Study On The Characteristics Of Color Change During The Storage Of Cold Fresh Beef Based On Raman Spectroscopy

In recent years,the fresh beef has gradually become the mainstream of meat products because of rich nutrition.Meat quality has been paid more and more attention by consumers.The color of beef determines the purchase desire of consumers directly.Many factors affect the stability of flesh color,such as pH,myoglobin oxidation,methemoglobin reductase activity,lipid oxidation.At present,the most of reports are about single factors,however,few researches analyze on myoglobin analysis by Raman spectroscopy and stoichiometry.In addition,the rapid determination of slaughtered beef and freshness based on Raman spectroscopy has not been reported.In this paper,the main factors affecting the color stability of beef during refrigerated storage will be studied and detected myoglobin content and adulteration discrimination using Raman spectroscopy combined with chemometrics methodology.The research contents are as follows:(1)Analysis of Meat Color Stability Determination of flesh(L*,a*,b*),pH,the relative content of deoxymyosin,relative content of oxymyoglobin,relative content of high-iron myoglobin,NADH Content,lactate dehydrogenase activity and other changes.The results showed that on the 0th to 9th day,the a*value was large,the change was stable,the relative content of oxymyoglobin was the highest,the relative content of high-iron myoglobin was low,and the color of meat was stable.During the storage process,the respiration of muscle cells is weakened,and the activity of NADH and LDH is weakened,so that the reducing ability of myoglobin of high-iron is reduced and the brown color of meat is changed.(2)The color detection method was established A calculation model for deoxymyosin,oxymyoglobin,and ferritin myoglobin was obtained.Compared with the correlation coefficient of one-dimensional linear regression,PCR and PLS,the multivariate calibration method is better than the traditional one-element linear regression method.The RMSEC of PLS regression model is lower than or close to the PCR model,indicating that PLS modeling is superior to PCR,it was concluded that Raman spectroscopy can be used to detect beef myoglobin content.(3)Correlation between freshness and color The total volatile basic nitrogen(TVB-N)values of sample were taken as the reference of classification,savitzky-golay(SG)smoothing methods were used as the pretreatment method for reflectance spectra processing,The classifier models of support vector machine(SVM)were built for identification of beef freshness.The results showed that SVM classification model based on Polynomial kernel function the discrimination ability is the best,the authenticity recognition rate is 94.65%and the misjudgment rate is5.35%The identification rate of validation set was 95.12%.Using Raman spectroscopy combined with support vector machine to realize the rapid,non-destructive and accurate discrimination of freshness of fresh cold beef,the change of color was studied.It was found that in the storage process,due to the influence of microorganisms and enzymes,TVB-N The value gradually increased,according to the change of TVB-N value and the change of beef flesh color and myoglobin content,the law of color change in beef storage can be obtained,which can be used as a basis for quickly judging the freshness of beef from the color.In this paper,Raman spectroscopy combined with chemometrics method was used to study the correlation between freshness and color change of cold fresh beef.The content of myoglobin in cold fresh beef was quantitatively determined by Raman spectroscopy combined with a linear regression method.From the protein level,changes in the color of beef during storage are revealed.