Matvieiev M. Improvement of methods for assessing the animals' breeding value in dairy farming based on the usage of information databases

Українська версія

Thesis for the degree of Doctor of Philosophy (PhD)

State registration number

0823U100535

Applicant for

Specialization

  • 204 - Технологія виробництва і переробки продукції тваринництва

28-07-2023

Specialized Academic Board

ДФ 26.004.082

National University of Life and Environmental Sciences of Ukraine

Essay

The dissertation is devoted to the improvement of methods of comprehensive assessment of the breeding value of animals based on information from various sources. Studies have established that milk productivity of primiparous cows, which was characterized by such traits as milk yield per standard lactation, protein content, fat content, protein yield, fat yield, and energy-corrected milk (ECM1), was different depending on the farm. Significant positive Pearson correlation coefficient between duration of days open and milk yield for standard lactation were established, which ranged from 0,115 (p≤0,01) to 0,447 (p≤0,001). With increasing milk yield in the studied herds, there was a tendency to deterioration in milk quality, an increase of SCS (somatic cells score) and a decrease in the content of its valuable components (fat and protein). It was established that with an increase of the milk yield of cows by 100 kg per standard lactation, the duration of days open increased by 0,3; 0,7 (р≤0,001); 0.7 (р≤0,01) and 3,2 (р≤0,001) days in ALLC “Agroko”, СС “Vostok”, AС “Kolos” and AC “Molocharske”, respectively. The protein yield had the biggest impact on the duration of days open. The results of the study showed that an increase in protein yield of 100 kg per standard lactation resulted in a significant extension of the duration of days open by 23 and 91.7 days (p≤0.001). The correlation coefficients were established between the duration of the days open and the rump width, the foot angle, udder texture, central ligament, and dairy character which were at the level of -0,093 (р≤0,05), -0,094 (р≤0,05), -0,104 (р≤0,05), - 0,107 (p≤0,01), -0,0139 (p≤0,001) and -0,026 (p≤0,001), respectively. Increasing of angle of the rear legs and of body condition scores caused the growth of duration of days open, as the positive correlation coefficient between these traits was found, which was 0.136 (p≤0.01) and 0.226 (p ≤ 0.001), respectively. The results of the study demonstrated that change of evaluation of rear legs and body condition scores by 1 point led to an increase in duration of days open by 5.9 and 6.9 days, respectively. In studied farms, a significant fluctuation between the productivity traits and the level of reproduction of the daughters of different bulls was observed. It was found that the “sire” factor had a more significant effect on productivity traits and on the content of valuable milk components comparing with duration of days open. An algorithm of artificial neural networks was used to calculate milk productivity for a standard lactation (milk yield, fat content, protein content) based on incomplete data collected during lactation. The most accurate forecast was obtained on the basis of input data with information on the first, second, fifth, eighth and tenth monthly milking record. It was established that the increase in milk yield, protein and fat yield per 1 kg of standard lactation caused an increase in gross margin by 2,58, 213,37 and 63,20 UAH, respectively. Regardless of the costs of the rearing of heifer, the highest income from increased productivity per unit was obtained for the traits of the protein yield and fat yield – 469,72 UAH and 361,67 UAH, respectively. Depending on the costs of the rearing of a heifer (12500 UAH or 48611 UAH) increasing of duration of days open by one day led to a decrease in income from -11,39 to -49,89 UAH, respectively. The use of proposed index for culling cows, which was calculated on the basis of economic weights (on the basis of gross margin), led to an additional profit of 13,567,65 UAH per lactation per cow.

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