奶牛体型性状育种值计算

近年来由于加大了选择强度(牛群更新率在25％-30％)和不断引进与消化吸收北美优良种公牛的遗传素质,上海地区荷斯坦牛在提高奶牛产奶量和改良体型外貌上都取得了较大进展,已基本形成体躯容积大,尻部方正,泌乳系统优良,乳用特征明显的优良体型奶牛群。但尻宽度,肢蹄等体型性状仍需持续改良。因此当前上海地区     

单性状BLUP法应用于上海奶牛育种

<正> 由于电子计算机的普及,早在70年代初由美国Henderson教授创立的最佳线性无偏预测(BLUP)法在家畜育种界逐渐得到了推广应用。在80年代初,我国学者纷纷开展了对这一新技术的研究和应用。如我国学者北京农业大学的张沅、张勤以及贵州农学院的俞渭江等不仅全面研究了BLUP法在我国奶牛育种中的应用,还设计编制了BLUP计算程序。 另外,由于现代奶牛育种工作的发展,尤其对于     

多浪羊主要性状遗传参数及育种值估计

本研究通过多浪羊体重、体尺性状进行育种值估计并制定综合育种值(Combined Breeding Value,CBV)公式。选用2019—2022年40头种公羊和541头后代周岁羊9586条生产记录,采用SAS9.2软件GLM对固定效应进行分析,利用DMU软件动物模型BLUP估计公羊的育种值。多浪羊初生重、断奶重、周岁重、体高、体长、胸围、胸深、胸宽、尾长、尾高、尾宽遗传力分别为0.29、0.23、0.42、0.20、0.32、0.47、0.41、0.12、0.08、0.07、0.12,周岁体重、体长、胸围和胸深为高遗传力(h²>0.3),尾长、尾宽为低遗传力(h²<0.1),其余性状为中等遗传力(0.1相似文献   

应用BLUP法进行家兔育种值的估计

收集四川省畜牧科学研究院种兔场A系兔第三世代公兔40只的女儿繁殖成绩共计356窝及第四世代公兔19只后代的生长性状资料共计150只,采用最佳线性无偏预测法（BLUP估计）种公兔育种值,以提高选种的准确性。     

利用动物模型最佳线性无偏预测法估计西门塔尔种公牛精液性状育种值研究

利用贵州省家畜冷冻精液站西门塔尔种公牛2006、2007、2008年采精量、鲜精活力、冻精活力和合格冻精产量7172条记录,建立动物模型,利用MTDFREML软件对种公牛的单个精液性状育种值进行估计,对育种值排序做秩相关分析,并跟据各性状的不同遗传特点,计算种公牛综合育种值。结果表明,各性状育种值排序有所差异;综合排名前10位的公牛依次是6021、2190、6019、6075、6059、6053、452、439、6051和6063。为该站种公牛的选择提供了一定的依据。     

奶牛繁殖技术与育种方案

繁殖技术与育种方案是奶牛科学中两个基础研究领域 ,对奶业生产的发展起着至关重要的作用。新的繁殖技术的发展对奶牛改良方案的影响很大。人工授精带来了后裔测定方案的闻世 ,超数排卵和胚胎移殖导致核心群育种方案的出现。本文就这两个研究领域的研究成果和发展动态作简要介绍 ,旨在为推广和开发奶牛生产的高新技术 ,为促进我国奶业现代化进程提供借鉴和参考。１人工授精与后裔测定方案人工授精是对动物育种方案产生主要影响的第一个繁殖技术。Ｒｉｎｄｅｌ与Ｒｏｂｅｒｔｓｏｎ１９５０年提出了后裔测定（简称ＰＴ）方案 ,以有效利用人工…     

估计猪早期生长性状和繁殖性状的动物模型比较

分析了三种模型对出生重，21、60、90日龄重，总产仔数，以及出生窝重性状遗传参数估计中的加性遗传效应、母体效应、窝效应和残差效应的方差组分、遗传力及其变化趋势。结果表明，出生重、21日龄重和60日龄重采用包含加性遗传效应、母体效应、窝效应和残差效应的模型进行估计比较适宜。90日龄重、总产仔、产活仔和出生窝重性状采用包含加性遗传效应、母体效应和残差效应的模型进行估计效果较好。     

陇州奶牛开放核心群育种性状遗传分析

本研究通过采用陕西省宝鸡市陇县陇州奶牛繁育中心及7个陇州奶牛开放核心群20年来育种资料的数据,对陇州奶牛的主要性状(305d产奶量、乳脂率、乳蛋白率、18月龄体重、18月龄日增重以及体型评分)进行分析,并运用动物模型及MT-DFEML(多性状非求导REML)软件,计算了这些性状的遗传参数。结果主要性状遗传力分别为0.32、0.28、0.27、0.32、0.25和0.19。产奶量与乳脂率、乳蛋白率均呈负相关,与体重、日增重呈正相关,乳脂率与乳蛋白率呈正相关,乳成分与体重没有遗传相关。体重、日增重与体型评分呈正相关。     

Transition Cow: Interaction with Fertility

In recent years a progressive worsening of fertility indices in dairy cow herds has been observed. Several factors (genetic, dietary and management) seem to be more related to poor fertility than milk yield level. The degree and the length of the energy deficit during the transition period are inversely related to reproductive indices (e.g. conception rate is < 30% for BCS decreases over one unit). A serious energy deficit reduces (or suppresses) pulsatile secretion of gonadotrophins (ovarian dysfunction and/or smaller follicles); IGF-1 and insulin plasma levels (slower follicle growth and higher embryonic mortality); and progesterone production from the corpus luteum (higher rate of embryonic abortions). The diet influences fertility in several ways. Excess of rumen degradable proteins, apart from negative energy balance, negatively affects reproductive activity. Conversely, some nutrients (i.e. some polyunsaturated fatty acids or some amino acids) seem to show positive effects on fertility. Finally, the relationship between health status, often compromised during the transition period, and fertility efficiency is discussed. The release of cytokines seems to be related directly and indirectly (mainly by the change in usual hepatic metabolism) to the malfunction of reproductive apparatus. Quick recovery of reproductive activity requires the adoption of strategies around calving to cover the higher environmental and nutritive requirements and to prevent disorders of any kind.

     

母牛养殖技术要点

以科尔沁肉牛为例,从犊牛培育前期、犊牛培育后期、育成牛前期、育成牛后期、妊娠前期、妊娠后期、分娩及产后护理、哺乳期8个时间段详述母牛养殖中的技术要点。     

奶牛生物技术育种研究进展

奶业已成为我国农业战略产业的重要组成部分,与发达国家相比,我国奶牛在良种率、产奶量、乳品质等方面仍存在较大差距。面对日益增长的消费量和品质需求,加快奶牛育种显得尤为迫切。本文便针对我国奶业当前发展现状分析了我国奶牛产业发展存在的问题及利用生物技术进行育种的必要性和迫切性。从分子标记辅助选择、QTL 定位、全基因组关联分析、全基因组选择、转基因以及胚胎工程等方面阐述了近些年国内外奶牛生物技术育种研究现状和进展,讨论了目前奶牛生物技术育种过程中存在的问题,以期对我国奶业发展有所裨益。     

应用促黄体素释放激素提高奶牛繁殖力试验

在５３９头黑白花奶牛中进行促黄体素释放激素（ＬＲＨ－Ａ）提高繁殖力试验，其中３８１头母牛在授精时每头肌注ＬＲＨ－Ａ２００μｇ，１５８头母牛作为对照。试验结果：肌注ＬＲＨ－Ａ的临床健康母牛一次输精受胎率为７８．８８％，显著高于对照牛的４８．０５％；肌注ＬＲＨ－Ａ的排卵延迟母牛一次输精受胎率为７３．３３％，情期受胎率６８％和总受胎率８５％，显著高于对照牛的２５％、２６．８６％和６４．２８％：产后１４天肌注ＬＲＨ－Ａ的母牛产犊间隔为３６０．３１±２７．６７天，显著短于对照牛（３９４．７３±０．３２天）。结果表明，应用ＬＲＨ－Ａ处理能明显提高奶牛繁殖力。     

奶牛育种技术的专利信息分析

为促进我国奶业更好更快地发展,应从根本上解决奶牛育种问题。本文以奶牛育种领域发明专利为研究对象,通过对国家知识产权局专利数据库提供的发明专利进行数据挖掘和可视化处理,完成了奶牛品种选育和遗传改良领域的专利申请趋势和专利布局概况,旨在探明国内外重要申请人的技术发展路线,同时为国内育种学家提供有价值的技术情报。     

酶制剂及其在奶牛养殖中的应用

本文主要阐述了酶制剂的作用机理,酶制剂在泌乳奶牛上的应用,影响酶制剂效果的因素以及目前国内饲用酶生产、研究中存在的问题:并对酶制剂的应用前景进行了展望.     

提早配种对育成奶牛受胎率及产乳性能的影响

长期以来，我市奶牛基地育成母牛的初配年龄采用１８～２０月龄、体重达４００千克开始进行初配，平均配准月龄一般为２１月龄或以上。从１９９０年后，采用１６～１８月龄、体重达３５０千克进行初配，平均配准月龄一般在２０月龄左右。为了加快奶牛的发展，提高饲养奶牛的综合效益，近年来，我市奶牛基地通过缩短哺乳期，加强犊牛、育成母牛阶段的精心饲养管理，对育成奶牛进行了提早配种的效果对比试验，观察１３～１４月龄体重达３２０千克时进行初配，对其受胎率、生长发育、犊牛初生重和产乳量的影响，从而为当地养牛专业户推广奶牛提…     

Effects of the Sire and District of A1 on Cow Fertility

Insemination results per bull and district of AI (or technician) were analysed in a 5 year study. Return Rates (RR) were registered between Oct. 1976 and Sept. 1981. Data included 856 850 first AI made by 56 technicians. Depending on years, AI were made with the semen of 81 to 103 bulls of 5 breeds. Only bulls which performed at least 500 AI's per year were taken into account. A first analysis made with the data of 14 bulls represented during the 5 years show that: 1) the breed, the bull within breed and district of AI (or technician) were the most important factors influencing RR. RR were less affected by other factors such as the size of the herd or the year. 2) results given for successive RR were nearly identical from RR₂₄ to RR₉₀. 3) the effect of breed, bull and district of AI were less important on the variable illustrating more specificially late return in oestrus (RR_25–300). Yearly analysis involving larger number of bulls gave very similar results to the 5 year study. Variability due to the district of AI (or technician) and to the bull were of the same magnitude. Maximum differences between bulls or districts varied from 10% (RR₂₄) to 20% (RR₉₀). As strong relationships between bull and district of AI or technician were found, complementary analyses from the 1978 set of data were made to investigate how the variability due to the district of AI could introduce bias when estimating bull's RR. Comparisons between models were made on the basis of correlations between a reference model including a district effect and reduced models. For RR₂₄ and RR₉₀ correlations between solutions were always higher than 0.97. This show that if sufficient number of AI's per bull are performed no major bias is introduced and the district of AI or technician is neglectable when evaluating bull's RR .