Quantitative Analysis of Adulterations in Oat Flour by FT-NIR Spectroscopy, Incomplete Unbalanced Randomized Block Design, and Partial Least Squares

Abstract

This paper developed a rapid and nondestructive method for quantitative analysis of a cheaper adulterant (wheat flour) in oat flour by NIR spectroscopy and chemometrics. Reflectance FT-NIR spectra in the range of 4000 to 12000 cm−1 of 300 oat flour objects adulterated with wheat flour were measured. The doping levels of wheat flour ranged from 5% to 50% (w/w). To ensure the generalization performance of the method, both the oat and the wheat flour samples were collected from different producing areas and an incomplete unbalanced randomized block (IURB) design was performed to include the significant variations that may be encountered in future samples. Partial least squares regression (PLSR) was used to develop calibration models for predicting the levels of wheat flour. Different preprocessing methods including smoothing, taking second-order derivative (D2), and standard normal variate (SNV) transformation were investigated to improve the model accuracy of PLS. The root mean squared error of Monte Carlo cross-validation (RMSEMCCV) and root mean squared error of prediction (RMSEP) were 1.921 and 1.975 (%, w/w) by D2-PLS, respectively. The results indicate that NIR and chemometrics can provide a rapid method for quantitative analysis of wheat flour in oat flour.

Fourier Transform Infrared and Raman and Hyperspectral Imaging Techniques for Quality Determinations of Powdery Foods: A Review

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Online NIR Analysis and Prediction Model for Synthesis Process of Ethyl 2-Chloropropionate

“…Spectral data were manipulated by identifying the proper spectral region (1000–1240 nm) and choosing SNV + second-order derivative as appropriate pretreatment method, and then they were correlated with the data measured by the reference assays using PLSR method to develop calibration models [ 21 ]. After the study of optimal number of principal components, the correlation diagram of reference and NIR prediction of ethyl 2-chloropropionate in related reaction process is shown in Figure 7 .…”

Estimation of Acacia melanoxylon unbleached Kraft pulp brightness by NIR spectroscopy

“…Given Near-infrared (NIR) spectroscopy it is one of the most powerful non-destructive techniques, has been applied to the determination of various properties in numerous materials, such as food (Wang et al, 2014;Fu et al, 2012), ethanol (Xu et al, 2013), and wood lignin (Zhang et al, 2011;Yao et al, 2010;Alves et al, 2006;Hodge & Woodbridge, 2004;Poke et al, 2004;Schwanninger & Hinterstoisser, 2001) and cellulose (Tyson et al, 2010;Hein et al, 2009;Poke et al, 2006), wood properties and basic density (Santos et al, 2012a;Alves et al, 2012;Sykes et al, 2005;Kelley et al, 2004;Hauksson et al, 2001), pulp yield, kappa number and mechanical and optical properties of pulps Downes et al, 2009;Schimleck et al, 2006;Fardim et al, 2005;Schimleck et al, 2005;Fardim et al, 2002).…”