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

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.

• Mikhailenko I.M.

• Искусство. Декоративно-прикладное искусство. Фотография. Музыка. Игры. Спорт

• Естественные науки
• Сельское хозяйство. Лесоводство