectra of 27 commercial soy sauce produced from whole soybeans and 30 from defatted soybeans were measured. Factor analysis applied to MIR and NIR spectra individually indicated the existence of some difference between two soy sauces. Then, SIC, conventional step-wise linear discriminant analysis (LDA) and LDA using genetic algorithms (GALDA) were applied to their spectra for classifying soy sauce samples according to types of soybeans. In step-wise LDA, 94.7% of samples were correctly assigned based on six wavenumbers in mid-IR spectra but 100% correct classification was obtained by six wavelengths in NIR spectra. Cooman's plots in SIMCA applied to mid- or near-IR spectra indicated that differentiating two types of soy sauce samples was difficult due to high similarity in their constituents. Perfectly correct classification was attained by five to eight mid-IR wavenumbers and four to five near-IR wavelengths selected by GALDA. In general, the differentiation using NIR spectra was more reliable than that using MIR spectra.
机译:为了证明酱油的真实性,测量了由整个大豆和30种来自脱脂大豆生产的27种商用酱油的中和近红外光谱。适用于MIR和NIR光谱的因子分析单独表明存在两种大豆酱汁之间的一些差异。然后,使用遗传算法(GALDA)的SiC,常规的逐步线性判别分析(LDA)和LDA根据大豆类型进行分类酱油样品的光谱。在逐步LDA中,基于中红外光谱中的六个波数正确分配94.7%的样品,但在NIR光谱中通过六个波长获得100%正确分类。 Cooman在SIMCA中施加到中间或接近IR光谱的地块表明,由于其成分中的高相似性,难以区分两种类型的酱油样品。五到八个中红外波兰人和盖达选择的四到五个近红外波长完全正确的分类。通常,使用NIR光谱的分化比使用MIR光谱更可靠。

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