Rapid identification method for four kinds of high-temperature sterilized commercial milk

Abstract

The invention belongs to the field of dairy product analysis, and particularly relates to a rapid identification method for four kinds of high-temperature sterilized commercial milk. The four kinds of high-temperature sterilized commercial milk are pure milk, high-end milk, organic milk and A2-beta casein milk. The method comprises the steps of 1) collecting samples of four kinds of high-temperature sterilized milk; 2) scanning the samples in the mid-infrared spectrum range to obtain mid-infrared spectrum data; 3) preprocessing the original mid-infrared spectrum to remove abnormal values; 4) dividing the preprocessed data set into a training set and a test set according to a stratified sampling principle; 5) screening spectral bands for modeling; 6) combining different spectrum preprocessing methods and modeling algorithms, establishing an identification model, evaluating the model by using accuracy and a Kappa coefficient, and screening out an optimal preprocessing method and modeling algorithm combination to obtain an optimal model; and 7) verifying the model, and evaluating the generalization ability of the model.

Description

technical field [0001] The invention belongs to the technical field of milk product analysis, and specifically relates to a rapid identification method for four main commercial milks in high-temperature sterilized milk. The four main commercial milks include pure milk (protein content 3.2g / 100ml, fat content 4g / 100ml), high-end Milk (protein content 3.6g / 100ml, fat content 4.4g / 100ml), organic milk (3.8g / 100ml, fat content 4.6g / 100ml) and A2-β casein pure milk (contains only A2-β casein without Pure milk with A1-beta casein). The technical field of the invention is related to the field of mid-infrared spectroscopy. Background technique [0002] In recent years, the income level of Chinese residents has continued to increase, and people's consumption tendency has also shifted to a higher level and more demand for dairy products, such as buying nutritious high-end milk with higher milk protein content, healthy and natural healthy organic milk, And special A2-β casein pure mi...

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 not 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 specific methods need to be used to preprocess the output data

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