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| Rapid Detection of Freshness of Crayfish by Near Infrared Spectroscopy |
| LU Wenchao, QIU Liang, XIONG Guangquan, BAI Chan, ZU Xiaoyan, LIAO Tao |
| 1.School of Chemistry and Environmental Engineering, Wuhan Institute of Technology, Wuhan 430073, China; 2.Key Laboratory of Agricultural Products Cold Chain Logistics, Ministry of Agriculture and Rural Affairs, Hubei Engineering Research Center for Agricultural Products Irradiation, Institute of Agro-Products Processing and Nuclear Agricultural Technology, Hubei Academy of Agricultural Sciences, Wuhan 430064, China |
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Abstract Near infrared spectroscopy (NIRS) combined with chemometrics was used to quickly detect the freshness of crayfish. Near infrared spectra of intact and minced crayfish flesh were recorded in the wavelength range of 850–1 050 nm and preprocessed for the development of a quantitative prediction model for crayfish freshness based on total volatile basic nitrogen (TVB-N) content using partial least square (PLS) and a combinatorial algorithm. The model established using a spectral pretreatment method combining standard normal variate transformation with first derivative had the best prediction performance, and the model based on the spectra of minced crayfish meat had better performance than that developed from the spectra of intact crayfish meat. In order to meet the needs of practical application, the TVB-N content prediction model for minced shrimp meat was analyzed, revealing that the cross-validation error and the cross-validation correlation coefficient were 3.123 and 0.947, respectively. This model was used to predict 24 samples in the prediction set, and it was found that the cross-validation correlation coefficient between the predicted and measured values was 0.951 4, and that the accuracy of prediction was 100% for TVB-N content exceeding 20 mg/100 g (stale samples). In conclusion, NIRS can be used to quickly detect the freshness of crayfish, and the established model has good predictive ability.
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2022, Vol. 36 
