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Description and validation of the Teagasc Lamb Production Model

Author

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  • Bohan, A.
  • Shalloo, L.
  • Malcolm, B.
  • Ho, C.K.M.
  • Creighton, P.
  • Boland, T.M.
  • McHugh, N.

Abstract

A stochastic budgetary simulation model of a sheep farm was developed to investigate the effects of changes in lamb production systems on farm profitability. Model inputs included: land, labour, capital, animal numbers, as well as, input and output prices. Model outputs were simulated on a monthly basis and included: flock sales and purchases, net energy demand, grass supply and demand, lamb growth and slaughtering pattern, as well as, land and labour utilization. Grass growth, ewe and lamb mortality, fertiliser and concentrate price along with lamb and mutton price were all included in the model as stochastic variables. Farm earnings before interest and tax and net profit, both including and excluding owner/operator labour, were calculated from total receipts from lamb, culled animals and wool less variable and fixed costs. Validation of the model was undertaken by comparing the model outputs to real farm data recorded on 20 Irish commercial sheep farms as well as comparing the model outputs to those of three individual Irish commercial sheep farms. The model outputs were similar to the real farm data indicating that the model provides a realistic representation of actual farm performance, output and profit. To demonstrate potential application of the model, two lambing date scenarios were investigated; a mid-season lambing flock, with a mean lambing date of March 1st and an early lambing flock, with a mean lambing date of January 1st. Both lambing date scenarios had the same farm area, overall herbage utilization, pregnancy scanning rate and number of lambs weaned per ewe joined to the ram, but the early lambing flock had a higher stocking rate (13.23ewes/ha versus 9.46ewes/ha for March 1st lambing) which increased due to the higher proportion of concentrate in the total flock diet compared with March 1st lambing. The annual return on investment (ROI) of the mid-season lambing flock was 0.95% with a net profit of €11,045 excluding owner/operator labour and management. The early lambing system produced a ROI of −0.70% and a net profit of −€4862. When owner/operator labour and management cost were included the ROI was −0.38% with net profits of −€5462 for March 1st lambing and a ROI of −2.46% and net profits of −€26,735 for January 1st lambing.

Suggested Citation

  • Bohan, A. & Shalloo, L. & Malcolm, B. & Ho, C.K.M. & Creighton, P. & Boland, T.M. & McHugh, N., 2016. "Description and validation of the Teagasc Lamb Production Model," Agricultural Systems, Elsevier, vol. 148(C), pages 124-134.
    • Handle: RePEc:eee:agisys:v:148:y:2016:i:c:p:124-134
    DOI: 10.1016/j.agsy.2016.07.008
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    1. Jackson, Thomas & Heard, J. & Malcolm, Bill, 2014. "System changes to a lamb farm in south-west Victoria: some pre-experimental modelling," AFBM Journal, Australasian Farm Business Management Network, vol. 11, pages 1-18.
    2. Edelsten, P. R. & Newton, J. E., 1977. "A simulation model of a lowland sheep system," Agricultural Systems, Elsevier, vol. 2(1), pages 17-32, January.
    3. McCarl, Bruce A. & Apland, Jeffrey, 1986. "Validation of Linear Programming Models," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 18(2), pages 155-164, December.
    4. S. S. Isukapalli & A. Roy & P. G. Georgopoulos, 1998. "Stochastic Response Surface Methods (SRSMs) for Uncertainty Propagation: Application to Environmental and Biological Systems," Risk Analysis, John Wiley & Sons, vol. 18(3), pages 351-363, June.
    5. Qureshi, M. E. & Harrison, S. R. & Wegener, M. K., 1999. "Validation of multicriteria analysis models," Agricultural Systems, Elsevier, vol. 62(2), pages 105-116, November.
    6. Cacho, O. J. & Finlayson, J. D. & Bywater, A. C., 1995. "A simulation model of grazing sheep: II. Whole farm model," Agricultural Systems, Elsevier, vol. 48(1), pages 27-50.
    7. Crosson, P. & O'Kiely, P. & O'Mara, F.P. & Wallace, M., 2006. "The development of a mathematical model to investigate Irish beef production systems," Agricultural Systems, Elsevier, vol. 89(2-3), pages 349-370, September.
    8. Cros, M. J. & Duru, M. & Garcia, F. & Martin-Clouaire, R., 2004. "Simulating management strategies: the rotational grazing example," Agricultural Systems, Elsevier, vol. 80(1), pages 23-42, April.
    9. Duncan Knowler, 2002. "A Review of Selected Bioeconomic Models with Environmental Influences in Fisheries," Journal of Bioeconomics, Springer, vol. 4(2), pages 163-181, May.
    10. Finlayson, J. D. & Cacho, O. J. & Bywater, A. C., 1995. "A simulation model of grazing sheep: I. Animal growth and intake," Agricultural Systems, Elsevier, vol. 48(1), pages 1-25.
    11. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    12. White, D. H. & Bowman, P. J. & Morley, F. H. W. & McManus, W. R. & Filan, S. J., 1983. "A simulation model of a breeding ewe flock," Agricultural Systems, Elsevier, vol. 10(3), pages 149-189, March.
    13. Tocker, Jonathon & Malcolm, Bill & Heard, J. & Sinnett, A. & Ho, C. & Behrendt, R., 2013. "Profit, cash, wealth and risk implications of changes to a prime lamb business in south-west Victoria," AFBM Journal, Australasian Farm Business Management Network, vol. 10, pages 1-27.
    14. Gutierrez-Aleman, Nestor & De Boer, A. J. & Hart, R. D., 1986. "A bio-economic model of small-ruminant production in the semi-arid tropics of the Northeast Region of Brazil: Part 1--Model description and components," Agricultural Systems, Elsevier, vol. 19(1), pages 55-66.
    15. Gutierrez-Aleman, Nestor & De Boer, A. J. & Kehrberg, E. W., 1986. "A bio-economic model of small-ruminant production in the semi-arid tropics of the Northeast region of Brazil: Part 2--Linear programming applications and results," Agricultural Systems, Elsevier, vol. 19(3), pages 159-187.
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    2. Villalba, D. & Díez-Unquera, B. & Carrascal, A. & Bernués, A. & Ruiz, R., 2019. "Multi-objective simulation and optimisation of dairy sheep farms: Exploring trade-offs between economic and environmental outcomes," Agricultural Systems, Elsevier, vol. 173(C), pages 107-118.
    3. Kamilaris, C. & Dewhurst, R.J. & Vosough Ahmadi, B. & Crosson, P. & Alexander, P., 2020. "A bio-economic model for cost analysis of alternative management strategies in beef finishing systems," Agricultural Systems, Elsevier, vol. 180(C).
    4. Farrell, L.J. & Kenyon, P.R. & Tozer, P.R. & Ramilan, T. & Cranston, L.M., 2020. "Quantifying sheep enterprise profitability with varying flock replacement rates, lambing rates, and breeding strategies in New Zealand," Agricultural Systems, Elsevier, vol. 184(C).
    5. Farrell, L. & Herron, J. & Pabiou, T. & McHugh, N. & McDermott, K. & Shalloo, L. & O'Brien, D. & Bohan, A., 2022. "Modelling the production, profit, and greenhouse gas emissions of Irish sheep flocks divergent in genetic merit," Agricultural Systems, Elsevier, vol. 201(C).

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