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基于近红外漫反射光谱的面包老化过程中非冻结水含量无损检测
引用本文:闫奕霏,高 薪,汤修映. 基于近红外漫反射光谱的面包老化过程中非冻结水含量无损检测[J]. 食品安全质量检测学报, 2022, 13(22): 7264-7271
作者姓名:闫奕霏  高 薪  汤修映
作者单位:中国农业大学工学院,中国农业大学工学院,中国农业大学工学院
基金项目:“十三五 食品安全关键技术研发”重点专项“粮油质量安全过程保障与追溯技术集成与示范”
摘    要:目的 建立一种基于近红外光谱技术快速无损测定面包老化过程中的非冻结水含量的方法。方法 应用近红外漫反射光谱技术采集新鲜面包在放置2h、2d、3d、4d、5d、6d、7d时的光谱,对比导数、S-G平滑(Savitzky Golay smooth)、标准正态变量变换(Standard normal variable transformation,SNV)及多元散射校正(Multiplicative scatter correction,MSC)预处理方法,利用偏最小二乘回归法(Partial least square regression,PLSR)和多元线性回归法(Multiple Linear Regression,MLR)建立面包老化过程中的非冻结水含量的预测模型,并对比两种模型预测结果。结果 利用PLSR建模相较MLR建模结果较好,建立的模型预测结果较好,模型的校正集相关系数(Rc)和均方根误差(RMSEC)分别为0.9386和0.0236 , 验证集相关系数(Rv)和均方根误差(RMSEP)分别为0.9271和0.0245。结论 通过近红外光谱技术结合偏最小二乘法建立面包老化过程中的非冻结水含量模型可作为面包老化过程中的非冻结水含量无损快速测定的可行性方法,其含量变化可以有效预测面包老化,为面包老化的无损检测提供了新的可行方案。

关 键 词:面包老化  非冻结水  近红外光谱  偏最小二乘回归
收稿时间:2022-08-16
修稿时间:2022-11-09

Non-destructive detection of non-frozen water content during bread aging based on near infrared diffuse reflection spectroscopy
YAN Yi-Fei,GAO Xin,TANG Xiu-Ying. Non-destructive detection of non-frozen water content during bread aging based on near infrared diffuse reflection spectroscopy[J]. Journal of Food Safety & Quality, 2022, 13(22): 7264-7271
Authors:YAN Yi-Fei  GAO Xin  TANG Xiu-Ying
Affiliation:College of Engineering,China Agricultural University,College of Engineering,China Agricultural University,College of Engineering,China Agricultural University
Abstract:Objective To establish a rapid and non-destructive method for the determination of non-frozen water content in bread aging process based on near infrared spectroscopy. Methods near infrared diffuse reflectance spectroscopy was used to collect the spectra of fresh bread at 2h, 2d, 3d, 4d, 5d, 6d and 7d [1], and the pretreatment methods of derivative, Savitzky Golay smooth, Standard Normal Variable transformation (SNV) and Multiple Scatter Correction (MSC) were compared, Partial Least Square Regression (PLSR) and Multiple Linear Regression (MLR) were used to establish the prediction model of non frozen water content during bread aging, and the prediction results of the two models were compared. Results The results of PLSR modeling are better than those of MLR modeling, and the prediction results of the established model are better. The correlation coefficient (RC) and root mean square error (RMSEC) of the model are 0.9386 and 0.0236 respectively, and the correlation coefficient (RV) and root mean square error (RMSEP) of the validation set are 0.9271 and 0.0245 respectively. Conclusion the model of non-frozen water content in bread aging process established by near infrared spectroscopy combined with partial least square method can be used as a feasible method for nondestructive and rapid determination of non-frozen water content in bread aging process. The change of its content can effectively predict the aging of bread, and provide a new feasible scheme for nondestructive testing of bread aging.
Keywords:bread aging   non-frozen water   near infrared spectroscopy   partial least squares regression
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