食品工业科技2024，Vol.45Issue(8)：301-308,8.DOI:10.13386/j.issn1002-0306.2023060175
基于低场核磁共振的预包装即食牛肉保质期预测模型研究
Research on Shelf Life Predicting Model of Prepackaged Instant Beef Based on Low-field Nuclear Magnetic Resonance
摘要
Abstract
Objective:Conducting research on fast,accurate,and non-destructive prediction methods for the shelf life of prepackaged instant beef had great significance for ensuring the safety of the shelf life of product.Methods:Using prepackaged instant beef as the analysis object,the T2 relaxation time of low field nuclear magnetic resonance(NMR)proton was collected from the sample,and a quantitative analysis model for the moisture content of instant beef was established.A prediction model for the shelf life of prepackaged instant beef was established based on the sensory acceptance of the sample.Results:The lateral relaxation time of the low-field nuclear magnetic resonance spectrum of prepackaged instant beef could better reflect the quality changes of spaceflight instant beef with the extension of storage time.A water content prediction model for instant beef was established,with a prediction error of less than 4%.The correlation coefficient(r)of the modeling set was 0.9405,the corrected standard deviation(RMSECV)was 34.5,and the relative analysis error(RPD)was 3.1.Ten samples stored for a certain period of time but not involved in modeling were predicted to be close to the end of shelf life.The correlation between the predicted results and the measured values was 0.99,and the error range of the predicted results was 0.7%to 9.9%.The RMSEP was 13.6.The accuracy of the prediction model met the accuracy requirements of shelf life prediction.Conclusion:Low field nuclear magnetic resonance technology would have potential application in predicting the shelf life of prepackaged instant beef products.关键词
低场核磁共振/保质期/预包装即食牛肉/无损预测Key words
low-field nuclear magnetic resonance/shelf life/pre-packaged instant beef/non-destructive prediction分类
轻工纺织引用本文复制引用
董海胜,刘恒言,徐楠,何凯锋,于燕波,兰海云,杜秉健,臧鹏..基于低场核磁共振的预包装即食牛肉保质期预测模型研究[J].食品工业科技,2024,45(8):301-308,8.基金项目
航天营养与食品工程重点实验室基金(SYFDJY08). （SYFDJY08）
