研究目的
To develop a rapid and non-destructive method based on visible near-infrared (Vis-NIR) hyperspectral imaging system for detection of adulteration with duck meat in minced lamb meat.
研究成果
The study demonstrated the great potential of hyperspectral imaging technology for rapidly and accurately detecting meat adulteration in minced lamb meat. The PLSR model with selected wavelengths achieved satisfactory results, and the prediction map of the duck minced in lamb meat was successfully generated.
研究不足
The study did not take breed of the lamb and duck into consideration when sampling, therefore the number and biological variability of samples will be the focus of next research.
1：Experimental Design and Method Selection:
The study utilized a visible/near-infrared (VIS/NIR) hyperspectral imaging system in the spectral range of 400–1100 nm for detecting adulteration in minced lamb meat. The method involved the use of multiple averages of the reference spectral and a predicted relative spatial distribution coefficient to reduce noise.
2：Sample Selection and Data Sources:
Pure raw lamb meat and raw duck meat were collected, minced, and adulterated by mixing minced duck meat in the range of 0%–100% (w/w) with 5% increments. A total of 63 samples were prepared for the study.
3：List of Experimental Equipment and Materials:
The hyperspectral imaging system was composed of a charge coupled device (CCD) camera, an imaging spectrograph, and an illumination unit with a halogen bulb. Samples were placed in a disposable Te?on dish for data collection.
4：Experimental Procedures and Operational Workflow:
Samples were scanned automatically line by line to build a hypercube. Data acquiring and processing was controlled by self-programed software.
5：Data Analysis Methods:
Partial least square regression (PLSR) was employed to develop a model to predict the content of adulteration. The accuracy of the calibration models was evaluated by coefficient of determination and root mean square errors.
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