中国乳业 ›› 2026, Vol. 0 ›› Issue (8): 11-17.doi: 10.12377/1671-4393.26.08.02

• 核心牛群繁育策略专栏 • 上一篇    下一篇

核心牛群繁育管理中的常见误区与改进建议

李明梅   

  1. 延津县农业农村局,河南延津 453200
  • 发布日期:2026-09-17
  • 作者简介:李明梅(1979-),女,河南延津人,本科,畜牧师,研究方向为畜禽养殖技术推广应用。

Common Misconceptions and Improvement Strategies in Breeding Management of Core Dairy Herds

LI Mingmei   

  1. Yanjin County Bureau of Agriculture and Rural Affairs,Yanjin Henan 453200
  • Published:2026-09-17

摘要: [目的] 核心牛群是奶牛育种体系的核心种质资源,其繁育管理水平直接影响遗传改良进程与牧场效益。然而,生产实践中,核心牛群管理仍存在若干认知与操作层面的误区,制约着遗传潜力的发挥。本文旨在系统剖析上述误区的生物学与遗传学机理,并提出针对性改进建议。[方法] 通过系统检索PubMed、CNKI等数据库中2011—2026年发表的奶牛繁育管理相关文献,并结合牧场生产实践,对核心牛群繁育管理中的五大常见误区进行梳理与分析。[结果] 五大误区分别为:过度依赖产奶量作为选择标准、忽视基因组选择与表型数据整合、营养管理滞后于繁殖调控需求、忽略子宫健康与胚胎移植衔接管理、数据记录缺乏长期连续性。针对各误区,分别从构建综合选择指数、建立基因组与表型双重筛选流程、实施分阶段精准营养方案、建立受体牛量化筛选体系、推进电子化数据管理等方面提出改进方案。[结论] 核心牛群管理须从经验驱动转向数据驱动,由单一性状选择转向多性状协同优化,方能实现遗传潜力与经济效益的同步提升。

关键词: 核心牛群, 繁育管理, 基因组选择, 繁殖效率, 营养调控

Abstract: [Objective] The core herd constitutes the foundational genetic resource of dairy cattle breeding systems,and its reproductive management directly influences both genetic improvement progress and farm profitability. In current production practices,several cognitive and operational misconceptions persist in managing core herds,constraining the full expression of their genetic potential. This paper systematically analyzed the biological and genetic mechanisms underlying these misconceptions and proposes targeted strategies for improvement.[Methods] By reviewing literature on dairy cattle reproduction and management published between 2011 and 2026 from databases such as PubMed and CNKI,and integrating field observations from commercial farms,this study identified and examined five prevalent misconceptions in core herd reproductive management.[Results] The five key misconceptions include: overreliance on milk yield as the primary selection criterion;inadequate integration of genomic selection with phenotypic data;nutritional management lagging behind reproductive regulation requirements;insufficient attention to the linkage between uterine health and embryo transfer protocols;and a lack of long-term continuity in data recording. Corresponding corrective measures are proposed: constructing comprehensive selection indices;establishing dual screening workflows combining genomic and phenotypic information;implementing stage-specific precision nutrition programs;developing quantitative screening systems for recipient cows;and advancing electronic data management.[Conclusion] Effective core herd management requires shifting from experience-driven to data-driven decision-making,and from single-trait selection to multi-trait optimization,thereby achieving synchronized improvements in genetic potential and economic returns.

Key words: core dairy herd, breeding management, genomic selection, reproductive efficiency, nutritional regulation

[1] Weller J I,Gershoni M,Ezra E. Breeding dairy cattle for female fertility and production in the age of genomics[J]. Veterinary Sciences,2022,9(8):434.
[2] Dodd G R,Miglior F,Schenkel F S,et al. Potential of sensor-derived estrus traits for genetic selection in dairy cattle[J]. Journal of Dairy Science, 2026, 109(5):5438-5449.
[3] Mckay C,Viora L,Denholm K,et al. Risk factors for ultrasound-diagnosed endometritis and its impact on fertility in Scottish dairy cattle herds[J]. Veterinary Record, 2023, 193(3):e3168.
[4] Tasara T,Meier A B,Wambui J,et al. Interrogating the diversity of vaginal, endometrial,and fecal microbiomes in healthy and metritis dairy cattle[J]. Animals, 2023,13(7):1221.
[5] Diaz-lundahl S,Nørstebø S F,Klem T B,et al. The microbiota of uterine biopsies, cytobrush and vaginal swabs at artificial insemination in Norwegian red cows[J]. Theriogenology,2023,209:115-125.
[6] Lynch C,Oliveira Junior G A,Schenkel F S,et al. Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle[J]. Journal of Dairy Science,2021, 104(11):11820-11831.
[7] Oliveira Junior G A,Schaeffer L R,Schenkel F,et al. Potential effects of hormonal synchronized breeding on genetic evaluations of fertility traits in dairy cattle:A simulation study[J]. Journal of Dairy Science,2021,104(4):4404-4412.
[8] 孟毅,魏勇,刘洋乐,等.不同因素对奶牛繁殖性能的影响[J].今日畜牧兽医,2023,39(1):70-73.
[9] Rearte R,Corva S G,De La Sota R L,et al. Associations of somatic cell count with milk yield and reproductive performance in grazing dairy cows[J]. Journal of Dairy Science,2022,105(7):6251-6260.
[10] Korket T,Koonawootrittriron S,Suwanasopee T,et al. Patterns of variation and relationships among fat,protein,and milk yield of individual dairy cattle in a Thai multibreed population[J]. Tropical Animal Health and Production,2024,56(8):324.
[11] Atzori A S,Cesarani A,Cresci R,et al. Characterization of milk losses and recovery in response to heat wave in dairy cows[J]. Journal of Dairy Science,2026,doi:10.3168/jds.2025-28202.
[12] 李聪,孙东晓,姜力,等. 奶牛重要经济性状全基因组关联分析研究进展[J]. 遗传,2012,34(5):545-550.
[13] Keogh K,Carthy T R,Mcclure M C,et al. Genome-wide association study of economically important traits in Charolais and Limousin beef cows[J]. Animal,2021,15(1):100011.
[14] Onogi A,Watanabe T,Ogino A,et al. Genomic prediction with non-additive effects in beef cattle:Stability of variance component and genetic effect estimates against population size[J]. BMC Genomics,2021,22(1):512.
[15] Al Kalaldeh M,Swaminathan M,Gaundare Y,et al. Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India[J]. Genetics Selection Evolution, 2021,53(1):73.
[16] Van Der Nest M A,Hlongwane N,Hadebe K,et al. Breed ancestry,divergence, admixture,and selection patterns of the Simbra crossbreed[J]. Frontiers in Genetics, 2020,11:608650.
[17] Sangalli J R,Nociti R P,Chiaratti M R,et al. Beta-hydroxybutyrate alters bovine preimplantation embryo development through transcriptional and epigenetic mechanisms[J]. Biology of Reproduction,2025,112(2):253-272.
[18] Reumann A L,Bilbao M G,Moran K D,et al. Impact of postpartum health disorders on metabolic status and reproductive performance of lactating dairy cows[J]. Veterinary Journal,2026,317:106662.
[19] 邢伟山,李然.奶牛繁殖管理中的常见问题及优化对策[J].现代农村科技,2026(2):94-95.
[20] Su Y,Li Q,Zhang Q,et al. Exosomes derived from placental trophoblast cells regulate endometrial epithelial receptivity in dairy cows during pregnancy[J]. Journal of Reproduction and Development,2022,68(1):21-29.
[21] Nowicki A. Embryo transfer as an option to improve fertility in repeat breeder dairy cows[J]. Journal of Veterinary Research,2021,65(2):231-237.
[22] Cordeiro C G,Souza F A,De Lara N S,et al. Pregnancy establishment and early embryonic survival in lactating Holstein cows are differentially constrained by parity, body reserves, and embryo transfer[J]. Theriogenology,2026,265:118076.
[23] Xie C,Huang C,Yan L,et al. Recipients' and environmental factors affecting the pregnancy rates of a large,fresh in vitro fertilization-embryo transfer program for dairy cows in a commercial herd in China[J]. Veterinary Sciences,2024,11(9):410.
[24] Choi W,Ro Y,Choe E,et al. Evaluation of corpus luteum and plasma progesterone the day before embryo transfer as an index for recipient selection in dairy cows[J]. Veterinary Sciences,2023,10(4):262.
[25] Madureira A M L,Burnett T A,Marques J C S, et al. Occurrence and greater intensity of estrus in recipient lactating dairy cows improve pregnancy per embryo transfer[J]. Journal of Dairy Science,2022,105(1):877-888.
[26] Boonkum W,Chankitisakul V,Duangjinda M,et al. Genomic selection using single-step genomic BLUP on the number of services per conception trait in Thai-Holstein crossbreeds[J]. Animals, 2023,13(23):3609.
[27] Passafaro T L,Rubio Y L B,Vukasinovic N,et al. Genetic evaluation of productive longevity in a multibreed beef cattle population[J]. Journal of Animal Science,2024, 102:skae363.
[28] Kim E H,Kang H C,Sun D W, et al. Estimation of breeding value and accuracy using pedigree and genotype of Hanwoo cows (Korean cattle)[J]. Journal of Animal Breeding and Genetics,2022,139(3):281-291.
[29] Buaban S,Prempree S,Sumreddee P, et al. Genomic prediction of milk-production traits and somatic cell score using single-step genomic best linear unbiased predictor with random regression test-day model in Thai dairy cattle[J]. Journal of Dairy Science,2021,104(12):12713-12723.
[30] 张哲,张勤,丁向东. 畜禽基因组选择研究进展[J]. 科学通报,2011,56(26):2224-2234.
[31]  Černá M, Zavadilová L,Vostrý L,et al. Genetic parameters for a weighted analysis of survivability in dairy cattle[J]. Animals,2023,13(7):1188.
[32] 闫成琪,赵源,田慧彬,等. 基因组选择技术在家畜育种中的应用[J]. 农业生物技术学报,2026,34(3):480-490.
[1] 张伟玺, 朱化彬. 核心牛群繁育策略的研究进展[J]. 中国乳业, 2026, 0(8): 2-10.
[2] 付畅, 李强, 李培明. 奶牛核心群精准育种与高效繁殖策略[J]. 中国乳业, 2026, 0(8): 18-23.
[3] 王春霞, 王鹏. 营养-环境互作对牦牛繁殖性能的影响及调控机制[J]. 中国乳业, 2026, 0(7): 55-62.
[4] 赵平, 聂伟, 柴沙驼. 牦牛营养调控与繁育效率提升研究[J]. 中国乳业, 2026, 0(7): 63-69.
[5] 吴泽鹏, 吴炜俊, 李颂群, 李冬梅, 范存斐, 孙克龙, 陈绮萍, 张婉莹, 刘帆, 林思怡. 反刍动物营养-健康-减排协同调控技术研究进展[J]. 中国乳业, 2026, 0(6): 30-39.
[6] 郭志坚. 热应激下母牛繁殖管理中布舍瑞林的应用[J]. 中国乳业, 2026, 0(6): 65-74.
[7] 周娟娟, 葛陇利, 曹云龙, 史晓莉, 刘红颖, 边会龙, 伊晨刚. 奶山羊同期发情与人工授精技术的应用效果及影响因素分析[J]. 中国乳业, 2026, 0(4): 14-19.
[8] 孙运娥. 围产期奶牛低血钙症的发生机制与防治策略[J]. 中国乳业, 2026, 0(3): 54-61.
[9] 袁洋, 魏金销, 赵广英, 张伟, 韦光辉, 郭利亚. 现代生物育种技术在牛品种培育中的选择与应用[J]. 中国乳业, 2026, 0(3): 19-24.
[10] 张建康. 秋季防疫对奶牛繁殖性能的影响与协同管理策略[J]. 中国乳业, 2025, 0(9): 37-43.
[11] 周长城. 奶牛同期发情处理技术的实践应用与关键管控策略[J]. 中国乳业, 2025, 0(8): 21-26.
[12] 刘明胜, 赵平. 奶牛胚胎早期死亡的多因素分析与综合防控技术研究[J]. 中国乳业, 2025, 0(7): 18-23.
[13] 谷粟琨, 王振成, 李志佳, 赵善江, 朱化彬, 赵慧秋. 奶牛早期胚胎损失与预防措施[J]. 中国乳业, 2025, 0(7): 12-17.
[14] 张廷青, 乔治, 吕宏伟. 奶牛早期胚胎死亡的综合研究与精准防控策略[J]. 中国乳业, 2025, 0(7): 6-6.
[15] 李玉森. 泌乳早期奶牛发情与乏情的代谢特征及生殖调控策略[J]. 中国乳业, 2025, 0(6): 87-92.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!