摘要
以直接干燥法和水分活度仪测定的结果作为参考值,采用低场核磁共振仪对大米样品进行测量,获取样品的横向弛豫数据,结合化学计量学算法建立多元校正模型,实现对大米水分含量及活度的快速测定。采用偏最小二乘方法(PLS)和误差反向传播人工神经网络方法(BP-ANN)对160个校正集样品进行训练后,建立多元校正模型,并对90个预测集样本进行预测。结果显示,PLS与BP-ANN 2种方法中预测集样品的水分含量预测值和参考值之间的相关系数分别为0.937 6和0.955 5,预测均方根偏差分别为0.005 8和0.004 6,水分活度预测值和参考值之间的相关系数分别为0.983 0和0.993 4,预测均方根偏差分别为0.009 2和0.006 2,表明2种方法能够快速而准确地对大米的水分含量及活度进行预测。
The water content and activity of rice samples were determined by direct drying method and water activity meter,respectively.The measured values are considered as reference values.Furthermore,rice samples were measured by LF-NMR,and the transverse relaxation data of the samples were generated.A multivariate calibration model was created by using chemometrics algorithm to rapidly determine the water content and activity of rice.PLS and BP-ANN methods were used to train 160 calibration set samples and establish the multivariate calibration models,respectively.90 prediction set samples were predicted by the calibration models.The results show the correlation coefficients between the predicted and reference values of the moisture content of the predicted set samples for the PLS and BP-ANN methods were 0.937 6 and 0.955 5,respectively,and the predicted root mean square deviations were 0.005 8 and0.004 6,respectively.The correlation coefficients between the water activity prediction value and the reference value for the PLS and BPANN methods were 0.983 0 and 0.993 4,respectively,and the predicted root mean square deviations were 0.009 2 and 0.006 2,respectively.The results showed that both methods can quickly and accurately predict the moisture content and activity of rice.
作者
吉琳琳
夏阿林
JI Lin-lin;XIA A-lin(School of Food and Chemical Engineering,Shaoyang University,Shaoyang,Hunan 422000,China)
出处
《食品与机械》
CSCD
北大核心
2018年第11期70-74,95,共6页
Food and Machinery
基金
湖南省教育厅科学研究重点项目(编号:16A236)
邵阳学院研究生科研创新项目(编号:CX2017SY011)
关键词
大米
低场核磁共振
水分含量
水分活度
化学计
量学
rice
low field nuclear magnetic resonance
water content
water activity
chemometrics
