Comparison of Estimated Genetic Connectedness among Three Herds of Chinese Holstein Cattle

Estimating genetic connectedness among herds is important for the accuracy of dairy cattle genetic evaluation. When selecting between animals raised in different herds, the accuracy of their genetic evaluations can be influenced by the degree of connectedness among these herds. In this study, two methods were used to measure genetic connectedness, CR （genetic connectedness rating ） and GLt （total number of direct genetic links between group）, among herds from Beijing, Shanghai, and Tianjin. Genetic connectedness between the herds from Beijing and Tianjin was 23.95%, between Beijing and Shanghai was 17. 10%, and between Shanghai and Tianjin it was 14.28%. Genetic connectedness between herds from Beijing and Tianjin was the highest and that between Shanghai and Tianjin was the lowest. The correlation coefficient for the two methods was 0. 808. Some suggestions for improved genetic evaluation of dairy cattle were also discussed.     

Estimation of genetic parameters and prediction of breeding values for multivariate threshold and continuous data in a simulated horse population using Gibbs sampling and residual maximum likelihood

Simulated horse data were used to compare multivariate estimation of genetic parameters and prediction of breeding values (BV) for categorical, continuous and molecular genetic data using linear animal models via residual maximum likelihood (REML) and best linear unbiased prediction (BLUP) and mixed linear-threshold animal models via Gibbs sampling (GS). Simulation included additive genetic values, residuals and fixed effects for one continuous trait, liabilities of four binary traits, and quantitative trait locus (QTL) effects and genetic markers with different recombination rates and polymorphism information content for one of the liabilities. Analysed data sets differed in the number of animals with trait records and availability of genetic marker information. Consideration of genetic marker information in the model resulted in marked overestimation of the heritability of the QTL trait. If information on 10,000 or 5,000 animals was used, bias of heritabilities and additive genetic correlations was mostly smaller, correlation between true and predicted BV was always higher and identification of genetically superior and inferior animals was - with regard to the moderately heritable traits, in many cases - more reliable with GS than with REML/BLUP. If information on only 1,000 animals was used, neither GS nor REML/BLUP produced genetic parameter estimates with relative bias 50% for all traits. Selection decisions for binary traits should rather be based on GS than on REML/BLUP breeding values.     

中国荷斯坦牛SCD1基因多态性与泌乳性状的关联分析

本研究旨在探索中国荷斯坦牛SCD1基因多态性与产奶性状的相关性.以上海某奶牛场610头中国荷斯坦牛为试验材料,采用PCR-SSCP法对SCD1基因A293V位点遗传多态性进行分析,利用一般线性模型分析SCD1基因A293V位点突变对测定日产奶量、乳脂率、乳蛋白率、305天校正产奶量、乳脂量、乳蛋白量及体细胞评分7个泌乳性状的影响.共检测到AA、AV和VV 3种基因型,频率分别为0.634、0.323和0.043,等位基因A和V的频率分别为0.796和0.204.该位点突变对乳脂率、乳蛋白率的影响达到显著水平(P＜0.05),对测定日产奶量、305天校正产奶量、305天乳蛋白量和305天乳脂量以及体细胞评分影响不显著(P＞0.05).多重比较表明,VV基因型个体的乳蛋白率、乳脂率极显著高于AA、AV型个体(P＜0.01).SCD1基因A293V位点突变对中国荷斯坦牛泌乳性状的遗传效应有一定程度的影响,但影响机理需要进一步的研究.     

泌乳量对荷斯坦泌乳牛某些血尿生化指标的影响

随机选取正常泌乳牛36头，按泌乳量分成3组，每组12头。对各组的血酮、尿酮、血糖、Ca、p、Mg、ALP、GPT、GOT、BUN等指标进行检测。结果表明：3组泌乳牛之间，尿酮差异极显著（P＜0.01），血酮、血糖差异显著（P＜0.05）。随产奶量的增加，血酮、尿糖升高，血糖降低。但三组血清Ca、P、Mg、ALP、GPT、GOT、BUN等指标均无显著差异（P＞0.05）。     

动物模型在荷斯坦牛遗传评定上的应用

本研究应用动物模型ＢＬＵＰ法在微机上评定了北京地区１９６５￣１９９２年间出生的荷斯坦牛４１０８０头，建立了一套荷斯坦牛的动物模型评定系统。迭代求解采用间接解法，在阅读数据文件时进行。对于管理组、公牛与牛场互作、永久环境效应，采用Ｇａｕｓｓ－Ｓｅｉｄｅｌ迭代法，对于动物个体和遗传组效应，采用不完全的Ｊａｃｏｂｉ迭代法。提供预期传递力、父母传递力均数、预期生产力、表型均值等有用的遗传和生产信息。在配备     

Mastitis detection in dairy cows by application of fuzzy logic

The aim of the present research was to develop a fuzzy logic model for classification and control of mastitis for cows milked in an automatic milking system. Recording of data was performed on the University of Kiel's experimental dairy farm “Karkendamm”. A data set of 403,537 milkings from 478 cows was used. Mastitis was determined according to three different definitions: udder treatments (1), udder treatment or somatic cell counts (SCC) over 100,000/ml (2) and udder treatment or SCC over 400,000/ml (3). Mastitis alerts were generated by a fuzzy logic model using electrical conductivity, milk production rate and milk flow rate as input data. To develop and verify the model, the data set was randomly divided into training data (284,669 milkings from 319 cows) and test data (135,414 milkings from 159 cows). The evaluation of the model was carried out according to sensitivity, specificity and error rate. If the block-sensitivity was set to be at least 80%, the specificities ranged between 93.9% and 75.8% and the error rate varied between 95.5% and 41.9% depending on mastitis definition. Additionally, the average number of true positive cows per day ranged from 0.1 to 7.2, and the average number of false negative positive cows per day ranged from 2.4 to 5.2 in an average herd size for the test data of 39.7 cows/day. The results of the test data verified those of the training data, indicating that the model could be generalized.

Fuzzy logic is a useful tool to develop a detection model for mastitis. A noticeable decrease in the error rate can be made possible by means of more informative parameters.     

不同模型估计中国荷斯坦牛生产寿命遗传参数

旨在估计中国荷斯坦牛生产寿命遗传参数,同时比较不同模型的预测可靠性和稳定性。本研究使用单性状动物模型、单性状公畜模型和多性状动物模型对北京地区29个牧场90049头中国荷斯坦母牛的生产寿命数据进行遗传参数估计,所有模型均考虑了场、出生年季、头胎产犊月龄组的固定效应,个体加性遗传效应(动物模型)或父亲遗传效应(公畜模型)的随机效应和残差效应。结果表明,单性状动物模型和单性状公畜模型估计的生产寿命遗传力分别为0.052和0.047,多性状动物模型估计的遗传力较为稳定,介于0.057与0.069之间,多性状动物模型的遗传相关在0.779~0.998之间。对于存在大量在群个体(删失记录)的数据,使用基于前三胎数据的多性状动物模型较为合适,模型预测稳定性更高。本研究对中国荷斯坦牛生产寿命进行了遗传评估,为提高牧场效益、实现平衡育种提供了理论基础。     

提高原料奶卫生指标的三种方法

提高原料奶的卫生指标根源在奶牛场,但大多数奶农并没有意识到奶牛场规范挤奶程序,保护牛舍环境舒适、干净,维护和清洁挤奶设备是生产优质原料奶的关键,是奶牛场中提高牛奶卫生质量的重要途径。