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Spectrum identification method for high-temperature sterilized milk, pasteurized milk and pasteurized milk doped with high-temperature sterilized milk

A high-temperature sterilization and pasteurization technology, which is used in character and pattern recognition, material analysis by optical means, measurement devices, etc., can solve the problems of poor data mining results, huge data, inconsistency, etc. The effect of improving speed and accuracy

Pending Publication Date: 2021-08-27
HUAZHONG AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The data output by the mid-infrared spectrometer is a matrix of n×1060 (n is the sample size), the data is huge, and it is difficult to avoid data incompleteness, inconsistency, and is easily disturbed by noise (errors or outliers). Low-quality data will lead to Poor data mining results, so some method is needed to preprocess the output data

Method used

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  • Spectrum identification method for high-temperature sterilized milk, pasteurized milk and pasteurized milk doped with high-temperature sterilized milk
  • Spectrum identification method for high-temperature sterilized milk, pasteurized milk and pasteurized milk doped with high-temperature sterilized milk
  • Spectrum identification method for high-temperature sterilized milk, pasteurized milk and pasteurized milk doped with high-temperature sterilized milk

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] Example 1: Establishment of the model

[0035] Apparatus and equipment: MilkoScanTM7RM milk component detector produced by FOSS Company was selected (operated according to the product instruction manual).

[0036] Specific steps are as follows:

[0037] (1) Collect milk samples

[0038]Commercially purchase different batches of pasteurized milk and high-temperature sterilized milk, mix all the high-temperature sterilized milk, and mix the high-temperature sterilized milk according to the volume percentage of 0%, 10%, 20%, 50%, and 100% respectively. Added to pasteurized milk, the numbers of the five adulterated fresh milks were 1, 2, 3, 4 and 5, and the sample numbers of the five adulterated fresh milks were 111, 110, 114, 113, 102, A total of 550 samples.

[0039] (2) Acquisition of mid-infrared spectra

[0040] Pour the milk samples into cylindrical sample tubes with a diameter of 3.5cm and a height of 9cm to ensure that the liquid level is greater than 6cm, then ...

Embodiment 2

[0060] Embodiment 2: the application of the model of the present invention

[0061] Using the technologies of measuring spectrum and data preprocessing in Example 1, 50 samples were measured and processed, and the optimal model selected was used for identification. The results are shown in Table 4.

[0062] Table 4 model application results

[0063]

[0064]

[0065] The present invention measures and processes 50 samples, and eliminates one abnormal value based on the Mahalanobis distance. Using the screened optimal model for identification, one misclassification was detected (category 2 was misjudged as category 3), and the remaining 48 samples were all classified correctly, with an overall accuracy rate of 0.98.

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Abstract

The invention belongs to the technical field of dairy product analysis, and particularly relates to a spectrum identification method for high-temperature sterilized milk, pasteurized milk and pasteurized milk doped with the high-temperature sterilized milk. The method comprises the steps of 1) taking pasteurized milk and high-temperature sterilized milk, and simulating different adding proportions of the pasteurized milk to prepare samples; 2) scanning the samples in a medium infrared spectrum range to obtain medium infrared spectrum data; 3) preprocessing the original mid-infrared spectrum, and removing abnormal values; 4) dividing the preprocessed data set into a training set and a test set according to stratified sampling; 5) screening a modeling spectral band; 6) detecting the sample identification model on the training set through 10-fold cross validation by using a nearest neighbor algorithm and the like, and evaluating and screening the model by using accuracy and kappa coefficients; and 7) verifying the optimal model. According to the method, less wave points are used for modeling, the operation cost is reduced, and the identification rate and accuracy are improved.

Description

technical field [0001] The invention belongs to the technical field of milk product analysis, in particular to a rapid identification method for pasteurized milk mixed with high-temperature sterilized milk, pasteurized milk and high-temperature sterilized milk Background technique [0002] Milk contains protein, fat, carbohydrates, vitamins, minerals and essential amino acids and other nutrients, but freshly squeezed raw milk also contains a variety of microorganisms, so it is necessary to destroy or reduce pathogenic microorganisms in milk and reduce enzymes To ensure milk safety and prolong shelf life, raw milk is usually heat-treated (Liu, Grosvenor et al. 2019). The most commonly used heat treatment methods are pasteurization (70-85°C for 15-20 seconds) and high temperature sterilization (UHT: 135-150°C for 1-10 seconds). Studies have shown that heat treatment will reduce the antioxidant capacity of milk. Compared with raw milk and pasteurized milk, high-temperature ste...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/3577G06K9/62
CPCG01N21/3577G06F18/2411G06F18/24323
Inventor 张淑君罗雪路南良康王海童苏俊东张依
Owner HUAZHONG AGRI UNIV
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