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Regression models to predict herbage production and digestibility in a non-regular sequence of cuts

Published online by Cambridge University Press:  27 March 2009

P. R. Edelsten  and
A. J. Corrall
P. R. Edelsten
Affiliation:
Grassland Research Institute, Hurley, Berkshire SLQ 5LR, England
A. J. Corrall
Affiliation:
Grassland Research Institute, Hurley, Berkshire SLQ 5LR, England
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Summary

Regression models were constructed to predict the yields and digestibilities of herbage cut in different sequences of harvests.

The yield model used a seasonal production curve modified by the effects of defoliation. Values for the model parameters were obtained by fitting the model to experimental data using a non-linear regression procedure. When these parameters were used, to predict treatment effects in another series of experimental data, good agreement was obtained. The digestibility model incorporated the effect on digestibility time of year, regrowth time and yield.

Using the models to interpolate between the results of cutting experiments, annual yields were shown to increase with the date of first cut and also with the interval between subsequent cuts, whereas the average digestibility of the harvested material ecreased with the date of first cut and with the subsequent cutting interval. Finally, a procedure was devised for combining the two models in order to find an optimum cutting strategy for a hypothetical animal production system.

Type
Research Article
Information
The Journal of Agricultural Science , Volume 92 , Issue 3 , June 1979 , pp. 575 - 585
Copyright
Copyright © Cambridge University Press 1979

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References

REFERENCES

Alberda, Th. & Sibma, L. (1968). Dry matter production and light interception of crop surfaces. 3. Actual production in different years as compared with potential values. Journal of the British Grassland Society 23, 206–215.CrossRefGoogle Scholar
Anslow, R. C. & Green, J. O. (1967). The seasonal growth of pasture grasses. Journal of Agricultural Science, Cambridge 68, 109–122.CrossRefGoogle Scholar
Agricultural Research Council (1965). The nutrient Requirements of Farm Livestock, No. 2, Ruminants. London: Agricultural Research Council.Google Scholar
Bartholomew, P. W. & Chestnutt, D. M. B. (1977). The effect of a wide range of fertilizer nitrogen application rates and defoliation intervals on the dry-matter production, seasonal response to nitrogen, persistence and aspects of chemical composition of perennial ryegrass (Lolium perenne cv. S. 24). Journal of Agricultural Science, Cambridge 88, 711–721.CrossRefGoogle Scholar
Blaxter, K. L. (1974). Metabolizable energy and feeding systems for ruminants. Proceedings of the University of Nottingham Nutrition Conference for Feed Manufacturers 7, 3–25.CrossRefGoogle Scholar
Brockington, N. R. (1976). Mathematical modelling of grass growth and production. Ph.D. thesis, University of London.Google Scholar
Brougham, B. W. & Glenday, A. C. (1967). Grass growth in mid-summer: A reinterpretation of published data. Journal of the British Grassland Society 22, 100–105.CrossRefGoogle Scholar
Cole, G. W. (1976). ELM version 2.0. Range Science Department, Science Series No. 20 Colorado State University.Google Scholar
Collins, D. P. & McCarrick, B. B. (1969). Effect of time and frequency of cutting on total and seasonal production of herbage. Irish Journal of Agricultural Research 8, 29–40.Google Scholar
Corrall, A. J. (1974). The effect of interruption of flower development on the yield and quality of perennial ryegrass. Vaxtodling 29, 39–43.Google Scholar
Corrall, A. J. & Fenlon, J. S. (1978). A comparative method for describing the seasonal distribution of production from grasses. Journal of Agricultural Science, Cambridge 91, 61–67.CrossRefGoogle Scholar
Edelsten, P. B. (1977). Bio-economic models of sheep systems. Ph.D. thesis, University of Beading.Google Scholar
Green, J. O., Corrall, A. J. & Terry, B. A. (1971). Grass species and varieties: Relationships between stage of growth, yield and forage quality. Technical Report No. 8, Grassland Research Institute, pp. 81.Google Scholar
Hunt, W. F. (1970). The influence of leaf death on the rate of accumulation of green herbage during pasture regrowth. Journal of Applied Ecology 7, 41–50.CrossRefGoogle Scholar
Leafe, E. L., Stiles, W. & Dickinson, S. E. (1974). Physiological processes influencing the pattern of productivity of the intensively managed grass sward. Proceedings of XIIth International Grassland Congress, Moscow, 1974, vol. 1, part 1, 442–457.Google Scholar
MacLusky, D. S. & Morris, D. W. (1964). Grazing methods, stocking rate and grassland production. Agricultural Progress 39, 97–108.Google Scholar
McBratney, J. & Laidlaw, A. S. (1974). The suitability of various grasses, cutting intervals and nitrogen levels for conservation systems as judged by dry matter production. Forty-seventh Annual Report 1973–1974, Agricultural Research Institute of Northern Ireland, pp. 21–26.Google Scholar
Mcivor, P. J. & Watkins, B. R. (1973). The pattern of defoliation of cocksfoot by grazing sheep. Proceedings of the New Zealand Grassland Society 34, 225–235.Google Scholar
Minson, D. J., Raymond, W. F. & Harris, C. E. (1960). Studies in the digestibility of herbage. VIII. The digestibility of S37 Cocksfoot, S23 Byegrass and S24 Byegrass. Journal of the British Grassland Society 15, 174–180.CrossRefGoogle Scholar
Mood, A. M. & Graybill, F. A. (1963). Introduction to the Theory of Statistics, 2nd ed.New York: McGraw-Hill.Google Scholar
Morley, F. H. W. (1968). Pasture growth curves and grazing management. Australian Journal of Experimental Agriculture and Animal Husbandry 8, 40–45.CrossRefGoogle Scholar
Noy-Meir, I. (1976). Rotational grazing in a continuously growing pasture: a simple model. Agricultural Systems 1, 87–112.CrossRefGoogle Scholar
Osbourn, D. F. (1970). The voluntary intake of forage crops by sheep. Ph.D. thesis, Reading University.Google Scholar
Pohjonen, V. (1975). A dynamic model for determining the optimum cutting schedule of Italian ryegrass. Journal of the Scientific Agricultural Society of Finland 47, 71–137.Google Scholar
Powell, M. J. D. (1968). A Fortran subroutine for solving systems of non-linear algebraic equations. AERE-R.594,1, United Kingdom Atomic Energy Authority, Harwell, Oxfordshire.Google Scholar
Tilley, J. M. A. & Terry, R. A. (1963). A two-stage technique for the in vitro digestion of forage crops. Journal of the British Grassland Society 18, 104–111.CrossRefGoogle Scholar
Voisin, A. (1959). Productivité de l'herbe. Flammarion, Paris.Google Scholar
Wilman, D., Koocheki, A. & Lwoga, A. B. (1976). The effect of interval between harvests and nitrogen application on the proportion and yield of crop fractions and on the digestibility and digestible yield and nitrogen content and yield of two perennial ryegrass varieties in the second harvest year. Journal of Agricultural Science, Cambridge 87, 59–74.CrossRefGoogle Scholar
Woodman, H. E., Norman, D. B. & Bee, J. W. (1929). Nutritive value of pasture. IV. The influence of the intensity of grazing on the yield, composition and nutritive value of pasture herbage (part II). Journal of Agricultural Science, Cambridge 19, 236–263.CrossRefGoogle Scholar