Discriminating Oat and Groat Kernels from Other Grains Using Near‐Infrared Spectroscopy

Oats and groats can be discriminated from other grains such as barley, wheat, rye, and triticale (nonoats) with near‐infrared spectroscopy. The two instruments tested herein were the manual version of the United States Department of Agriculture–Agricultural Research Service single‐kernel near‐infrared (SKNIR) instrument and the automated QualySense QSorter Explorer high‐speed sorter, both used in similar near‐infrared spectral ranges. Three linear discriminate self‐prediction models were developed: 1) oats versus groats + nonoats, 2) oats + groats versus nonoats, and 3) groats versus nonoats. For all three models, the SKNIR instrument showed high correct classification of oats or groats (94.5–100%), which was similar to results of the QSorter Explorer at 95.0–99.4%. The amount of nonoats that were misclassified as oats or groats was low for both instruments at 0–0.2% for the SKNIR instrument and 0.8–3.7% for the QSorter Explorer. Linear discriminate models from independent prediction and validation sets yielded classification accuracies of 91.6–99.3% (SKNIR) and 90.5–97.8% (QSorter Explorer). Small differences in classification accuracy were attributed to processing speeds between the two instruments: 3 kernels/s for the SKNIR instrument and 35 kernels/s for the QSorter Explorer. This indicated that both instruments are useful for quantifying grain sample compositions of oat and groat samples and that both could be useful tools for meeting consumer demand for gluten‐free or low‐gluten products. Discrimination between grains will help producers and manufacturers meet various regulatory requirements. Examples include requirements such as those from the U.S. Food and Drug Administration and the Commission of European Communities, in which gluten‐free oats or other products can only be labeled as nongluten if they contain gluten at less than 20 ppm, the established safe consumption limit for people with celiac disease. The QSorter Explorer is currently being used to meet these requirements.