Body volume modeling by linear features of the Irmen type cattle
https://doi.org/10.26898/0370-8799-2020-6-12
Abstract
About the Authors
A. F. PetrovRussian Federation
Alexey F. Petrov, Senior Lecturer
160 Dobrolyubova St., Novosibirsk, 630039
E. V. Kamaldinov
Russian Federation
Evgeniy V. Kamaldinov, Doctor of Science in Biology, Associate Professor
Novosibirsk
O. D. Panferova
Russian Federation
Ol'ga D. Panferova, Postgraduate
Novosibirsk
O. V. Efremova
Russian Federation
Ol'ga V. Efremova, Livestock Breeder
Novosibirsk region, Verkh-Irmen village
V. A. Rogozin
Russian Federation
Vitaliy A. Rogozin, Senior Zootechnician
Novosibirsk region, Verkh-Irmen village
References
1. Kamaldinov E.V., Dement'ev V.N., Gart V.V. Applying of information technologies in pedigree pig breeding. Vestnik Novosibirskogo gosudarstvennogo agrarnogo universiteta = Bulletin of Novosibirsk State Agrarian University, 2012, vol. 22, no. 1, pp. 50–54. (In Russian).
2. Marinchenko T.E. Digitalization as a driver of development of domestic animal breeding. IOP Conference Series: Materials Science and Engineering, 2020, vol. 873, p. 012004. DOI: 10.1088/1757-899X/873/1/012004.
3. Katkov K., Skorykh L.N., Pashtetsky V.S., Pashtetsky A.V., Ostapchuk P.S. Mathematical prediction of breeding value in sheep. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2018, vol. 9, no. 6, pp. 1645–1649.
4. Singh S., Gautam B., Rao A., Tandon G., Kaur S. Bioinformatics Approaches for Animal Breeding and Genetics. Current trends in Bioinformatics: An Insight. Singapore, 2018, pp. 287–306. DOI: 10.1007/978-981-10-74837_17.
5. Faid-Allah E. Multi-trait and multi-source selection indices for milk production and reproductive traits in a herd of Holstein cattle in Egypt. Jurnal Ilmu Ternak dan Veteriner, 2015, vol. 20, no. 3, pp. 159–167. DOI: 10.14334/JITV.V20I3.1182.
6. Addo S., Schäler J., Hinrichs D., Thaller G. Genetic Diversity and Ancestral History of the German Angler and the Red-and-White Dual-Purpose Cattle Breeds Assessed through Pedigree Analysis. Agricultural Sciences, 2017, vol. 8, no. 9, pp. 1033–1047. DOI: 10.4236/as.2017.89075.
7. García-Ruiz A., Wiggans G.R., Ruiz-López F.J. Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population. Journal of Dairy Science, 2019, vol. 102, no. 2, pp. 1806–1810. DOI: 10.3168/jds.2018-15076.
8. Moore K.L., Vilela C., Kaseja K., Mrode R., Coffey M. Forensic use of the genomic relationship matrix to validate and discover livestock pedigrees. Journal of Animal Science, 2019, vol. 97, no. 1, pp. 35–42. DOI: 10.1093/jas/sky406.
9. Mel'nikova E.E., Yanchukov I.N., Yermilov A.N., Zinovieva N.A., Osadchaya O.Yu., Kharitonov S.N. Selection index for cow breeding value in black and white population of dairy cattle in Moscow region. Izvestiya Timiryazevskoi sel'skokhozyaistvennoi akademii = Izvestiya of Timiryazev Agricultural Academy, 2017, no. 1, pp. 85–97. (In Russian).
10. Yanchukov I.N., Sermyagin A.A., Mel'nikova E.E., Nemchinova M.V., Kharitonov S.N. Comprehensive assessment of dairy cattle based on the selection index. Aktual'nye problemy intensivnogo razvitiya zhivotnovodstva = Current Problems of Intensive Development of Animal Husbandry, 2017, vol. 20, no. 1, pp. 13–21. (In Russian).
11. Miglior F., Muir B.L., Van Doormaal B.J. Selection Indices in Holstein Cattle of Various Countries. Journal of Dairy Science, 2005, vol. 88, no. 3, pp. 1255–1263. DOI: 10.3168/jds.S0022-0302(05)72792-2.
12. Viana J.H.M., Bartolo P.J.D.S. New applications of three-dimensional data acquisition, modelling, and printing in animal sciences: a case report. Singapore, Progress in Additive Manufacturing, 2016, pp. 122–127.
13. Soloshenko V.A., Popovski Z., Goncharenko G.M., Petukhov V.L., Grishina N.B., Shishin N.I., Kamaldinov E.V. Association of polymorphism of κ-casein gene and its relationship with productivity and qualities of a cheese production. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 2016, vol. 7, no. 5, pp. 982–989.
14. Kamaldinov E.V. Canonical discriminant model of the father genotype influence on some interior indicators of its pig descendants. Vestnik KRASGAU = Bulletin of KrasGAU, 2012, no. 1, pp. 117–122. (In Russian).
15. Kamaldinov E.V., Korotkevich O.S. Canonical discriminant model of interbreed differentiation for biochemical and hematological blood indices. Agrarnaya Rossiya = Agrarian Russia, 2011, no. 5, pp. 8–12. (In Russian).
Review
For citations:
Petrov A.F., Kamaldinov E.V., Panferova O.D., Efremova O.V., Rogozin V.A. Body volume modeling by linear features of the Irmen type cattle. Siberian Herald of Agricultural Science. 2020;50(6):106-114. (In Russ.) https://doi.org/10.26898/0370-8799-2020-6-12