A method and system for rapidly detecting the freshness of edible meat

A technology for edible meat and freshness, applied in the field of detection, can solve problems such as complex algorithms, expensive instruments, and inability to be put into consumer market applications, and achieve the effects of optimizing analysis algorithms, increasing computing speed, and improving data processing efficiency

Active Publication Date: 2019-07-12
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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  • A method and system for rapidly detecting the freshness of edible meat
  • A method and system for rapidly detecting the freshness of edible meat
  • A method and system for rapidly detecting the freshness of edible meat

Examples

Experimental program
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Embodiment 1

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

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

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

[0057] S2 performs smoothing preprocessing on the spectral curve; in this embodiment, N=5 neighborhood mean filters are selected to remove the influence of random noise, and the specific formula is as follows:

[0058]

[0059] Among them, R i is the reflection value at the center wavelength after smoothing, N is the total number o...

Embodiment 2

[0067] In this embodiment, the freshness evaluation index can be used to effectively classify the freshness grades of meat samples. Threshold segmentation method was used to set thresholds for normal temperature and refrigerated samples to classify freshness. When applied to the consumer market, three freshness grades are determined, and two thresholds T1 and T2 are set as standards for dividing the freshness grades of meat samples. When FT2, it is classified as stale meat. The specific values ​​of T1 and T2 are set with reference to the standards of relevant regulatory authorities.

[0068] After detecting the sample to be tested and obtaining the original hyperspectral data, process the data according to steps S2 to S4 of Example 1 to obtain the F value of the freshness characteristic index, and determine which grade it belongs to.

Embodiment 3

[0070] see figure 2 , a system for quickly detecting the freshness of edible meat, comprising 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, which are all integrated in the smart phone. The result display module refers to returning the results obtained through the processing and analysis of the cloud data processing center to the smart phone through the wireless network for display. The result display module utilizes the screen that comes with the smartphone.

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

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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 in particular 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 public. The freshness is a direct reflection of the quality of the meat, and its status is actually related to the safety and health of consumers. However, there is no clear division mark on the freshness of chilled meat in the consumer market at this stage, and its quality varies from good to bad. 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 means such as l...

Claims

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Application Information

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Patent Type & Authority Patents(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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