A rapid determination of wheat flours components based on near infrared spectroscopy and chemometrics

IF 2.7 3区 化学 Q2 CHEMISTRY, ANALYTICAL Vibrational Spectroscopy Pub Date : 2024-01-01 DOI:10.1016/j.vibspec.2024.103650
Wanzhu Zhou , Yongqian Lei , Qidong Zhou , Jingwei Xu , He Xun , Chunhua Xu
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Abstract

In this work, a rapid and simple analytical method for the quantitative determination of moisture, protein, wet gluten, starch and sedimentation index in the wheat flour was established by the combination of near infrared spectroscopy and chemometrics. The spectra of the 229 wheat flour samples were collected by a portable near infrared fast analyzer. The contents of these components were determined according to the relevant Chinese National Standards, and were taken as the corresponding reference database. Seven spectral pretreatment methods were employed to eliminate the optical interference from background and other noise information. The best result was obtained with FD+SG(15, 3)+MC method for moisture, protein, wet gluten and sedimentation index, FD+SG(15, 2)+MC method was more suitable for starch. The principal component numbers (PCs) were also optimized to obtain a superior model effect. Furthermore, partial least squares (PLS) and multiple linear regression (MLR) modeling methods were used to quantify the content of the components. When using FD+SG(15, 3)+MC pretreatment, all the PLS model parameters were significantly better than the MLR model. Both the predicted values and the reference values showed superior linear relationship within the calibration range. Moreover, the absolute error of the predicted values and their corresponding reference values in the PLS model were within their confidence intervals, respectively. The relative errors for moisture, protein, wet gluten and starch fluctuated little, only sedimentation index fluctuated greatly. The actual prediction correct rate of moisture, protein, wet gluten, starch and sedimentation index were 96.8%, 96.8%, 90.3%, 100.0% and 80.6%, respectively, which indicated the prediction was excellent.

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基于近红外光谱和化学计量学的小麦粉成分快速测定方法
本研究采用近红外光谱法和化学计量学相结合的方法,建立了一种快速简便的定量测定小麦粉中水分、蛋白质、湿面筋、淀粉和沉淀指数的分析方法。使用便携式近红外快速分析仪采集了 229 份小麦粉样品的光谱。这些成分的含量是根据相关的中国国家标准测定的,并作为相应的参考数据库。采用了七种光谱预处理方法来消除背景和其他噪声信息的光学干扰。在水分、蛋白质、湿面筋和沉降指数方面,FD+SG(15,3)+MC 法的结果最佳;在淀粉方面,FD+SG(15,2)+MC 法更为合适。为了获得更好的模型效果,还对主成分数(PC)进行了优化。此外,还采用了偏最小二乘法(PLS)和多元线性回归(MLR)建模方法来量化各组分的含量。在使用 FD+SG(15, 3)+MC 预处理时,所有 PLS 模型参数都明显优于 MLR 模型。在定标范围内,预测值和参考值均显示出良好的线性关系。此外,PLS 模型中预测值和相应参考值的绝对误差分别在其置信区间内。水分、蛋白质、湿面筋和淀粉的相对误差波动较小,只有沉降指数波动较大。水分、蛋白质、湿面筋、淀粉和沉淀指数的实际预测正确率分别为 96.8%、96.8%、90.3%、100.0% 和 80.6%,表明预测结果非常好。
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来源期刊
Vibrational Spectroscopy
Vibrational Spectroscopy 化学-分析化学
CiteScore
4.70
自引率
4.00%
发文量
103
审稿时长
52 days
期刊介绍: Vibrational Spectroscopy provides a vehicle for the publication of original research that focuses on vibrational spectroscopy. This covers infrared, near-infrared and Raman spectroscopies and publishes papers dealing with developments in applications, theory, techniques and instrumentation. The topics covered by the journal include: Sampling techniques, Vibrational spectroscopy coupled with separation techniques, Instrumentation (Fourier transform, conventional and laser based), Data manipulation, Spectra-structure correlation and group frequencies. The application areas covered include: Analytical chemistry, Bio-organic and bio-inorganic chemistry, Organic chemistry, Inorganic chemistry, Catalysis, Environmental science, Industrial chemistry, Materials science, Physical chemistry, Polymer science, Process control, Specialized problem solving.
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