Simplifying Wheat Quality Assessment: Using Near-Infrared Spectroscopy and Analysis of Variance Simultaneous Component Analysis to Study Regional and Annual Effects

Assessing the quality
of wheat, one of humanity’s most important
crops, in a straightforward manner, is essential. In this study, analysis
of variance (ANOVA) simultaneous component analysis (ASCA) paired
with near-infrared spectroscopy (NIRS) was used as an easy-to-implement
and environmentally friendly tool for this purpose. The capabilities
of combining NIRS with ASCA were demonstrated by studying the effects
of sampling site and year on the quality of 180 Austrian wheat samples
across four sites over 3 years. It was found that the year, sample
site, and their combination significantly (p <
0.001) affect the NIR spectra of wheat. NIR spectral preprocessing
tools, usually employed in chemometric workflows, notably influence the results obtained by ASCA,
particularly in terms of the variance attributed to annual and regional
effects. The influence of the year was identified as the dominant
factor, followed by region and the combined effect of year and sampling
site. Interpretation of the loading plots obtained by ASCA demonstrates
that wheat components such as proteins, carbohydrates, moisture, or
fat contribute to annual and regional differences. Additionally, the
protein, starch, moisture, fat, fiber, and ash contents of wheat samples
obtained using a NIR-based calibration were found to be significantly
influenced by year, sampling site, or their combination using ANOVA.
This study shows that the combination of ASCA with NIRS simplifies
NIR-based quality assessment of wheat without the need for time- and
chemical-consuming calibration development.