Simplifying Wheat Quality Assessment: Using Near-Infrared\nSpectroscopy and Analysis of Variance Simultaneous Component Analysis\nto Study Regional and Annual Effects

Assessing the quality\nof wheat, one of humanity’s most important\ncrops, in a straightforward manner, is essential. In this study, analysis\nof variance (ANOVA) simultaneous component analysis (ASCA) paired\nwith near-infrared spectroscopy (NIRS) was used as an easy-to-implement\nand environmentally friendly tool for this purpose. The capabilities\nof combining NIRS with ASCA were demonstrated by studying the effects\nof sampling site and year on the quality of 180 Austrian wheat samples\nacross four sites over 3 years. It was found that the year, sample\nsite, and their combination significantly (<i>p</i> <\n0.001) affect the NIR spectra of wheat. NIR spectral preprocessing\ntools, usually employed in chemometric workflows, notably influence the results obtained by ASCA,\nparticularly in terms of the variance attributed to annual and regional\neffects. The influence of the year was identified as the dominant\nfactor, followed by region and the combined effect of year and sampling\nsite. Interpretation of the loading plots obtained by ASCA demonstrates\nthat wheat components such as proteins, carbohydrates, moisture, or\nfat contribute to annual and regional differences. Additionally, the\nprotein, starch, moisture, fat, fiber, and ash contents of wheat samples\nobtained using a NIR-based calibration were found to be significantly\ninfluenced by year, sampling site, or their combination using ANOVA.\nThis study shows that the combination of ASCA with NIRS simplifies\nNIR-based quality assessment of wheat without the need for time- and\nchemical-consuming calibration development.