Sel’skokhozyaistvennaya Biologiya [Agricultural Biology], 2015, V. 50, № 4, pp. 467-475.

UDC 636/639:636.2.034:51-76

doi: 10.15389/agrobiology.2015.4.467eng

NEW PROBABILISTIC STATISTICAL AND DYNAMIC MODELS
TO CONTROL LIFE CYCLE IN LACTING COWS

I.M. Mikhailenko

Agrophysical Research Institute, Federal Agency of Scientific Organizations, 14, Grazhdansky prosp., St. Petersburg, 195220 Russia,
e-mail IMikhailenko@agrophys.ru

Received August 28, 2014

Reproduction in dairy herds recently has become increasingly important. The tendency to its reduction occurs everywhere in all countries with a developed dairy husbandry. On average, the number of lactations per cow is diminishing and now close to 3 while a genetic potential of many cattle breeds is over 10 lactations. To resolve this issue, a theoretical base should be developed using latest progress in various related sciences. The aim of the present study is the first theoretical justification for a key stage of the general concept of lactating cows’ health management, proposed in our previous paper (I.M. Mikhailenko, 2014). Herein we suggest an approach to programming cow’s life cycle from the first to the last economically reasonable lactation. As a result, the risk of animal culling and unnecessary costs are minimized. The problem is solved for the first time in biological science. Our theory is based on developed dynamic and probabilistic statistical models. At its core, this approach provides a science-based standard of animal feeding for optimized lactation during life cycle. The dynamic models for lifetime annual yields reflect animal age and nutrient intake with diet, and the probabilistic statistical modeling, used to control cows’ culling due to ill health and diseases, is the most important feature of the developed approach to life-cycle control. All physiological states, from a heifer to the last lactation, are considered, and all the flows within the dairy herd and possible causes for culling are identified. These mathematical models allow assessing the risk of possible livestock losses, which are minimized due to optimized annual diet. The developed algorithm allows to specify adjustments in annual feeding rations during the cow’s life cycle (the feeding strategies for dairy cattle), which ensure optimal reproduction rate, optimal number of possible lactation per cow and optimal annual yields. Thus, the use of a lactating cow is normalized resulting in healthy livestock and maximized profitability of milk production. Since the individual approach to cows’ feeding is a substantial reserve for increasing profitability of a dairy herd as a whole, the task of life cycle control is regarded at two levels, for an individual and for the herd on average. For a particular herd, the choice to one of the levels depends on whether there are the means to provide individual health control and dosing concentrated feed and food additives. Practically, the use of proposed mathematical models is mainly limited by lack of long-term (10-12 years) surveys of animal health as depended on the actual diet, since these data are necessary for identification and validation of the algorithms, but an experimental model such as 100-150 cows’ dairy farm, equipped with systems for health monitoring and feed composition control, could improve the situation.

Keywords: dairy husbandry, reproduction, concept of lactating cows’ health control, health, life cycle, lactation period, control algorithms, mathematical modeling.

 

Full article (Rus)

Full text (Eng)

 

REFERENCES

  1. Ferris T.A., Mao I.L., Anderson C.R. Selecting for lactation curve and milk yield in dairy cattle. J. Dairy Sci., 1985, 68: 1438-1448 CrossRef
  2. Oltenacu P.A., Rousaville T.R., Milligan R.A., Foote R.H. System analysis for designing reproductive management programs to increase production and profit in dairy herds. J. Dairy Sci., 1981, 64: 2096-2104 CrossRef
  3. Haile-Mariam M., Goddard M.E. Genetic and phenotypic parameters of lactations longer than 305 days (extended lactations). Animal, 2008, 2: 325-335 CrossRef
  4. Kirkpatrick M., Lofsvold D., Bulmer M. Analysis of the inheritance, selection and evolution of growth trajectories. Genetics, 1990, 124: 979-993.
  5. Meuwissen T.H.E. Optimization of dairy cattle breeding plans with increased female reproductive rates. Thesis. Research Institute for Animal Production «Schoonoord», Wageningen, 1990.
  6. Oltenacu P.A., Rousaville T.R., Milligan R.A., Foote R.H. System analysis for designing reproductive management programs to increase production and profit in dairy herds. J. Dairy Sci., 1981, 64: 2096-2104 CrossRef
  7. Vargas B., Koops W.J., Herrero M., Van Arendonk J.A. Modeling extended lactations of dairy cows. J. Dairy Sci., 2000, 83: 1371-1380 CrossRef
  8. Mikhailenko I.M. V knige: Tochnoe sel'skoe khozyaistvo (Precision Agriculture) [Precision agriculture]. St. Petersburg, 2010: 321-336.
  9. Trofimov A.A., Chugin I.V. Modeling turnover herds of cattle and optimal planning of the production of farms. In: Simulation of innovation processes and economic dynamics. Moscow, 2006: 212-225.
  10. Spravochnik po veterinarnoi meditsine /Pod redaktsiei A.F. Kuznetsova [Handbook on veterinary medicine. A.F. Kuznetsov (ed.).]. St. Petersburg, 2004.
  11. Mikhailenko I.M. Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2014, 2: 50-58 CrossRef, CrossRef
  12. Dijkstra J., Lopez S., Bannink A., Dhanoa M.S., Kebreab E., Odongo N.E., Fathi Nasri M.H., Behera U.K., Hernandez-Ferrer D., France J. Evaluation of a mechanistic lactation model using cow, goat and sheep data. J. Agr. Sci., 2010, 148: 249-262 CrossRef
  13. Grossman M., Koops W.J. Modeling extended lactation curves of dairy cattle: a biological basis for the multiphasic approach. J. Dairy Sci., 2003, 86: 988-998 CrossRef
  14. Jaffrezic F., White I.M.S., Thompson R., Hill W.G. A link function approach to model heterogeneity of residual variances over time in lactation curve analyses. J. Dairy Sci., 2000, 83: 1089-1093 CrossRef
  15. Macciotta N.P.P., Dimauro C., Steri R., Cappio-Borlino A. Mathematical modelling of goat lactation curves. In: Dairy goats feeding and nutrition /A. Cannas, G. Pulina (eds.). CAB International, Wallingford, UK, 2008: 31-46.
  16. Congleton W.R. Jr. Dynamic model for combined simulation of dairy management strategies. J. Dairy Sci., 1984, 67: 644-660 CrossRef
  17. Dijkhuizen A.A., Stelwagen J., Renkema J.A. A stochastic model for the simulation of management decisions in dairy herds, with special reference to production, reproduction, culling and income. Prev. Vet. Med., 1986, 4: 274-289 CrossRef
  18. Guo Q., White R.E. Cubic spline regression for the open-circuit potential curves of a lithium-ion battery. J. Electrochem. Soc., 2005, 152: A343-A350 CrossRef
  19. Leon-Velarde C.U. A simulation model to analyze the bio-economic function of cows in intensive dairy farms using a systems approach. Thesis Ph.D. University of Guelph, 1991.
  20. Mayer D.G., Belward J.A., Burrage K. Use of advanced techniques to optimize a multidimensional dairy model. Agricultural Systems, 1996, 50: 239-253.
  21. Oltenacu P.A., Milligan R.A., Rounsaville T.R., Foote R.H. Modelling reproduction in a herd of dairy cattle. Agricultural Systems, 1980, 8: 193-205.
  22. Quiroz R., Arce B., Cañas R. Aguilar C. Development and use of simulation models in animal production.systems research. In: Animal production system research; methodological and analytical guidelines. IDRC/IICA-RISPAL; San José, C.R., 1994: 103-149.
  23. Wilson D.J., González R.N., Hertl J., Schulte H.F., Bennet G.J., Schukken Y.H., Gröhn Y.T. Effect of clinical mastitis on the lactation curve: a mixed model estimation using daily milk weights. J. Dairy Sci., 2004, 87: 2073-2084 CrossRef
  24. White I.M.S., Thompson R., Brotherstone S. Genetic and environmental smoothing of lactation curves with cubic splines. J. Dairy Sci., 1999, 82: 632-638 CrossRef
  25. Wang Z., Goonewardene L.A. The use of MIXED models in the analysis of animal experiments with repeated measures data. Can. J. Anim. Sci., 2004, 84: 1-11 CrossRef
  26. Vetharaniam I., Davis S.R., Upsdell M., Kolver E.S., Pleasants A.B. Modeling the effect of energy status on mammary gland growth and lactation. J. Dairy Sci., 2003, 86: 3148-3156 CrossRef
  27. Sorensen A., Muir D.D., Knight C.H. Extended lactation in dairy cows: effects of milking frequency, calving season and nutrition on lactation persistency and milk quality. J. Dairy Res., 2008, 75: 90-97 CrossRef

back