Cereals & Grains Association
Log In

02 Features
Cereal Foods World, Vol. 63, No. 1
DOI: https://doi.org/10.1094/CFW-63-1-0017
Print To PDF
A Single Analytical Platform for the Rapid and Simultaneous Measurement of Protein, Oil, and β-Glucan Contents of Oats Using Near-Infrared Reflectance Spectroscopy
Devendra Paudel, Melanie Caffe-Treml, and Padmanaban Krishnan1

South Dakota State University, Brookings, SD, U.S.A.
1Corresponding author. E-mail: Padmanaban.Krishnan@SDSTATE.EDU


Abstract

Effective near-infrared reflectance spectroscopy (NIRS) predictive calibrations were developed for simultaneous multiple component measurement of constituents (protein, oil, and β-glucan contents) in whole and ground oat groats. The use of whole oat groats as a starting material represents an advancement in the science as it precludes the need for sample grinding. Samples were collected from the 2015 and 2016 crop years from various locations in the United States (South Dakota, North Dakota, Washington, Iowa, and Wisconsin), representing a large geographical region and diverse genetic range (N = 500). Predictive calibration equations were developed based on the modified partial least squares (MPLS) regression technique. Reference analyses were done using standard methods approved by AACC International and AOCS (AACCI Method 32-23.01 for β-glucan content, AACCI Method 46-30.01 for crude protein content, AOCS Standard Procedure Am 5-04 for oil content, and AACCI Method 44-15.02 for moisture content). The use of validation sample sets for each constituent, which were independent of samples used in NIRS calibration development, served as additional evidence of accuracy and precision. High coefficient of determination (R2) and one minus variance ratio (1-VR) and low standard error of calibration (SEC) and standard error of cross-validation (SECV) values provided evidence supporting the accuracy and precision of the calibration models developed for estimation of oat β-glucan, protein, and oil contents. The NIRS calibration for estimation of β-glucan content of ground oat groats yielded R2, SEC, SECV, and 1-VR values of 0.94, 0.16, 0.22, and 0.87, respectively. Protein calibration for ground oat groats yielded R2, 1-VR, SEC, and SECV values of 0.94, 0.93, 0.61, and 0.64, respectively. Calibration employing ground oat groats for oil content estimation yielded high R2 and 1-VR values of 0.93 and 0.92, respectively, and low SEC and SECV values of 0.23 and 0.26, respectively. Whole oat groat NIRS calibrations proved to be as effective as ground groat calibrations. Whole oat groat β-glucan calibrations yielded excellent R2, SEC, SECV, and 1-VR values of 0.93, 0.18, 0.23, and 0.89, respectively. For protein calibrations of whole oat groats, R2, SEC, SECV, and 1-VR values were 0.92, 0.70, 0.80, and 0.89, respectively. Oil content calibration developed with whole oat groats yielded R2, SEC, SECV, and 1-VR values of 0.90, 0.27, 0.30, and 0.88, respectively. This study showed that NIRS is an accurate and effective technology for oat quality measurement in plant breeding programs and food processing.





Trying to reach content?

View Full Article

if you don't have access, become a member

References

  1. AACC International. Method 32-23.01, β-Glucan Content of Barley and Oats—Rapid Enzymatic Procedure; Method 44-15.02, Moisture—Air-Oven Methods; Method 46-30.01, Crude Protein—Combustion Method. Approved Methods of Analysis, 11th ed. Published online at http://methods.aaccnet.org. AACC International, St. Paul, MN.
  2. Anderson, J. W., Spencer, D. B., Hamilton, C. C., Smith, S. F., Tietyen, J., Bryant, C. A., and Oeltgen, P. Oat-bran cereal lowers serum total and LDL cholesterol in hypercholesterolemic men. Am. J. Clin. Nutr. 52:495, 1990.
  3. AOCS. AOCS Official Procedure, Approved Procedure Am 5-04, Rapid Determination of Oil/Fat Utilizing High Temperature Solvent Extraction. American Oil Chemists Society, Urbana, IL, 2005.
  4. Bellato, S., Del Frate, V., Redaelli, R., Sgrulletta, D., Bucci, R., Magrì, A. D., and Marini, F. Use of near infrared reflectance and transmittance coupled to robust calibration for the evaluation of nutritional value in naked oats. J. Agric. Food Chem. 59:4349, 2011.
  5. Belousov, A. I., Verzakov, S. A., and von Frese, J. Applicational aspects of support vector machines. J. Chemom. 16:482, 2002.
  6. Bhatty, R. S. The potential of hull-less barley. Cereal Chem. 76:589, 1999.
  7. Blakeney, A. B., and Flinn, P. C. Determination of non-starch polysaccharides in cereal grains with near-infrared reflectance spectroscopy. Mol. Nutr. Food Res. 49:546, 2005.
  8. Borggard, C., and Thodberg, H. H. Optimal minimal neural interpretation of spectra. Anal. Chem. 64:545, 1992.
  9. Chen, D., Hu, B., Shao, X., and Su, Q. A new hybrid strategy for constructing a robust calibration model for near-infrared spectral analysis. Anal. Bioanal. Chem. 381:795, 2005.
  10. De Sá, R. M., and Palmer, G. H. Analysis of β-glucan in single grains of barley and malt using NIR-spectroscopy. J. Inst. Brew. 112:9, 2006.
  11. Frey, K. J. Improvement of quantity and quality of cereal grain protein. Page 9 in: Alternative Sources of Protein for Animal Production: Proceedings of a Symposium. B. R. Baumgarten, T. J. Cunha, J. Milton Bell, J. E. Halver, W. H. Hale, N. L. Jacobson, R. R. Oltjen, M. L. Sunde, and D. E. Ullrey, eds. National Academy of Sciences, Washington, DC, 1973.
  12. Geladi, P., and Kowalski, B. R. Partial least-squares regression: A tutorial. Anal. Chim. Acta 185:1, 1986.
  13. Herrera, M. P., Gao, J., Vasanthan, T., Temelli, F., Henderson, K., and Navabi, A. β-Glucan content, viscosity, and solubility of Canadian grown oat as influenced by cultivar and growing location. Can. J. Plant Sci. 96:183, 2016.
  14. Jacobsen, S., Søndergaard, I., Møller, B., Desler, T., and Munck, L. A chemometric evaluation of the underlying physical and chemical patterns that support near infrared spectroscopy of barley seeds as a tool for explorative classification of endosperm genes and gene combinations. J. Cereal Sci. 42:281, 2005.
  15. Krishnan, P. G., Park, W. J., Kephart, K. D., Reeves, D. L., and Yarrow, G. L. Measurement of protein and oil content of oat cultivars using near-infrared reflectance spectroscopy. Cereal Foods World 39:105, 1994.
  16. Krishnan, P. G., Reeves, D. L., Kephart, K. D., Thiex, N., and Calimente, M. Robustness of near infrared reflectance spectroscopy measurement of fatty acids and oil concentrations in oats. Cereal Foods World 45:513, 2000.
  17. Manley, M. Near-infrared spectroscopy and hyperspectral imaging: Non-destructive analysis of biological materials. Chem. Soc. Rev. 43:8200, 2014.
  18. Osborne, B. Review: Applications of near infrared spectroscopy in quality screening of early-generation material in cereal breeding programmes. J. Near Infrared Spectrosc. 14:93, 2006.
  19. Osborne, B. G. Near-infrared spectroscopy in food analysis. In: Encyclopedia of Analytical Chemistry (Online). DOI: 10.1002/9780470027318.a1018. John Wiley & Sons, Ltd., Hoboken, NJ, 2006.
  20. Peterson, D. M., Wesenberg, D. M., Burrup, D. E., and Erickson, C. A. Relationships among agronomic traits and grain composition in oat genotypes grown in different environments. Crop Sci. 45:1249, 2005.
  21. Queenan, K. M., Stewart, M. L., Smith, K. N., Thomas, W., Fulcher, R. G., and Slavin, J. L. Concentrated oat β-glucan, a fermentable fiber, lowers serum cholesterol in hypercholesterolemic adults in a randomized controlled trial. Nutr. J. 6:6, 2007.
  22. Schmidt, J., Gergely, S., Schönlechner, R., Grausgruber, H., Tömösközi, S., Salgó, A., and Berghofer, E. Comparison of different types of NIR instruments in ability to measure β-glucan content in naked barley. Cereal Chem. 86:398, 2009.
  23. Shewry, P. R. Seed storage proteins: Structures and biosynthesis. Plant Cell Online 7:945, 1995.
  24. Sohn, M., Himmelsbach, D. S., Barton, F. E., Griffey, C. A., Brooks, W., and Hicks, K. B. Near-infrared analysis of whole kernel barley: Comparison of three spectrometers. Appl. Spectrosc. 62:427, 2008.
  25. Thomas, E. V., and Haaland, D. M. Comparison of multivariate calibration method for quantitative spectral analysis. Anal. Chem. 62:1091, 1990.
  26. U.S. Department of Agriculture National Agricultural Statistics Service. Statistics by subject: National statistics for oats. Published online at www.nass.usda.gov/Statistics_by_Subject/result.php?D71E4540-3A48-302A-834B-537275051111&sector=CROPS&group=FIELD%20CROPS&comm=OATS. USDA-NASS, Washington, DC, 2016.
  27. Wolever, T. M., Tosh, S. M., Gibbs, A. L., Brand-Miller, J., Duncan, A. M., Hart, V., Lamarche, B., Thomson, B. A., Duss, R., and Wood. P. J. Physicochemical properties of oat-glucan influence its ability to reduce serum LDL cholesterol in humans: A randomized clinical trial. Am. J. Clin. Nutr. 92:723, 2010.