摘要
【目的】本研究基于试验测定的中国荷斯坦牛血液和乳汁中的孕酮浓度表型,探究了影响中国荷斯坦牛体内孕酮分泌的环境因素、孕酮浓度的变化趋势、孕酮浓度与乳成分的关联程度以及血乳中孕酮浓度的预测方法。【方法】试验于2021年8月在北京、山东两个牧场采集不同胎次、泌乳阶段和妊娠状态的中国荷斯坦泌乳牛的奶样、尾根血样,测定孕酮浓度,最终获得402条乳汁孕酮浓度和298条血液孕酮浓度表型用于数据分析。对孕酮浓度进行数据转化使其近似服从正态分布后,采用固定效应模型探究胎次、泌乳阶段、妊娠状态、牧场等固定效应对奶牛孕酮表型的影响,运用R语言cor函数计算孕酮与各乳成分间的关联,并利用偏最小二乘法和个体及乳成分信息对孕酮浓度进行预测,以建立孕酮浓度表型高通量获取手段。【结果】妊娠状态对转化乳汁孕酮浓度存在极显著影响(P<0.01),胎次、场效应对转化乳汁孕酮浓度均有显著影响(P<0.05),而转化血液孕酮浓度只受到妊娠状态影响(P<0.01);全乳固体、乳脂率、乳蛋白率、脂蛋比与转化乳血孕酮浓度均存在显著或极显著的正相关关系(r=0.14~0.37,P<0.05;P<0.01);基于本试验数据,乳成分与个体信息对转化乳血孕酮浓度的预测准确性不高(R2=0.030~0.17),但如果增加血液或乳汁的转化孕酮浓度对乳汁或血液的转化孕酮浓度进行预测,预测效果则有大幅提升(R2=0.40)。【结论】影响泌乳期中国荷斯坦牛转化孕酮浓度的因素除妊娠状态外,可能还包括饲养条件与胎次。此外转化孕酮浓度与乳脂率、乳蛋白率等乳成分呈极显著相关。基于乳成分信息与转化孕酮的关系,获得了对中国荷斯坦牛乳血转化孕酮浓度预测的可用策略,为今后牧场的繁殖辅助管理、奶牛育种新性状研发以及孕酮浓度的高通量获取等提供了新思路。
【Objective】 This study was aimed to investigate the phenotypic features of blood progesterone(BP) concentration and milk progesterone(MP) concentrations in Chinese Holstein cows based on the experimental data, the significant impact factors on the progesterone concentration and the relationship with milk composition.Then an attempt was made to find a way to obtain the progesterone phenotype on large population.【Method】 In August 2021,milk samples and tail root blood samples of Chinese Holstein lactating cows with different parity, lactation stage and pregnancy status were collected in two pastures in Beijing and Shandong, and progesterone concentration was measured.Finally, 402 MP concentrations and 298 BP concentration phenotypes were obtained for data analysis.After transforming the data of progesterone concentration to approximate following normal distribution, the fixed effect model was used to explore the influence of fixed effects on the progesterone phenotype of dairy cows, such as parity, lactation stage, pregnancy state, and pasture.Then, the R language cor function was used to calculate the correlation between progesterone and milk composition.The partial least squares method and individual and milk component information were used to predict progesterone concentration, so as to establish a high-throughput acquisition method for progesterone concentration phenotype.【Result】 Pregnancy state had an extremely significant effect on the concentration of transforming MP(P<0.01),parity and field effect had a significant effect on the concentration of transforming MP(P<0.05),while transforming BP concentration was only affected by pregnancy state(P<0.01).There was a significant or extremely significant positive correlation between milk solid, milk fat percentage, milk protein percentage, and transforming milk-blood progesterone concentration(r=0.14-0.37,P<0.05 or P<0.01).Based on the test data, the prediction accuracy of milk composition and individual information on transforming milk-blood progesterone concentration was not high(R~2=0.030-0.17),but if the transforming progesterone concentration in blood or milk was increased to predict milk or blood transforming progesterone concentration, the prediction effect would be greatly improved(R~2=0.40).【Conclusion】 This study showed that the factors affecting transforming progesterone concentration of Chinese Holstein cows in lactation period might include feeding conditions and parity in addition to pregnancy status.In addition, transforming progesterone concentration was significantly correlated with milk components such as milk fat percentage and milk protein percentage. Based on the relationship between transforming progesterone concentration and milk composition, the available strategy for predicting the transforming progesterone concentration in Chinese Holstein cows during lactation.Accordingly, it provided a supplement for the reproductive management in the farm and new ideas for developing new traits in dairy cattle breeding, a high-throughput method for collecting progesterone phenotype in Chinese Holstein cows.
作者
曾治钦
娄文琦
许静漪
马烨桦
张永福
任小丽
陈少侃
闫磊
郭刚
张震
王雅春
ZENG Zhiqin;LOU Wenqi;XU Jingyi;MA Yehua;ZHANG Yongfu;REN Xiaoli;CHEN Shaokan;YAN Lei;GUO Gang;ZHANG Zhen;WANG Yachun(Key Laboratory of Animal Genetics,Breeding and Reproduction(MARA),National Engineering Laboratory for Animal Breeding,College of Animal Science and Technology,China Agricultural University,Beijing 100193,China;Henan Seed Industry Development Center,Zhengzhou 450046,China;Henan Dairy Herd Improvement Center,Zhengzhou 450045,China;Beijing Sunlon Livestock Development Company Limited,Beijing 100176,China)
出处
《中国畜牧兽医》
CAS
CSCD
北大核心
2023年第1期186-197,共12页
China Animal Husbandry & Veterinary Medicine
基金
国家重点研发计划(2021YFD1200903)
国家现代农业产业技术体系(CARS-36)
河南省科技攻关项目(212102110011、222102520042、222102110342)
财政部和农业农村部:长江学者和创新团队发展计划(IRT_15R62)
河南省现代农业产业技术体系建设专项(HARS-22-14-S)
河南省重点研发专项:奶牛特色优质新品系选育与种质提升关键技术研究(221111111100)。
关键词
中国荷斯坦牛
孕酮
乳成分
线性预测
Chinese Holstein cows
progesterone
milk composition
linear model
