Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-02T22:22:53.933Z Has data issue: false hasContentIssue false

Near infrared reflectance spectroscopy wavelengths for selecting barley for the genotypic feeding value of its straw

Published online by Cambridge University Press:  27 February 2018

A. V. Goodchild
Affiliation:
International Center for Agricultural Research in the Dry Areas, PO Box 5466, Aleppo, Syria
F. J. El Haramein
Affiliation:
International Center for Agricultural Research in the Dry Areas, PO Box 5466, Aleppo, Syria
S. Ceccarelli
Affiliation:
International Center for Agricultural Research in the Dry Areas, PO Box 5466, Aleppo, Syria
E. F. Thomson
Affiliation:
International Center for Agricultural Research in the Dry Areas, PO Box 5466, Aleppo, Syria
Get access

Extract

In the semi-arid parts of west Asia and north Africa, barley straw (Hordeum vulgareL. subsp. vulgare)and cereal stubbles provide between one-quarter and one-half of the metabolizable energy (ME) offered to sheep. In barley straw, voluntary straw dry-matter (DM) intake (VSI) is a good predictor of body weight gain (R2 = 0.85; data of Capper et al., 1989). This varies according to location and year (CV = 0.30 to 0.40) and varies genetically, with an average genotypic CV of 0.07, which can exceed 0.10 in wet years. Genotype X environment interactions in VSI are important (Table 1).

A genetically high VSI is advantageous in cool, wet, favourable growing conditions, when VSI is normally low. In drought conditions, VSI is high, genetically varies relatively little (Table 1) and is less important for the farmer than straw and grain yields. Barley breeders working in drought-prone environments prefer to do most of their selection for yield in dry conditions (Ceccarelli, 1993). Breeders are increasingly selecting for high VSI but wish to focus their testing plots in dry areas. Therefore they need indirect tests that indicate the nutritive value of straw when it is grown in wet environments.

Type
Posters
Copyright
Copyright © British Society of Animal Science 1998

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

Capper, B. S., Thomson, E. F. and Rihawi, S. 1989. Voluntary intake and digestibility of barley straw as influenced by variety and supplementation with either barley grain or cottonseed cake. Animal Feed Science and Technology 26: 105118.Google Scholar
Ceccarelli, S. 1993. Plant breeding technologies relevant to developing countries. In Animal production in developing countries (ed. Gill, M., Owen, E., Pollott, G. E. and Lawrence, T. L. J.), pp. 3746. British Society of Animal Production, occasional publication no. 16.Google Scholar
Falconer, D. S. 1981. Introduction to quantitative genetics, second edition. Longman, Harlow, UK.Google Scholar
Goodchild, A. V., Jaby El-Haramein, F., and Treacher, T. T. 1994. Predicting the voluntary intake of barley straw with near infrared reflectance spectroscopy. Animal Production 58: 455 (abstr.).Google Scholar
Murray, I. 1993. Forage analysis by near infra-red spectroscopy. In Sward measurement handbook (ed. Davies, A., Baker, R. D., Grant, S. A. and Laidlaw, A. S.), pp. 285312. British Grassland Society, Reading, U.K.Google Scholar
NIRSystems, Inc. 1992. NSAS, near infrared spectral analysis software. Perstorp Analytical, Silver Spring, MD, USA.Google Scholar
Statistical Analysis Systems Institute. 1989. SAS/STAT user's guide, version 6, fourth edition.Cary, NC, USA.Google Scholar
Williams, P. C, and Norris, K. 1987. Near infrared technology in the agricultural and food industries, American Association of Cereal Chemists, St Paul, Minnesota, USA. Google Scholar