Rapid Detection Of Water-injected Pork Based On Low-field Nuclear Magnetic Resonance

Many methods have been used for detecting water-injected meat,while they are difficult to achieve the goal of fast and effective detection.Low-field nuclear magnetic resonance?LF-NMR?,as a new detection method,not only can obtain the information of water distribution and moisture content in samples,but also have the advantages of rapid and non-destructive detection,no pretreatment,real-time data acquisition,etc.So,it is very suitable for analyzing and detecting water-injected meat.In this study,porcine meat was used as the research object.LF-NMR was adopted to analyze and detect the water-injected pork,and the prediction model was selected to quickly predict the moisture content in water-injected pork.The specific researches were as follows:The water-injected experiment was implemented by injecting water into the longissimus dorsi muscles.The optimal standing time after injecting water into pork was determined by analyzing the dynamic changes of the effective injection ratio and the changes of moisture content in different parts of pork samples during storage.The optimal injection level was determined by comparing the color parameters?L^*,a^*,b^*,and?E^*?,drip loss,cooking loss,and shear force value of water-injected pork which was injected with different content of water.The results showed that the optimal standing time after water injection was 30 min when the distance between water-injected points was 2 cm.Meanwhile,L^*,a^*,drip loss,cooking loss and shear force had significant changes when the effective injection ratio was 10%?P<0.05?.Therefore,the limit of effective injection ratio should not exceed 10%.The parameters?repetition time,semi-echo time,EchoCount,scanning times and sample weight?of LF-NMR for detecting water-injected pork were optimized in order to acquire more stable and repeatable results.Meanwhile,the effects of effective injection ratio on the relaxation characteristics of the water molecule in pork were analyzed.The results indicated that more stable results were obtained when the parameters were as follows:sample weight=3 g,repetition time=3500 ms,semi-echo time=150?s,EchoCount=3000,scanning times=16.After injecting water into pork,T_21max,T₂₂,T_22max and P₂₂ were significant increased?P<0.05?,while P₂₁ was significantly decreased?P<0.05?.This indicated that the fluidity of immobile and free water was obviously enhanced,and the content of free water was significantly increased.The combination of LF-NMR and prediction models was used for the detection of water-injected pork.LF-NMR was used to obtain the relaxation information of water-injected pork.Single linear regression?SLR?,multiple linear regression?MLR?and partial least squares regression?PLSR?models were used to quantitatively detect the moisture content in water-injected pork,and the prediction models were compared with each other for determining the optimal prediction model for water-injected pork detection.The results showed that the correlation coefficient?r?between measured moisture content and predicted moisture content obtained based on the relationship of water weight and peak area?SLR?was 0.31,root mean squared error?RMSE?was 4.02%,after optimization,r=0.45,RMSE=1.79%.In addition,PLSR and MLR models were also established,and the results showed that the prediction accuracy of moisture content was significantly improved compared with the SLR model.By comparing the prediction models of PLSR and MLR,it is found that the MLR model had better prediction results than PLSR.Furthermore,the injected water in pork samples could be clearly visualized by magnetic resonance imaging.