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Systematic approach to evaluation of sires progeny using information technology

https://doi.org/10.32634/0869-8155-2020-340-7-39-43

Abstract

Relevance.  In the Republic of Kazakhstan, mainly 4 breeds of dairy cattle are bred: Holstein black-motley, Black-motley, Simmental and Alatau. The article reflects the results of studies that give reason to conduct effective breeding to provide the breeding stock with seed of bulls producing their own reproduction. Calculations showed that for this it is necessary to receive at least 265 repair bullcalves annually, of which 17 should be the fathers of the future generation. The rationale for the minimum requirements for the mothers of future bulls is given. Effective schemes for assessing repair bull-calves on the quality of offspring and a removal procedure using information technology are proposed.

Methodology. Scientific research was carried out according to generally accepted, zootechnical methods, using statistical models in Excel.

Results. As a result of scientific research, it was found that to ensure the breeding of the uterine livestock of 4 main breeds of the Kazakhstan population; at least 17 improvement bulls are required annually. For this purpose, a schematic diagram of the reproduction of dairy cattle was developed. From the obtained materials of the information-analytical system, scientifically-based productivity parameters for bull-producing groups of cows were calculated. A scheme has been developed for removing bulls from an assessment of the quality of offspring using information technology. 

About the Authors

T. N. Karymsakov
LLP Kazakh Scientific Research Institute of Animal Husbandry and Forage Production
Kazakhstan

Talagat N. Karymsakov

51, Zhandosov  str., Almaty



D. A. Baimukanov
LLP Kazakh Scientific Research Institute of Animal Husbandry and Forage Production
Kazakhstan

Dastanbek A. Baimukanov

51, Zhandosov  str., Almaty



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For citations:


Karymsakov T.N., Baimukanov D.A. Systematic approach to evaluation of sires progeny using information technology. Agrarian science. 2020;(7-8):39-43. (In Russ.) https://doi.org/10.32634/0869-8155-2020-340-7-39-43

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ISSN 0869-8155 (Print)
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