Study On Color Change And Spectral Model Of Cured Tan Mutton During Storage

Tan sheep,as a dominant and characteristic livestock species in Ningxia,is favored by consumers because of its tender meat,low fat and rich nutrition.During the processing and storage of Tan mutton,meat color is an important indicator to judge the freshness and acceptability.However,Tan mutton is prone to color deterioration due to oxidation in the supply chain,limiting the high-quality development of its industry.Therefore,on the premise of effectively extending the shelf life of Tan mutton and meat products and ensuring its the quality and safety.How to maintain its attractive color is an urgent problem to be solved in the processing of Tan mutton products.Therefore,in this paper,Tan mutton was used as the research object to study the effect of different sodium nitrite addition on the color quality of Tan mutton,and to reveal the key role of sodium nitrite in cured meat.To explore the effect of sodium nitrite on myoglobin of Tan mutton,and to clarify the mechanism of sodium nitrite stabilizing myoglobin.Raman spectroscopy prediction model of nitrosomyoglobin in cured Tan mutton was established,which provided a theoretical basis for non-destructive detection of color of cured mutton products.The main results are as follows:(1)Effect of sodium nitrite on color change of Tan mutton during storageBy measuring the sensory score,chromaticity value,pH value,metmyoglobin content,and TBARS of cured Tan mutton with different sodium nitrite addition during storage.It was found that sodium nitrite could significantly improve the color quality of Tan mutton during storage.Specifically,sodium nitrite could improve the redness value a*of Tan mutton during storage,reduce L*,b*and pH value,inhibit the increase of metmyoglobin and TBARS value,and have no significant effect on cooking loss.At the same time,the results of sensory evaluation showed that the storage quality of Tan mutton was improved with the increase of sodium nitrite addition.The sensory quality of Tan mutton treated with 100 mg/kg sodium nitrite was higher than other treatment groups during storage,maintaining a better appearance and flavour of the meat and improving its food and commercial value.(2)Effect of sodium nitrite on oxidative properties of myoglobin in Tan mutton during storageBy measuring the turbidity,solubility,surface hydrophobicity,total sulfhydryl content,carbonyl content,and secondary structure of cured Tan mutton myoglobin.It was found that sodium nitrite treatment inhibited the oxidation of myoglobin in Tan mutton.Specifically,sodium nitrite could inhibit the decrease of myoglobin solubility and total sulfhydryl content,delay the increase of turbidity,reduce surface hydrophobicity and carbonyl content which indicated that sodium nitrite could inhibit the aggregation and precipitation of myoglobin in Tan mutton,thereby reducing the oxidation of myoglobin.In addition,during the curing process,the secondary structure of myoglobin in the control group was mainly dominated by the decrease of α-helix,β-sheet and random coil and the rise of β-turn,while in the treatment group,these changes were inhibited to a certain extent,indicating that the addition of sodium nitrite could help to promote the stability of the secondary structure of myoglobin,thereby maintaining the stability of meat color.(3)Detection of nitrosomyoglobin content in Tan mutton by Raman spectroscopyThe raw spectral information of cured Tan mutton samples was collected by Raman spectroscopy,and after five abnormal samples(No.106,87,90,88,89)were eliminated sequentially by using Monte Carlo outlier detection method,the correction set and prediction set were divided by RS,KS,SPXY and 3:1 methods,among which the KS was more effective with R2p=0.8552 and RMSEP=5.2913.The raw spectra were preprocessed by eight preprocessing algorithms,MA,GF,MF,SG,SNV,De-trending,MSC and Deresolve,and a PLSR model based on the full band was built.The results demonstrated that the De-trending-PLSR model was better with R2p=0.8690 and RMSEP=5.1627.The CARS,BOSS,IRIV,UVE,VCPA,VCPA-IRIV,iVISSA-CARS,BOSS-iVISSA algorithms were used to select the characteristic wavelengths and build the characteristic wavelength based of PLSR and PCR models.The results showed that the BOSS-iVISSA-PLSR model was relatively optimal for the prediction of nitrosomyoglobin,with R2p=0.8607 and RMSEP=5.009.