View More View Less
  • 1 Faculty of Agriculture, University of Zagreb Svetosimunska cesta 25, 10000 Zagreb, Croatia
  • 2 Faculty of Agriculture, University of Zagreb Svetosimunska cesta 25, 10000 Zagreb, Croatia
  • 3 Faculty of Food Science, Corvinus University of Budapest Ménesi út 45, H-1118 Budapest, Hungary
  • 4 Faculty of Agriculture, University of Zagreb Svetosimunska cesta 25, 10000 Zagreb, Croatia
  • 5 Faculty of Agriculture, University of Zagreb Svetosimunska cesta 25, 10000 Zagreb, Croatia
  • 6 Faculty of Agriculture, University of Zagreb Svetosimunska cesta 25, 10000 Zagreb, Croatia
Restricted access

Purchase article

USD  $25.00

1 year subscription (Individual Only)

USD  $173.00

Intensive livestock feeding requires constant monitoring of diet composition to ensure a consistent level of milk or meat production. A rapid analysis of fresh grass silage samples for dry matter (DM) and crude protein (CP) content would provide basic, rapid information what would permit decision to be made regarding the need to supplement the diet. The aim of the present study was to determine dry matter (DM) and crude protein (CP) content in fresh grass silage samples by NIR spectroscopy. Crude protein content can be expressed as g per kg dry matter (g kg-1 DM) or as per cent of fresh weight (% FW). Near-infrared reflectance spectra were recorded for 103 fresh grass silage samples. Laboratory analysis of DM and CP were determined for these samples. MLR, PCR and PLS techniques were used for data modelling to determine the optimum models for predicting each of the chemical constituents. It was concluded that the PLS method was superior to the PCR and MLR methods for DM and CP prediction in fresh grass silage samples, while MLR showed a promising possibility to determine the CP content using only two spectral values measured at two “characteristic”wavelengths.

  • Barber, G. D., Givens, D. I., Kridis, M. S., Offer, N. W., Murray, I. (1990) Prediction of the organic matter digestibility of grass silage. Animal Feed Science and Technology 28: 115-128.

    'Prediction of the organic matter digestibility of grass silage. ' () 28 Animal Feed Science and Technology : 115 -128.

    • Search Google Scholar
  • Blanco, M., Coello, J., Iturriaga, H., Maspoch, S., Gonzalez, R. (1998) Determination of water in lubricating oils by mid- and near-infrared spectroscopy. Microchim. Acta 128: 235.

    'Determination of water in lubricating oils by mid- and near-infrared spectroscopy. ' () 128 Microchim. Acta : 235.

    • Search Google Scholar
  • Castle, M. E., Retter, W. C., Watson, J. N. (1980) Silage and milk production: a comparison between three grass silages of different digestibilities. Grass and Forage Science 35: 219-225.

    'Silage and milk production: a comparison between three grass silages of different digestibilities. ' () 35 Grass and Forage Science : 219 -225.

    • Search Google Scholar
  • Gordon, F. J., Murdoch, J. C. (1978) An evaluation of a high-quality grass silage for milk production. Journal of the British Grassland Society 33: 5-11.

    'An evaluation of a high-quality grass silage for milk production. ' () 33 Journal of the British Grassland Society : 5 -11.

    • Search Google Scholar
  • Marten, G. C., Halgerson, J. L., Cherney, J. H. (1983): Quality prediction of small grain forage by near infrared reflectance spectroscopy. Crop Science 23: 94-96.

    ': Quality prediction of small grain forage by near infrared reflectance spectroscopy. ' () 23 Crop Science : 94 -96.

    • Search Google Scholar
  • McKee, C. A., Cushnahan, A., Mayne, C. S., Unsworth, E. F. (1996) The effect of partial replacement of grass silage with fresh grass on rumen fermentation characteristics and rumen outflow rates in cattle. Grass and Forage Science 51: 32-41.

    'The effect of partial replacement of grass silage with fresh grass on rumen fermentation characteristics and rumen outflow rates in cattle. ' () 51 Grass and Forage Science : 32 -41.

    • Search Google Scholar
  • Murray, I. (1986) Near infrared reflectance analysis of forages. In: Haresign, W., Cole, D. J. A. (eds) Recent Advances in Animal Nutrition. London: Butterworths.

    Recent Advances in Animal Nutrition , ().

  • Norris, K. H., Barnes, R. F., Moore, J. E., Shenk, J. S. (1976) Predicting forage quality by infrared reflectance spectroscopy. Journal of Animal Science 43: 889-897.

    'Predicting forage quality by infrared reflectance spectroscopy. ' () 43 Journal of Animal Science : 889 -897.

    • Search Google Scholar
  • Redshaw, E. S., Mathison, G. W., Milligan, L. P., Weisenburger, R. D. (1986) Near infrared reflectance spectroscopy for predicting forage composition and voluntary consumption and digestibility in cattle and sheep. Canadian Journal of Animal Science 66:103-115.

    'Near infrared reflectance spectroscopy for predicting forage composition and voluntary consumption and digestibility in cattle and sheep. ' () 66 Canadian Journal of Animal Science : 103 -115.

    • Search Google Scholar
  • Rosental, B., Williams, P. (1996) The Future waves. In: Davies, A. M. C., Williams, P. (eds) Near Infrared Spectroscopy. NIR Publications, Chichester, UK, 1.

    Near Infrared Spectroscopy , () 1.

  • SAS (1999) SAS® Software, SAS Institute Inc., Cary, North Carolina, USA.

  • Steen, R. W. J., Gordon, F. J., Mayne, C. S., Poots, R. E., Kilpatrick, D. J., Unsworth, E. F., Barnes, B. J., Porter, M. G., Pippard, C. J. (1995) Prediction of the intake of grass silage by cattle. Recent Advances in Animal Nutrition 4: 67-89.

    'Prediction of the intake of grass silage by cattle. ' () 4 Recent Advances in Animal Nutrition : 67 -89.

    • Search Google Scholar
  • Wilman, D., Field, M., Lister, S. J., Givens, D. I. (2000) The use of near infrared spectroscopy to investigate the composition of silages and the rate and extent of cell-wall degradation. Animal Feed Science and Technology 88:139-151.

    'The use of near infrared spectroscopy to investigate the composition of silages and the rate and extent of cell-wall degradation. ' () 88 Animal Feed Science and Technology : 139 -151.

    • Search Google Scholar
  • Windham, W. R., Flinn, P. C. (1992) Bridging the gap between data analysis and NIR applications. In: Hildrum, K. I., Isaksson, T., Naes, T., Tandberg, A. (eds) Near Infrared Spectroscopy. Chichester, UK: Ellis Horwood, 459.

    Near Infrared Spectroscopy , () 459.

  • Cushnahan, A., Mayne, C. S., Goodall, E. A. (1996) Effects of stage of maturity and period of ensilage on the production and utilization of grass silage by dairy cows. In: Jones, D. I. H., Jones, R., Dewhurst, R., Merry, R., Heigh, P. M. (eds) Proceedings of Eleventh International Silage Conference,, IGER, Aberystwyth, 78-79.

    , , .

    • Search Google Scholar
  • Flinn, P. C., Murray, I. (1987) Potential of near infrared reflectance spectroscopy (NIR) for evaluation of herbage quality in Southern Australia. In: Wheeler, J. L., Pearson, C. J., Robards, G. E. (eds) Temperate Pastures, Their Production, Use and Management. Australia: CSIRO.

    Temperate Pastures, Their Production, Use and Management , ().

  • Steen, R. W. J., Gordon, F. J., Dawson, L. E. R., Park, R. S., Mayne, C. S., Agnew, R. E., Kilpatrick, D. J., Porter, M. G. (1998) Factors affecting intake of grass silage by cattle and prediction of silage intake. Animal Science 66: 115-128.

    'Factors affecting intake of grass silage by cattle and prediction of silage intake. ' () 66 Animal Science : 115 -128.

    • Search Google Scholar
  • Stimson, C., Kellaway, R. C., Tassell, R. J., Ison, R. L. (1991) Prediction of the nutrient content of botanical fractions from annual legumes by near infrared reflectance spectroscopy. Grass and Forage Science 46: 99-105.

    'Prediction of the nutrient content of botanical fractions from annual legumes by near infrared reflectance spectroscopy. ' () 46 Grass and Forage Science : 99 -105.

    • Search Google Scholar

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Oct 2020 0 0 0
Nov 2020 0 0 0
Dec 2020 1 3 4
Jan 2021 0 0 0
Feb 2021 1 0 0
Mar 2021 0 0 0
Apr 2021 1 0 0