Method for discriminating soy kind based on multivariate statistical analysis

A multivariate statistical analysis, soy sauce technology, applied in the direction of analysis of materials, material separation, measuring devices, etc., can solve the problems of narrow application range, and achieve the effect of wide application range, simple operation, and high accuracy

Active Publication Date: 2013-10-09
FOSHAN HAITIAN FLAVOURING & FOOD CO LTD +1
2 Cites 8 Cited by

AI-Extracted Technical Summary

Problems solved by technology

Since this method uses the characteristic fingerprint peaks of brewed soy sauce in the infrared spectrum for identification, and the infrared characteristic fin...
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Abstract

The invention discloses a method for discriminating soy kind based on multivariate statistical analysis. The method comprises: using the multivariate statistical analysis technology to establish standard cluster spaces respectively for brewed-soy volatile components and prepared-soy volatile components; then calculating to obtain a projective point of a to-be measured sample in the principle components space of the two standard cluster spaces; comparing the space distances of the projective point respectively to the two standard cluster space centers, if the distance of the projective point to the center of the brewed-soy standard cluster space, determining that the to-be measured soy sample is a brewed soy, otherwise determining that the to-be measured soy sample is a prepared soy; and thus the discrimination between the brewed soy and the prepared soy can be realized. The discrimination method between the brewed soy and the prepared soy is simple in operation, high in accuracy and wide in application.

Application Domain

Component separation

Technology Topic

Pattern recognitionMultivariate statistics +1

Image

  • Method for discriminating soy kind based on multivariate statistical analysis
  • Method for discriminating soy kind based on multivariate statistical analysis
  • Method for discriminating soy kind based on multivariate statistical analysis

Examples

  • Experimental program(2)

Example Embodiment

[0058] Example 1
[0059] Take two samples of brewed soy sauce, prepared soy sauce and HVP as the samples to be tested, and process them according to the above-mentioned discrimination method. The principal component projection diagram is as follows figure 2 As shown, the discrimination results of distance discrimination are shown in Table 2. from figure 2 It can be seen that the two samples of brewed soy sauce to be tested and the standard sample of brewed soy sauce are clustered into one category, and the other two samples of prepared soy sauce to be tested, the two HVP samples and the standard sample of prepared soy sauce are clustered into another category, which is consistent with the actual situation. match. As can be seen from Table 2, the identification accuracy rate is 100%.
[0060] Table 2 Investigation on the accuracy of identification
[0061]

Example Embodiment

[0062] Embodiment 2
[0063] The raw material HVP for preparing soy sauce is added into the brewed soy sauce, prepared into a mixture of 20%, 30%, 40% and 50%, and processed according to the above discrimination scheme. The main component projection diagram is as follows image 3 As shown, the discrimination results of distance discrimination are shown in Table 3. from image 3 It can be seen that the four HVP spiked samples to be tested and the prepared soy sauce standard samples are clustered into the same category, which is consistent with the actual situation. As can be seen from Table 3, the identification accuracy rate is 100%.
[0064] Table 3 Investigation on the accuracy of identification
[0065]
[0066]

PUM

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