One focus of the forage quality research program is Near-Infrared (NIR) Spectroscopy, a powerful analytical technique that predicts composition of small samples of material based on spectral properties of transmitted or reflected infrared light. NIR spectroscopy differs from standard infrared spectroscopy in its empirical approach; it may be thought of as a benchtop equivalent to remote sensing, although it is more accurate. As an empirical procedure, NIR spectroscopy does not require the analyst to understand physical relationships between spectra reflected by the sample and functional groups of its chemical compounds. Rather, this technology utilizes mathematical relationships between spectra and reference data, referred to as “regression equations” or “calibrations,” which are achieved through complex modeling procedures. The resulting mathematical relationships are monitored for accuracy using chemical analyses of a few samples for verification. It is common for NIR-predicted data of large sample populations to be at least as accurate as the chemically-derived data used to spawn its equations.

Researchers at other institutions are developing hardware and algorithms; this program explores NIR applications. The specific goal of this program is to quantify constituents regarded as difficult to measure by this technology. The most successful accomplishments, which also represent the first such applications of NIR spectroscopy, include quantification of mold in alfalfa, chitinase activity in tall fescue, ergovaline in toxic tall fescue, and total ergot alkaloids in tall fescue. Development of these applications represents stand-alone research, but their resulting equations also provide methods to analyze samples from our greenhouse and field experiments, as noted above.

This program is actively engaged with other researchers in the analysis of non-forage samples. Working with collaborators at other universities and in departments of Animal Physiology, Food Science, and Natural Resources, the program has analyzed bovine anatomical parts (Purdue University), barley grain (University of Manitoba), vegetable oils, and purple coneflower.

Key Publications

  • Roberts, C.A., J.H. Houx III, and F.B. Fritschi. 2011. Near-infrared analysis of sweet sorghum bagasse. Crop Sci. 51: (in press).
  • Roberts, C.A., C. Ren, P. R. Beuselinck, H. R. Benedict, and K. Bilyeu. 2006. Fatty acid profiling of soybean cotyledons by near-infrared spectroscopy. Appl. Spectrosc. 60:1328-1333.
  • Roberts, C.A., H.R. Benedict, N.S Hill, R.L. Kallenbach, and G.E. Rottinghaus. 2005. Determination of ergot alkaloid content in tall fescue by near-infrared spectroscopy. Crop Sci. 45:778-783.
  • Roberts, C.A., J.W. Workman, and J.B. Reeves (eds.) 2004. Near-Infrared Spectroscopy in Agriculture. 822 p. ASA Monogr. 44, ASA, Madison, WI. Front matter (PDF)
  • Roberts, C.A., J.S. Stuth, and P.C. Flinn. 2004. Near-infrared applications in forages and feedstuffs. p. 231-267. In C.A. Roberts et al. (eds.) Near-Infrared Spectroscopy in Agriculture. ASA Monogr. 44, ASA, Madison, WI.
  • Gray, D.E., C.A. Roberts, G.E. Rottinghaus, H.E. Garrett, and S.G. Pallardy. 2001. Quantification of chicoric acid in purple coneflower by near infrared reflectance spectroscopy. Crop Sci. 41:1159-1161.
  • Kallenbach,R.L., C.A. Roberts, L.R. Teuber, G.J. Bishop-Hurley, and H.R. Benedict. 2001. Estimation of fall dormancy in alfalfa by near infrared reflectance spectroscopy. Crop Sci. 41:774-777.
  • Roberts, C.A., R.E. Joost, and G.E. Rottinghaus. 1997. Quantification of ergovaline in tall fescue by near infrared reflectance spectroscopy. Crop Sci. 37:281-284.
  • Bewig, K.M., A.D. Clarke, C.A. Roberts, and N. Unklesbay. 1994. Discriminant analysis of vegetable oils using near infrared reflectance spectroscopy. J. Am. Oil Chem. 71:195-200.
  • Roberts, C.A., S.M. Marek, W. Lei, and A.L. Karr. 1994. Quantification of chitinase activity by near infrared reflectance spectroscopy. Crop Sci. 34:1070-1073.
  • Roberts, C.A., R.R. Marquardt, A.A. Frohlich, R.L. McGraw, R.G. Rotter, and J.C. Henning. 1991. Chemical and spectral quantification of mold in barley. Cereal Chem. 68:272-275.
  • Moore, K.J., C.A. Roberts, and J.O. Fritz. 1990. Indirect estimation of the botanical composition of alfalfa-smooth bromegrass mixtures at three stages of maturity. Agron. J. 82:287-290.
  • Roberts, C.A., P.L. Houghton, K.J. Moore, K.A. MacMillan, and R.P. Lemenager. 1987. Analysis of bovine udder, plate, and viscera using near infrared reflectance spectroscopy. J. Anim. Sci. 65:278-281.
  • Roberts, C.A., K.J. Moore, D.W. Graffis, H.W. Kirby, and R.P. Walgenbach. 1987. Quantification of mold in hay using near infrared reflectance spectroscopy. J. Dairy Sci. 70:2560-2564.