Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-18T07:57:12.083Z Has data issue: false hasContentIssue false
  • English
  • Français

The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples

Published online by Cambridge University Press:  09 March 2007

D. Cozzolino ,
F. Montossi  and
R. San Julian
D. Cozzolino*
Affiliation:
Animal Nutrition and NIRS Laoratory. Estación Experimental INIA La Estanzuela. Instituto Nacional de Investigación Agropecuaria, Colonia, Uruguay
F. Montossi
Affiliation:
Sheep Program, Estación Experimental INIA Tacuarembó. Tacuarembó, Uruguay
R. San Julian
Affiliation:
Sheep Program, Estación Experimental INIA Tacuarembó. Tacuarembó, Uruguay
*
E-mail: Daniel. [email protected]
Get access

Abstract

Abstract Visible (VIS) and near infrared (NIR) reflectance spectroscopy combined with multivariate data analysis were explored to predict fibre diameter in both clean and greasy Merino wool samples. Fifty clean and 400 greasy wool samples were analysed. Samples were scanned in a large cuvette using a NIRSystems 6500 monochromator instrument by reflectance in the VIS and NIR regions (400 to 2500 nm). Partial least square (PLS) regression was used to develop a number of calibration models between the spectral and reference data. Different mathematical treatments were used during model development. Cross validation was used to assess the performance and avoid overfitting of the models. The NIR calibration models gave a coefficient of determination in calibration (R2) > 0·90 for clean wool samples and a R2 < 0·50 for greasy wool samples. The values for the residual predictive value, RPD (ratio of standard deviation (s. d.) to the root mean square of the standard error of cross validation (RMSECV)) were 3 for clean and 0·6 for greasy wool samples, respectively. The results indicated that fibre diameter in greasy wool samples was poorly predicted with NIR, while clean wool showed good relationships.

More research is required to improve the calibration on greasy wool samples if the technology is to be used for rapid analysis to assist in the selection of animals in breeding programmes.

Keywords

Fibresspectroscopywool
Type
Research Article
Information
Animal Science , Volume 80 , Issue 3 , June 2005 , pp. 333 - 337
Copyright
Copyright © British Society of Animal Science 2005

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.)

Footnotes

†The Australian Wine Research Institute, Waite Road, PO Box 197, Urrbrae, Glen Osmond 5064, Australia.

References

Barnes, R. J., Dhanoa, M. S. and Lister, S. J. 1989. Standard normal variate transformation and detrending of near infrared diffuse re. ectance spectra. Applied Spectroscopy 43: 772–777.CrossRefGoogle Scholar
Batten, G. D. 1998. Plant analysis using near infrared reflectance spectroscopy: the potential and the limitations. Australian Journal of Experimental Agriculture 38: 697–706.CrossRefGoogle Scholar
Church, J. S. and O'Neill, J. A. 1999. The detection of polymeric contaminants in loose scoured wool. Vibrational Spectroscopy 19: 285–293.CrossRefGoogle Scholar
Cleve, E., Bach, E. and Schollmeyer, E. 2000. Using chemometrics methods and NIR spectrophotometry in the textile industry. Analytica Chimica Acta 420: 163–167.CrossRefGoogle Scholar
Coleman, S. W., Lupton, C. J., Pfeiffer, F. A., Minikhiem, D. L. and Hart, S. P. 1999. Prediction of clean mohair, fibre diameter, vegetable matter, and medullated . bre with near infrared spectroscopy. Journal of Animal Science 77: 2594–2602.CrossRefGoogle Scholar
Connell, J. P. 1983. Predicting wool base of greasy wool by near infrared reflectance spectroscopy. Textile Research Journal 53: 651–655.CrossRefGoogle Scholar
Connell, J. P. and Brown, O. H. 1978. The yield testing of wool by reflectance spectroscopy. Journal of Textile Institute 69: 357–363.CrossRefGoogle Scholar
Cowe, I. A. and McNicol, J. W. 1985. The use of principal components in the analysis of near infrared spectra. Applied Spectroscopy 39: 257–265.CrossRefGoogle Scholar
Dahm, D. J. and Dahm, K. D. 2001. The physics of near infrared scattering. In Near infrared technology in the agricultural and food industries (ed. Williams, P. C. and Norris, K. H.), pp. 1–19. American Association of Cereal Chemists, St Paul, Minnesota.Google Scholar
Deaville, E. R. and Flinn, P. C. 2000. Near infrared (NIR. spectroscopy: an alternative approach for the estimation of forage quality and voluntary intake. In Forage evaluation in ruminant nutrition (ed. Givens, D. I. Owen, E., Axford, R. F. E. and Omed, H. M.), pp. 301–320. CABI Publishing, Wallingford.CrossRefGoogle Scholar
Fearn, T. 2002. Assessing calibrations: SEP, RPD, RER and R 2. NIR News 13: 12–14.CrossRefGoogle Scholar
Hammersley, M. J. 1992. NIR analysis of wool. In Handbook of near-infrared analysis (ed. Burns, D. A. and Ciurczak, E. W.), pp.475–494. Marcel Dekker Inc., New York.Google Scholar
Hammersley, M. J. and Townsend, P. E. 1994. Exploiting the shorter wavelengths: wool measurements including colour. In Leaping ahead with near infrared spectroscopy (ed. Batten, G. D., Flinn, P. C., Welsh, L. A. and Blakeney, A. B.), pp. 465–469. Royal Australian Chemical Institute, Melbourne, Australia.Google Scholar
Hammersley, M. J. and Townsend, P. E. 2004. Applications in the analysis of wool. In Near infrared spectroscopy in agriculture (ed. Roberts, C. A., Workman, J., and Reeves, J. B.) agronomy monograph no. 44, pp. 663–671. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America.Google Scholar
Hammersley, M. J., Townsend, P. E., Graystone, G. F. and Ranford, S. L. 1995. Visible/near infrared spectroscopy of scoured wool. Textile Research Journal 65: 241–246.CrossRefGoogle Scholar
Hruschka, W. R. 1992. Spectral reconstruction. In Handbook of near-infrared analysis (ed. Burns, D. A. and Ciurczak, E. W.), pp. 365–383. Marcel Dekker Inc., New York.Google Scholar
Larsen, S. A. and Kinnison, J. L. 1982. Estimating quality components of natural . bres by near infrared reflectance. Clean wool base and average wool fibre diameter. Textile Research Journal 52: 25–31.CrossRefGoogle Scholar
Martens, H. and Naes, T. 1989. Multivariate calibration. John Wiley and Sons Ltd, New York.Google Scholar
Miller, Ch. E. 2001. Chemical principles of near infrared technology. In Near infrared technology in the agricultural and food industries (ed. Williams, P. C. and Norris, K. H.), pp. 19–37. American Association of Cereal Chemists, St Paul, Minnesota.Google Scholar
Murray, I. 1986. The NIR spectra of homologous series of organic compounds. In NIR/NIT conference (ed. Hollo, J., Kaffka, K. J. and Gonczy, J. L.), pp. 13–28. Akademiai Kiado, Budapest.Google Scholar
Murray, I. 1993. Forage analysis by near infrared spectroscopy. In Sward herbage measurement handbook (ed. Davies, A., Baker, R. D., Grant, S. A. and Laidlaw, A. S.), pp. 285–312. British Grassland Society, Maidenhead.Google Scholar
Naes, T., Isaksson, T., Fearn, T. and Davies, T. 2002. A user-friendly guide to multivariate calibration and classification. NIR Publications, ChichesterGoogle Scholar
NIRS 2. 1995. Routine operation and calibration software for near infrared instruments. Perstorp Analytical, Silver Spring, MD.Google Scholar
Osborne, B. G., Fearn, T. and Hindle, P. H. 1993. Near infrared spectroscopy in food analysis, second edition. Longman Scientific and Technical, Harlow.Google Scholar
Slack-Smith, T., Fong, D. and Douglas, S. A. S. 1979. The potential application of near infra red re. ectance to estimate the alcohol extractable matter content of scoured wool. Journal of Textile Institute 70: 1.CrossRefGoogle Scholar
Sommerville, P. 2002. Fundamental principles of fibre fineness measurements. In Technologies for measuring the fineness of wool fibres. Part 3. Australian Wool Testing Authority Ltd, pp.1–5.Google Scholar
Stryer, L. 1995. Biochemistry, fourth edition. Stanford University, W. H. Freeman and Co., New York.Google Scholar
The Unscrambler. 1996. User's guide, version 60. CAMO AS, Trondheim, Norway.Google Scholar
Williams, P. C. 2001. Implementation of near infrared technology. In Near infrared technology in the agricultural and food industries (ed. Williams, P. C. and Norris, K. H.), pp. 145–171. American Association of Cereal Chemists, St Paul, Minnesota.Google Scholar
Woodhead, A. L., Harrigan, F. J. and Church, J. S. 1997. Assessment of wool chlorination by infrared spectroscopy. II. The chemometric approach. Vibrational Spectroscopy 115: 179–189.CrossRefGoogle Scholar