Method and system for quickly detecting freshness of edible meat

A technology for edible meat and freshness, applied in the field of detection, can solve the problems of being unable to be used in the consumer market, complex algorithms, expensive instruments, etc., and achieve the effects of improving data processing efficiency, optimizing analysis algorithms, and increasing computing speed

Active Publication Date: 2017-06-13
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to propose a method for quickly detecting the freshness of edible meat based on hyperspectral technology, so as to solve the problem of complex algorithms and expensive instruments in the current technology, which are only limited to the laboratory. The problem of identifying the freshness of meat cannot be put into the consumer market

Method used

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  • Method and system for quickly detecting freshness of edible meat
  • Method and system for quickly detecting freshness of edible meat
  • Method and system for quickly detecting freshness of edible meat

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Experimental program
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Embodiment 1

[0054] The sample detected in this embodiment is pork, and the data processing flow is as follows figure 1 .

[0055] S1 activates the light source and the miniature hyperspectral sensor to obtain the original hyperspectral data of the edible meat sample to be detected; the portable spectrometer obtains the hyperspectral reflectance curve of the pork sample to be identified in the preset waveband, and the spectral range covers 400-2500nm.

[0056] Pork samples were placed under normal temperature and refrigerated conditions, and tested every 12h between 0~96h, such as image 3 , Figure 4 The time marked in the inner text box.

[0057] S2 performs smoothing preprocessing on the spectral curve; in this embodiment, an N=5 neighborhood average filter is selected to remove the influence of random noise. The specific formula is as follows:

[0058]

[0059] Where R i Is the reflection value at the center wavelength after smoothing, N is the total number of bands in the neighborhood window, ...

Embodiment 2

[0067] In this embodiment, the freshness evaluation index can be used to effectively classify the freshness levels of meat samples. Threshold segmentation method is used to set thresholds for normal temperature and refrigerated samples to classify freshness. When applied to the consumer market, three levels of freshness are determined, and two thresholds T1 and T2 are set as the criteria for dividing the freshness levels of meat samples. F It is classified as stale meat at T2. The specific values ​​of T1 and T2 are set with reference to the standards of relevant regulatory authorities.

[0068] After the sample to be tested is tested and the original hyperspectral data is obtained, the data is processed according to steps S2 to S4 in Example 1 to obtain the freshness characteristic index F value and determine which level it belongs to.

Embodiment 3

[0070] See figure 2 , A system for quickly detecting the freshness of edible meat, including a light source module, a spectral data acquisition module, a spectral data analysis module, a meat freshness detection module, and a result display module.

[0071] The light source module includes a miniature halogen lamp, and the spectral data acquisition module includes a miniature hyperspectral sensor, all of which are integrated in the smartphone. The result display module refers to the processing and analysis of the results obtained by the cloud data processing center through the wireless network back to the smart phone for display. The result display module uses the screen that comes with the smartphone.

[0072] The spectral data analysis module refers to that the cloud data processing center calls a pre-set spectral data preprocessing model, feature transformation model, freshness index calculation model, etc., to process and analyze the raw spectral data of the meat. This module...

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Abstract

The invention provides a method for quickly detecting freshness of edible meat. The method comprises the following steps: S1) starting a light source and a miniature hyperspectral sensor to acquire original hyperspectral data of a to-be-detected edible meat sample; S2) preprocessing collected hyperspectral data, wherein the preprocessing includes one or more of noise reduction treatment, reflectivity calculation and characteristic enhancement process; S3) performing characteristic space alternation on the preprocessed hyperspectral data, thereby acquiring a hyperspectral characteristic value relative to No. i waveband in the characteristic space of to-be-detected meat; S4) selecting the characteristic value corresponding to a specific wavelength in the transformed characteristic space and constructing a freshness distinguishing index used for distinguishing the freshness level of an unknown meat sample. According to the method provided by the invention, the freshness index with high reliability is acquired through the treatment and analysis on spectroscopic data of meat under different conditions in several days and the sample freshness can be quickly judged.

Description

Technical field [0001] The invention belongs to the detection field, and specifically relates to a method for detecting the freshness of meat by using the optical properties of materials. Background technique [0002] Chilled meat is one of the main foods consumed by the general public. Freshness is a direct reflection of the quality of meat, and its status is actually related to the safety and health of consumers. However, there is no clear classification mark on the freshness of chilled meat in the consumer market at this stage, and its quality varies. Commonly used meat freshness detection methods include sensory detection, physical and chemical detection, microbial detection, and detection methods based on near-infrared spectroscopy that have developed rapidly in recent years. Sensory testing is the most widely used freshness identification method in the consumer market. Consumers can qualitatively judge the freshness of meat through physical methods such as color, smell, an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/25
CPCG01N21/25
Inventor 张立福黄长平张霞岑奕王楠
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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