Elucidating the attributes of winter wheat grain quality under reduced nitrogen input through near‐infrared spectroscopy.

Background and Objectives: Research in crop science is usually conducted in studies with a small number of plants and crops. The aim of this project was to investigate whether near‐infrared spectroscopy (NIRS) can contribute to the analysis of such small data sets. For this purpose, NIR spectra of a small sample set of whole‐grain wheat flours of two winter wheat cultivars harvested from greenhouse and field experiments with different fertilization management were analyzed. Findings: Principal component analysis (PCA) facilitated the discrimination of samples based on fertilization, baking volume, and growing conditions for each wheat cultivar. In addition, PCA allowed the differentiation of wheat cultivars in a data set containing both cultivars. Spectra–structure relationships were also established. Accurate calibrations with R2 of.98,.98, and.54 were obtained for fertilization, crude protein concentration, and baking volume, respectively, even for a small data set of 10 samples of wheat cultivar Discus. Conclusion: The NIR spectra of whole‐grain wheat flour samples provided high‐resolution information on various parameters such as fertilization, baking volume, wheat cultivar, and growing site. This study demonstrates that NIRS is a valuable and efficient tool for the analysis of small data sets in crop science. This illustrates the effectiveness of the elegant NIRS method. Significance and Novelty: In this study, small data sets of whole‐grain wheat flour from crop science experiments were analyzed by NIRS. Characteristic changes of the NIR spectra based on applied fertilizer amount, crude protein concentration, baking volume, growing site, and wheat cultivar were revealed. The detection of cause‐and‐effect relationships between spectra and chemical properties of samples contributes to a better understanding of NIR spectra of wheat flours in an interpretative way. [ABSTRACT FROM AUTHOR]