Adulteration detection method for beef on the basis of bio-speckles and inertia moment spectrum analysis

Abstract

The invention discloses an adulteration detection method for beef on the basis of bio-speckles and inertia moment spectrum analysis. The method includes the steps of: 1) collecting a bio-speckle imageof a beef sample by means of a He-Ne laser device and a CCD camera; 2) constructing an inertia moment spectrum of the bio-speckle image; 3) establishing a beef adulteration detection model. For the first time, the method employs the bio-speckle for adulteration detection of beef. The detection method is high in accuracy, is low in cost and short in time, is low in requirement on experimental equipment and personnel, and is a quick, simple and sensitive adulteration detection method for beef.

Description

technical field [0001] The invention belongs to the field of food detection and relates to a method for detecting beef adulteration. Background technique [0002] As a high-protein, low-fat and low-cholesterol food, beef is one of the main meat foods in my country. However, unscrupulous traders adulterate beef products driven by economic interests, such as mixing low-value meat such as chicken and pork into beef products. Beef adulteration has seriously endangered the economic interests and health of consumers, and it is difficult to be detected by conventional methods. Therefore, it is very necessary to detect beef adulteration. In recent years, detection methods such as chromatography, protein electrophoresis separation, immunology and DNA technology have been widely used in the detection of meat adulteration. However, although these methods have high detection accuracy, they are expensive, time-consuming, and have high requirements for experimental equipment and experi...

AI Technical Summary

Problems solved by technology

However, the former method only extracts the local information of the sample space, and the result is easily affected by the local differences of the sample (such as the uniformity of the sample, the irregularity of the sample surface, and the abnormal points of the speckle image, etc.), and cannot reflect the overall Speckle activity

However, when calculating the maximum value of all column (row) IM values, the abnormal points in the speckle image will cause deviations in the results, and there is still no effective theoretical support for using the maximum value of IM to represent the biological speckle activity of the sample.

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