Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-05T10:31:49.316Z Has data issue: false hasContentIssue false

A comparison of sample preparation and calibration techniques for the estimation of nitrogen, oil and glucosinolate content of rapeseed by near infrared spectroscopy

Published online by Cambridge University Press:  27 March 2009

Carol Starr
Affiliation:
Plant Breeding Institute, Maria Lane, Trumpington, Cambridge, 0B2 2LQ
Janet Suttle
Affiliation:
Plant Breeding Institute, Maria Lane, Trumpington, Cambridge, 0B2 2LQ
A. G. Morgan
Affiliation:
Plant Breeding Institute, Maria Lane, Trumpington, Cambridge, 0B2 2LQ
D. B. Smith
Affiliation:
Plant Breeding Institute, Maria Lane, Trumpington, Cambridge, 0B2 2LQ

Summary

Predictions of nitrogen, oil and glucosinolate concentration in rapeseed samples were made by near infrared reflectance analysis after various grinding treatments. Also examined were the effects of normalizing reflectance data and the possible advantage of using all combinations of two and three wavelengths in the calibration regression analysis over forward stepwise regression. The main conclusion was that drying the samples prior to a controlled grinding treatment gave the best results, although acceptable results for selection purposes could be obtained using whole seeds to predict nitrogen and oil. None of the treatments of the seed or reflectance data allowed acceptable prediction of glucosinolate content.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1985

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allison, M. J., Cowe, I. A. & Mchale, R. (1978). The use of infrared reflectance for the rapid estimation of soluble β-glucan content of barley. Journal of the Institute of Brewing 84, 153155.CrossRefGoogle Scholar
American Association Of Cebeal Chemists (1980). Approved Methods.Method 39–10. St Paul: A.A.C.C.Google Scholar
Appelqvist, L. A. (1967). Further studies on a multisequential method for determination of oil content in oilseeds. Journal of the American Oil Chemists Society 44, 209214.CrossRefGoogle Scholar
Craig, E. A. & Morgan, A. G. (1980). A modified method for the quantitative determination of total glucosinolate in rapeseed. Analytical Chemistry of Rapeseed and its Products(ed. Daun, J. K., McGregor, D. I. and McGregor, E. E.), pp. 8185. Winnipeg: The Canola Council of Canada.Google Scholar
Fearn, T. & Osborne, B. G. (1982). The use and abuse of statistics in NIR. Flour, Milling and Baking Research Association Bulletin 5, 222232.Google Scholar
Hunt, W. H., Fulk, D. W., Elder, B. & Norris, K. (1977). Collaborative study on infrared reflectance devices for determination of protein in hard red winter wheat, and for protein and oil in soybeans. Cereal Foods World 22, 534536.Google Scholar
Mcclure, W. F., Hamid, A., Giesbrecht, F. G. & Weeks, W. W. (1984). Fourier analysis enhances Analysis of oil and N in rapeseed by NIB323 NIK diffuse reflectance spectroscopy. Applied Spectroscopy 38, 322329.CrossRefGoogle Scholar
Murray, I. & Hall, P. A. (1983). Animal feed evaluation by use of near infrared reflectance (NIR) spectrocomputer. Analytical Proceedings of the Royal Society of Chemistry 20, 7579.Google Scholar
Norms, K. H. & Williams, P. C. (1984). Optimization of mathematical treatments of raw near-infrared signal in the measurement of protein in hard red spring wheat. 1. Influence of particle size. Cereal Chemistry 61, 158165.Google Scholar
Rotolo, P. (1979). Near infrared reflectance instrumentation. Cereal Foods World 24, 9498.Google Scholar
Rubenthaler, G. L. & Bruinsma, B. L. (1978). Lysine estimation in cereals by near-infrared reflectance. Crop Science 18, 10391042.CrossRefGoogle Scholar
Starr, C., Morgan, A. G. & Smith, D. B. (1981). An evaluation of near infra-red reflectance analysis in some plant breeding programmes. Journal of Agricultural Science, Cambridge 97, 107118.CrossRefGoogle Scholar
Starr, C. & Smith, D. B. (1978). A semi-micro dryblock and automated analyser technique suitable for determining protein nitrogen in plant material. Journal of Agricultural Science, Cambridge 91, 639644.CrossRefGoogle Scholar
Starr, C., Smith, D. B., Blackman, J. A. & Gill, A. A. (1983). Applications of near infrared reflectance analysis in breeding wheats for bread-making quality. Analytical Proceedings of the Royal Society of Chemistry 20, 7274.Google Scholar
Tkachuk, R. (1981). % Oil and protein analysis of whole rapeseed kernels by near infrared reflectance spectroscopy. Journal of the American Oil Chemists Society 58, 819822.CrossRefGoogle Scholar
Tkachuk, R. & Kuzina, F. D. (1982). Chlorophyll analysis of whole rapeseed kernels by near infrared reflectance. Canadian Journal of Plant Science 62, 875884.CrossRefGoogle Scholar
Williams, P. C. (1975). Application of near infrared reflectance spectroscopy to analysis of cereal grains and oilseeds. Cereal Chemistry 52, 561576.Google Scholar
Williams, P. C. (1984). The significance of outliers. Proceedings of 11th ICC Congress (Vienna)(in the Press).Google Scholar
Williams, P. C., Norris, K. H., Gehrke, G. W. & Bernstein, K. (1983). Comparison of near-infrared methods for measuring protein and moisture in wheat. Cereal Foods World 28, 149152.Google Scholar