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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #329407

Research Project: Impacting Quality through Preservation, Enhancement, and Measurement of Grain and Plant Traits

Location: Stored Product Insect and Engineering Research

Title: Discriminating oat and groat kernels from other grains using near infrared spectroscopy

Author
item Armstrong, Paul
item Dell'endice, Francesco - Qualysense Ag
item Maghirang, Elizabeth
item Rupenyan, Alisa - Qualysense Ag

Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/8/2016
Publication Date: 5/9/2017
Publication URL: http://handle.nal.usda.gov/10113/5683881
Citation: Armstrong, P.R., Dell'Endice, F., Maghirang, E.B., Rupenyan, A. 2017. Discriminating oat and groat kernels from other grains using near infrared spectroscopy. Cereal Chemistry. 94(3):458-463. doi:10.1094/CCHEM-06-16-0162-R.

Interpretive Summary: U.S. Food and Drug Administration and Commission of European Communities requires that gluten-free oats or products can only be labeled as non-gluten if it contains less than 20 ppm gluten, the established safe consumption limit for people with celiac disease. The need for testing samples for gluten products is highly sought by industry to assure a gluten-free product can be delivered. In response to this need two instruments were tested to see if they could discriminate gluten containing grains from oat and groat grains. One instrument was developed by USDA-ARS and the other was a commercially available high-speed sorter, QSorter Explorer from QualySense AG. Both instruments use near-infrared light measurement techniques for measurement. Initial design and testing was completed under a CRADA with USDA-ARS for the QualySense instrument. Multiple grain types from many sources were used in the study and included various US classes of wheat and barley, rye and triticale. Results from the study show both instruments can distinguish oats and groats from other grains with excellent accuracy, 95% to 100%, and can thus provide an excellent method to evaluate samples for gluten containing products. The USDA-ARS instrument can operate at 3 kernels/s while the QSorter operates at 35 kernels/s. The QSorter Explorer is currently being used to help meet gluten–free requirements by some processors.

Technical Abstract: Oat and groats can be discriminated from other grains such as barley, wheat, rye, and triticale (non-oats) using near infrared spectroscopy. The two instruments tested were the manual version of the ARS-USDA Single Kernel Near Infrared (SKNIR) and the automated QualySense QSorter Explorer high-speed sorter, both using similar near-infrared spectral ranges. Three linear discriminate models were developed: (1) oats versus groats plus non-oats, (2) oats plus groats versus non-oats, and (3) groats versus non-oats. For all three models, the SKNIR showed high correct classification of oats and/or groats (94.5 to 100%) similar to that of the QSorter Explorer at 95.0 to 99.4%. The misclassified non-oats that were classified as oats and/or groats were low for both instruments at 0 to 0.2% for SKNIR and 0.8 to 3.7% for the QSorter Explorer. The difference in classification accuracies may be attributed to processing speeds between the two instruments at 3 kernels/s for SKNIR and 35 kernels/s for QSorter Explorer. This shows that both instruments are useful to quantify grain sample composition of oats and groats samples, and can be a useful tool in meeting consumer demand for non-gluten or low-gluten products. This potential for discriminating across grains will continue to help producers and manufacturers meet various requirements such as those from the U.S. Food and Drug Administration and Commission of European Communities where gluten-free oats or other products can only be labeled as non-gluten if it contains less than 20 ppm gluten, the established safe consumption limit for people with celiac disease. The QSorter Explorer is currently being used to meet these requirements.