DOI QR코드

DOI QR Code

Development and Evaluation of a Simulation Model for Dairy Cattle Production Systems Integrated with Forage Crop Production

  • Kikuhara, K. (Laboratory of Animal Husbandry Resources, Graduate School of Agriculture Kyoto University) ;
  • Kumagai, H. (Laboratory of Animal Husbandry Resources, Graduate School of Agriculture Kyoto University) ;
  • Hirooka, H. (Laboratory of Animal Husbandry Resources, Graduate School of Agriculture Kyoto University)
  • 투고 : 2008.02.08
  • 심사 : 2008.09.13
  • 발행 : 2009.01.01

초록

Crop-livestock mixed farming systems depend on the efficiency with which nutrients are conserved and recycled. Home-grown forage is used as animal feed and animal excretions are applied to cultivated crop lands as manure. The objective of this study was to develop a mixed farming system model for dairy cattle in Japan. The model consisted of four sub-models: the nutrient requirement model, based on the Japanese Feeding Standards to determine requirements for energy, crude protein, dry matter intake, calcium, phosphorus and vitamin A; the optimum diet formulation model for determining the optimum diets that satisfy nutrient requirements at lowest cost, using linear programming; the herd dynamic model to calculate the numbers of cows in each reproductive cycle; and the whole farm optimization model to evaluate whole farm management from economic and environmental viewpoints and to optimize strategies for the target farm or system. To examine the model' validity, its predictions were compared against best practices for dairy farm management. Sensitivity analyses indicated that higher yielding cows lead to better economic results but higher emvironmental load in dairy cattle systems integrated with forage crop production.

키워드

참고문헌

  1. ARC. 1980. The nutrient requirements of ruminant livestock. 2nd Ed. Commonwealth Agricultural Bureaux, Slough, UK
  2. AFRC. 1993. Energy and protein requirements of ruminants. CAB International, Wallingford, UK
  3. Berentsen, P. B. M. 2003. Effects of animal productivity on the costs of complying with environmental legislation in Dutch dairy farming. Livest. Prod. Sci. 84:183-194 https://doi.org/10.1016/j.livprodsci.2003.09.007
  4. Berentsen, P. B. M. and G. W. J. Giesen. 1995. An environmentaleconomic model at farm level to analyze institutional and technical change in dairy farming. Agric. Syst. 49:153-175 https://doi.org/10.1016/0308-521X(94)00042-P
  5. Berentsen, P. B. M. and M. Tiessink. 2003. Potential effects of accumulating environmental policies on Dutch dairy farms. J. Dairy Sci. 86:1019-1028 https://doi.org/10.3168/jds.S0022-0302(03)73685-6
  6. Berntsen, J., B. M. Petersen, B. H. Jacobsen, J. E. Olesen and N. J. Hutchings. 2003. Evaluating nitrogen taxation scenarios using the dynamic whole farm simulation model FASSET. Agric. Syst. 76:817-839 https://doi.org/10.1016/S0308-521X(02)00111-7
  7. Brody, S. 1945. Bioenergetics and growth. Reinhold Publishing, New York
  8. Dent, J. B. and M. J. Blackie. 1979. System simulation in agriculture. Applied Science Publishers Ltd., London
  9. Devendra, C. 2007. Perspectives on animal production systems in Asia. Livest. Sci. 106:1-18 https://doi.org/10.1016/j.livsci.2006.05.005
  10. Devendra, C. and D. Thomas. 2002. Crop-animal interactions in mixed farming systems in Asia. Agric. Syst. 71:27-40 https://doi.org/10.1016/S0308-521X(01)00034-8
  11. Ghebremichael, L. T., P. E. Cerosaletti, T. L. Veith, C. A. Rotz, J. M. Hamlett and W. J. Gburek. 2007. Economic and phosphorus-related effects of precision feeding and forage management at a farm scale. J. Dairy Sci. 90:3700-3715 https://doi.org/10.3168/jds.2006-836
  12. Groen, A. F. 1988. Derivation of economic values in cattle breeding: A model at farm level. Agric. Syst. 27:195-213 https://doi.org/10.1016/0308-521X(88)90057-1
  13. Henry, G. M., M. A. Delorenzo, D. K. Beede, H. H. Van Horn, C. B. Moss and W. G. Boggess. 1995. Determining optimal nutrient management strategies for dairy farms. J. Dairy Sci. 78:693-703 https://doi.org/10.3168/jds.S0022-0302(95)76681-4
  14. Herrero, M., R. H. Fawcett and J. B. Dent. 1999. Bio-economic evaluation of dairy farm management scenarios using integrated simulation and multiple-criteria models. Agric Syst. 62:169-188 https://doi.org/10.1016/S0308-521X(99)00063-3
  15. Hirooka, H. 1992. A comparison of two mathematical model of the lactation curve in dairy cattle. Jpn. J. Biomet. 13:15-24 (in Japanese) https://doi.org/10.5691/jjb.13.15
  16. Hirooka, H., A. F. Groen and J. Hillers. 1998. Developing breeding objectives for beef cattle production. 1. A bioeconomic simulation model. Anim. Sci. 66:607-621 https://doi.org/10.1017/S1357729800009188
  17. Janssen, S. and M. K. Van Ittersum. 2007. Assessing farm innovations and responses to policies: a review of bioeconomic farm models. Agric. Syst. 94:622-636 https://doi.org/10.1016/j.agsy.2007.03.001
  18. JDC. 2002. Trend livestock management. Japanese Dairy Council, Tokyo, Japan (in Japanese)
  19. JLIA. 1990. Guideline for management improvement of grasslanddependent dairy management. Japan Livestock Industry Association, Tokyo, Japan (in Japanese)
  20. Kahn, H. E. 1982. The developing of a simulation model and its use in the evaluation of cattle production systems. Ph.D. Thesis. University of Reading
  21. Kikuhara, K. and H. Hirooka. 2008. Application of a simulation model for dairy cattle production systems integrated with forage crop production: the effects of whole crop rice silage utilization on nutrient balance and profitability. Asian-Aust. J. Anim. Sci. 22(2):216-224
  22. Koenen, E. P. C., P. B. M. Berentsen and A. F. Groen. 2000. Economic values of live weight and feed-intake capacity of dairy cattle under Dutch production circumstances. Livest. Prod. Sci. 66:235-250 https://doi.org/10.1016/S0301-6226(00)00167-6
  23. LIAJ. 2007. Distribution of testing cows by parity. 2005. Livestock Improvement Association of Japan (in Japanese). Available from: http://liaj.lin.go.jp/japanese/kentei/ke0532.html. Accessed 15 October 2007
  24. MAFF. 1999. Japanese feeding standard for dairy cattle. 1999. Agriculture, Forestry and Fisheries Research Council Secretariat, Ministry of Agriculture, Forestry and Fisheries, Japan Livestock Industry Association, Tokyo, Japan (in Japanese)
  25. MAFF. 2005a. Survey statistics on prices in agriculture. Ministry of Agriculture, Forestry, and Fisheries, Association of Agriculture and Forestry Statistics, Tokyo, Japan (in Japanese)
  26. MAFF. 2005b. Basic plan for modernization of dairy and beef cattle production. Ministry of Agriculture, Forestry, and Fisheries, Tokyo, Japan (in Japanese). Available from:http://www.maff.go.jp/lin/pdf/03-01rakuniku.pdf. Accessed 5 October 2007
  27. MAFF. 2005c. Production costs of animal products. Ministry of Agriculture, Forestry, and Fisheries, Tokyo, Japan (in Japanese). Available from: http://www.tdb.maff.go.jp/toukei/a02smenu4TokID=E009&TokKbn=B&TokID1=E00 9B2004-002&TokID2=E009B2004-002-005&TokID3=E009B2004-002-005-001#TOP. Accessed 21 October 2007
  28. MAFF and NARO. 2004. Quality assessment and application manual for livestock manure. Association of Agriculture, Forestry, and Fisheries Research Council, Tokyo, Japan and National Agricultural Research Organization, Tokyo, Japan (in Japanese)
  29. NARO. 2001. Standard tables of feed composition in Japan. 2001. National Agricultural Research Organization, Tokyo, Japan (in Japanese)
  30. National Research Council. 2001. Nutrient requirements of dairy cattle. 7th Rev. Ed. National Academy Press, Washington, DC
  31. Rotz, C. A., D. R. Mertens, D. R. Buckmaster, M. S. Allen and J. H. Harrison. 1999a. A dairy herd model for use in whole farm simulations. J. Dairy Sci. 82:2826-2840 https://doi.org/10.3168/jds.S0022-0302(99)75541-4
  32. Rotz, C. A., L. D. Satter, D. R. Mertens and R. E. Muck. 1999b. Feeding strategy, nitrogen cycling, and profitability of dairy farms. J. Dairy Sci. 82:2841-2855 https://doi.org/10.3168/jds.S0022-0302(99)75542-6
  33. Rotz, C. A. and C. U. Coiner. 2006. Integrated farm system model (IFSM): Reference manual version 2.0. USDA Agricultural Research service, University Park, PA. Available from:http://www.ars.usda.gov/Main/docs.htm?docid=8519. Accessed 13 February 2007
  34. Rotz, C. A., A. N. Sharpley, L. D. Shatter, W. J. Gburek and M. A. Sanderson. 2002. Production and feeding strategies for phosphorus management on dairy farms. J. Dairy Sci. 85:3142-3153 https://doi.org/10.3168/jds.S0022-0302(02)74402-0
  35. Rotz, C. A., D. L. Zartman and K. L. Crandall. 2005. Economic and environmental feasibility of a perennial cow dairy farm. J. Dairy Sci. 88:3009-3019 https://doi.org/10.3168/jds.S0022-0302(05)72981-7
  36. Sanders, J. O. and T. C. Cartwright. 1979a. A general cattle production systems model I: Structure of the model. Agric. Syst. 4:217-227 https://doi.org/10.1016/0308-521X(79)90031-3
  37. Sanders, J. O. and T. C. Cartwright. 1979b. A general cattle production systems model. Part 2-Procedures used for simulation animal performance. Agric. Syst. 4:289-302 https://doi.org/10.1016/0308-521X(79)90004-0
  38. Soder, K. J. and C. A. Rotz. 2001, Economic and environmental impact of four levels of concentrate supplementation in grazing dairy herds. J. Dairy Sci. 84:2560-2572 https://doi.org/10.3168/jds.S0022-0302(01)74709-1
  39. Steverink, M. H. A., A. F. Groen and P. B. M. Berentsen. 1994. The influence of environmental policies for dairy farms on dairy cattle breeding goals. Livest. Prod. Sci. 40:251-261 https://doi.org/10.1016/0301-6226(94)90093-0
  40. Tamminga, S. 1992. Nutrition management of dairy cows as a contribution to pollution control. J. Dairy Sci. 75:345-357 https://doi.org/10.3168/jds.S0022-0302(92)77770-4
  41. Tedeschi, L. O., D. G. Fox, L. E. Chase and S. J. Wang. 2000. Whole-herd optimization with the Cornell net carbohydrate and protein system. I. predicting feed biological values for diet optimization with linear programming1. J. Dairy Sci. 83:2139-2148 https://doi.org/10.3168/jds.S0022-0302(00)75097-1
  42. Thornton, P. K. and M. Herrero. 2001. Integrated crop-livestock simulation models for scenario analysis and impact assessment. Agric. Syst. 70:581-602 https://doi.org/10.1016/S0308-521X(01)00060-9
  43. Tsuiki, M. and Y. Harada. 1996. Quantitative estimation of nutrient flow in dairy farms: (1) Nitrogen flow. J. JASS 12(2):113-117 (in Japanese, with English abstract)
  44. Van Calker, K. J., P. B. M. Berentsen, I. M. J. De Boer, G. W. J. Giesen and R. B. M. Huirne. 2004. An LP-model to analyse economic and ecological sustainability on Dutch dairy farms:model presentation and application for experimental farm "de Marke"'. Agric. Syst. 82:139-160 https://doi.org/10.1016/j.agsy.2004.02.001
  45. Wood, P. D. P. 1967. Algebraic model of the lactation curve in cattle. Nature (London) 216:164-165 https://doi.org/10.1038/216164a0

피인용 문헌

  1. Least cost ration formulation with whole crop rice silage for beef cattle feedlot production vol.81, pp.3, 2010, https://doi.org/10.2508/chikusan.81.333
  2. Application of the modified feed formulation to optimize economic and environmental criteria in beef cattle fattening systems with food by-products vol.165, pp.1, 2009, https://doi.org/10.1016/j.anifeedsci.2011.02.015
  3. Stochastic simulation model of Ankole pastoral production system: Model development and evaluation vol.222, pp.20, 2011, https://doi.org/10.1016/j.ecolmodel.2011.08.027
  4. Alternative options for sustainable intensification of smallholder dairy farms in North-West Michoacan, Mexico vol.144, pp.None, 2016, https://doi.org/10.1016/j.agsy.2016.02.001
  5. A fermentation and storage TMR model for dairy cattle vol.12, pp.1, 2009, https://doi.org/10.1016/j.eaef.2018.10.001
  6. Using Mixed Integer Non-Linear Programming to Develop Dairy Farm Simulation Models for Forage Crop Production Scenario Analysis vol.29, pp.4, 2009, https://doi.org/10.3173/air.29.70
  7. Methane emissions from livestock in East Asia during 1961−2019 vol.7, pp.1, 2021, https://doi.org/10.1080/20964129.2021.1918024
  8. Evaluating environmental and economic trade-offs in cattle feed strategies using multiobjective optimization vol.195, pp.None, 2009, https://doi.org/10.1016/j.agsy.2021.103308