摘要
本文研究低场核磁共振技术与肉中水分测量的预测模型,选取新鲜猪肉样品利用MesoMR23低场核磁分析实验仪器测定T2弛豫特性,同时应用直接干燥法测定肉中实际水分含量,分别利用最小二乘法(LSE)、偏最小二乘法(PLSR)和主成分回归法(PCR)建立预测模型比较。结果表明:三种预测模型的决定系数R2均大于0.9。LSE、PLSR和PCR的预测集中,样品水分含量的预测值与参考值之间的决定系数分别为0.960、0.969和0.941,预测均方根偏差分别为0.048、0.048和0.104。因而,PLSR模型具有更好的预测结果。
The model study of moisture measurement in meat by LF-NMR was studied in this paper. The fresh pork sample was selected by MesoMR23 low field nuclear magnetic analysis instrument to determine the T2 relaxation characteristics. At the same time,the direct moisture method was used to determine the actual moisture content in the meat. Multiplication,partial least squares(PLSR)and principal component regression(PCR)were used to establish prediction models. Results indicated that the decision coefficients R2 of the three prediction models were all greater than 0.9. LSE,PLSR and PCR,the coefficient of determination between the predicted value of the sample moisture content and the reference value were 0.960,0.969 and 0.941,respectively,and the predicted root mean square deviations were 0.048,0.048 and 0.104,respectively. Therefore,the PLSR model has better prediction results.
作者
崔智勇
丁杰
徐艳
姚婕
李春保
CUI Zhi-yong;DING Jie;XU Yan;YAO Jie;LI Chun-bao(Key Laboratory of Meat Processing,MARA,Key Laboratory of,MOE,Jiangsu Collaborative,Innovation Center of Meat Production and Processing,Quality and Safety Control,College of Food science and Technology,Nanjing Agricultural University,Nanjing 210095,China;College of Science,Nanjing Agricultural University,Nanjing 210095,China)
出处
《食品工业科技》
CAS
北大核心
2020年第5期215-220,226,共7页
Science and Technology of Food Industry
基金
国家仪器重大专项课题(2018YFC1602804)
“低场核磁共振技术在肉品水分含量检测中的方法研究”(1818A02)
关键词
低场核磁共振
T2弛豫特性
水分含量
多元拟合
偏最小二乘法
low-field nuclear magnetic resonance
T2 relaxation characteristics
moisture content
multivariate calibration
partial least squares regression
