The purpose of the study was to determine the milk productivity and chemical composition of the milk of mares of the Kazakh breed of the jabe type (KJ) and the Novoaltay-Kazakh crossbreeds of the 1st generation (NA x KJ) in the conditions of herd keeping. To determine the milk productivity of mares, 2 experimental groups were formed with a total of 30 mares, 15 individuals were selected in each group. The studied animals were formed according to the principle of pairs of analogues in the context of full-age groups from 5 to 11 years. Kazakh horses of the jabe type in the group of experimental mares in milk have an average live weight of 433.5 kg, and are significantly inferior to the Novoaltay-Kazakh crosses (515.3 kg). The body measurements were 142.0-149.0-174.9-18.2 cm in Kazakh horses of the jabe type, and 150.1-157.1-186.7-20.02 cm, respectively, in Novoaltay-Kazakh crossbreeds. According to the results of studies, the milkiness of mares of the Novoaltay-Kazakh crosses for 105 days of lactation averaged 1932 liters or higher by 25.2% (487.2 liters) than the milkiness of mares of the Kazakh breed of the jabe type. As a result of studies on the composition of milk of mares of different genotypes, it was found that in mares of Kazakh jabe, on average, protein and fat indicators compared to Novoaltay-Kazakh crossbreeds were higher by 0.07% and 0.05%. In the course of determining the live weight of mares among the experimental groups, it was found that the Novoaltay-Kazakh crossbreeds, on average, had a higher live weight of 515.3 kg or higher compared to the Kazakh jabe by 81.8 kg (15.8%). Thus, the studies have proved the prospects of using stallions of the Novoaltay breed to increase the milkiness of local Kazakh horses of the jabe type in herd and pasture conditions.

Концепция развития продуктивного и племенного верблюдоводства Республики Казахстан на 2021-2030 годы

Background/Objectives: The Yanqi horse is a distinguished local breed in China, known for its robust physique and strong adaptability. However, due to insufficient breeding populations and a loosely structured breeding system, the number of Yanqi horses has been declining annually. To protect its genetic resources and develop scientific breeding strategies, this study aimed to analyze the genetic diversity, parentage relationships, and genetic structure of the Yanqi horse conservation population using microsatellite markers. Materials and Methods: A total of 117 Yanqi horses were selected for genotyping analysis using 16 microsatellite markers. Genetic diversity parameters (e.g., allele number, heterozygosity, F-statistics) were calculated using GeneAIEX (v.6.503) and Fstat software (v.2.9.4). Parentage analysis was conducted using Cervus software. Bayesian clustering analysis was performed using STRUCTURE software (v.2.3.4), and a phylogenetic tree was constructed based on Nei’s genetic distance to reveal the population genetic structure. Results: A total of 191 alleles were detected, with an average allele number of 11.969, observed heterozygosity of 0.481, and expected heterozygosity of 0.787. Parentage testing showed a cumulative exclusion probability (CEP) of 0.9652999 when one parent’s genotype was known and 0.9996999 when both parents’ genotypes were known, achieving an accuracy of 99%. Genetic differentiation analysis revealed moderate genetic divergence among populations (FST = 0.128) and moderate inbreeding levels (FIS = 0.396). Bayesian clustering analysis (K = 4) indicated that the Yanqi horse population could be divided into four genetic clusters, reflecting the impact of geographical isolation on genetic structure. Conclusions: The Yanqi horse conservation population exhibits moderate genetic diversity, high accuracy in parentage identification, and moderate genetic differentiation and inbreeding. The findings provide a scientific basis for the conservation and sustainable utilization of Yanqi horse genetic resources. Future efforts should focus on strengthening conservation measures, optimizing breeding strategies, and further investigating the genetic background using genomic technologies to ensure the sustainable development of the Yanqi horse population.