牛奶体细胞数的影响因素及其调控技术

牛奶体细胞数是作为优质奶质量评判标准中的一个重要指标,关系着牛奶的品质安全。文章对牛奶体细胞的来源和危害,体细胞的影响因素及调控技术进行了综述,旨在为低体细胞数的优质奶生产提供资料参考。     

牛奶体细胞数及牛乳中酶活性与隐性乳腺炎致病菌之间的相关性

奶牛隐性乳腺炎是影响奶牛生产的重要疾病之一,通常表现为牛奶体细胞数升高,牛奶中酶的活性升高,以及牛乳中的相应成分均发生变化,从而影响牛奶的品质。因此,有必要了解牛奶体细胞数与牛乳中相关酶的活性变化以及奶牛隐性乳腺炎主要致病菌的相关性,为预防与治疗奶牛隐性乳腺炎提供理论依据。     

降低牛奶中体细胞数的营养调控

牛奶中的体细胞数(somatic cell count,SCC)是奶牛乳房健康状况的一项重要的指标,也是衡量牛乳品质的关键性指标。文章介绍了牛奶中体细胞数对牛奶成分及乳品质的影响,并总结了通过营养调控的方式降低牛奶中体细胞数、提高牛奶品质的的技术措施。     

国内外牛奶中体细胞数研究进展

目的:综述近几年国内外文献奶牛牛奶中体细胞数研究进展。方法:以体细胞数为关键词,运用中国知网(CNKI)和美国国家生物技术信息中心(NCBI)Pub Med数据库检索相关文献。结果:体细胞是奶牛牛奶中有益的天然成分,对奶牛乳房炎具有免疫防御功能。体细胞数受多种因素的影响,其中抗生素残留会引起高水平的体细胞数。应用中兽医药控制牛奶中的体细胞数、防治奶牛乳房炎可能更符合有机奶或无抗奶的要求。     

奶牛体细胞数与乳腺炎遗传相关性的研究进展

牛奶中的体细胞数和乳腺炎关系密切,当奶牛患乳腺炎时,牛奶中的体细胞数会显著增加,体细胞数成为奶牛乳腺炎的指示物。为了选育出抗乳腺炎的奶牛品种,首先应该研究体细胞数和乳腺炎之间的遗传力和遗传相关度。本文对国外奶牛体细胞数与遗传相关性的研究进行了综述。     

创造新鲜 创新生活——巴氏杀菌鲜奶论坛研讨会讲话摘录—高品质决定乳业的未来

降低牛奶中的体细胞数对成就高品质的牛奶具有非常重要的意义。把牛奶中的体细胞数和细菌数尽可能降到最低．这是我们要控制的目标。当然，牛奶中也不能有任何掺杂使假的成分。牛奶的质量首先取决于奶牛场，一旦牛奶离开奶牛场．乳品企业就没有办法把牛奶质量变得更好。     

改善养殖措施降低牛奶中的体细胞数量

正牛奶中的体细胞(SCC)是由巨噬细胞、淋巴细胞、多形核嗜中性白细胞和少量乳腺组织上皮细胞等组成的。牛奶中的体细胞数不仅反映了牛奶的质量,而且也会体现奶牛的健康情况,牛奶中体细胞数一般在20万~30万个/mL属于正常范围,过高了就说明奶牛的乳房出现疾病,如损伤、感染病原菌等,如果乳房病情恶化,体细胞数量就会急剧增高,没有了炎症,体细胞数量就会恢复到正常水平,体细胞数     

奶牛现代疾病防治新观念

1 奶牛场和奶牛现代疾病防治存在的问题 1．1 牛奶的卫生质量欠佳 牛奶生产中的卫生质量问题主要是牛奶质量偏低，如细菌总数、大肠杆菌数、嗜冷菌数超标，体细胞含量偏高，抗生素含量有时会比较高。     

体细胞数变化规律及对产奶性状和乳品质的影响

牛奶中的体细胞数(Somatic Cell Count,SCC)是指每毫升牛奶中体细胞的含量,是动物及生物体中最小的功能单位,通常由巨噬细胞、淋巴细胞和多形核嗜中性白细胞和少量的乳腺组织上皮细胞组成.正常情况下,理想的牛奶中体细胞数:第一胎≤15万/ml;第二胎≤25万/ml;第三胎≤30万/ml.若超过50万/ml,牛奶场的经济效益就立即受到损失.目前,体细胞数已经成为奶牛场衡量奶牛乳房健康状况、产奶能力、牛奶品质和奶牛保健状况的一项重要参考指标.本文对体细胞数的变化规律及对乳成份的影响做了简单描述,对控制乳中体细胞数超标提出几点应对措施. 1 泌乳牛体细胞数的变化规律及导致体细胞数升高的因素 1.1不同场对体细胞数的影响不同奶牛场的挤奶设备先进程度、挤奶程序和管理水平都有区别.     

乳中体细胞数在牛奶生产中的监控作用

1　牛乳中体细胞数牛乳中的体细胞 (SomaticCellCount,SCC) ,是指每毫升奶中的细胞总数 (挤奶前的第一把奶 ) ,多数是白细胞 (即巨噬细胞、嗜中性白细胞和淋巴细胞 ) ,其中约占牛体细胞数的 98%～ 99% ,其他 1 %～ 2 %的体细胞是乳腺组织脱落的上皮细胞 ,其数量反映了牛奶产量、质量及牛只的健康状况。在正常情况下 ,牛奶体细胞数不可能为零 ,牛奶中体细胞数一般在 2 0万～ 30万个 /mL。当乳房外伤或发生疾病产生炎症时 ,机体将大量的白细胞分泌进入乳房以清除感染 ,体细胞数一般都超过 5 0万个 /mL(Ruegg ,1 997)。因此 ,牛奶中体细胞…     

体细胞计数及其在降低奶牛乳房炎发病率方面的应用

介绍奶牛体细胞计数的概念、特征、测量方法、体细胞值所受到的影响及其在乳制品行业的应用,尤其是在降低奶牛乳房炎发病方面,用体细胞值作为一种遗传性状进行选择以提高奶牛对乳房炎抗性的应用。     

牛奶体细胞生成与乳品质量和安全的关系

牛奶体细胞数是反映奶牛乳房健康状况的重要指标之一,该指标偏高意味着奶牛可能处于亚健康或疾病状态。在奶牛正常生理状态下,牛奶体细胞的组成和数量都是基本稳定的,而当乳房外伤或疾病(如乳房炎等)发生时,牛奶体细胞数增多,产奶量降低,乳品质量下降。牛奶的品质关系到消费者的健康,因此,确保生鲜乳的质量安全是奶牛养殖工作者必须着手解决的首要问题。因此,本文围绕牛奶体细胞生成与产奶量和乳品质之间的关系展开综述,为提高乳品质量安全提供理论指导。     

Diagnostic tools to monitor udder health in dairy goats

This article discusses the use of somatic cell count (SCC) and bacteriological culture (BC) as monitoring tools to assess the udder health situation of dairy goats. Both SCC and BC can be applied for milk samples from individual goats or at bulk milk samples. The causative agent of primary concern in the dairy goat industry is Staphylococcus aureus. This pathogen strongly increases goat milk SCC. The SCC is therefore a useful test to detect S. aureus-infected goats. However, several non-infectious factors, most importantly the stage of lactation, also influence SCC, complicating the interpretation of this test. BC has a low sensitivity for the detection of S. aureus-infected goats, but is a valuable tool to obtain information on which bacterial species are responsible for udder health problems in a herd.     

基于ARIMA模型对宁夏地区奶牛体细胞数的趋势预测

本研究通过对生产性能测定（DHI）数据的挖掘与分析建立预测宁夏地区奶牛体细胞数（SCC）的模型,为奶牛乳房炎的防制提供借鉴,使得DHI数据更加有效、及时地指导奶业的发展。对2011年9月~2016年2月宁夏地区奶牛平均SCC数据进行差分使其达到平稳化,采用季节ARIMA模型对数据进行分析、拟合和预测。利用R软件的auto.arima函数计算出合适的时间序列模型ARIMA（1,1,0）（1,1,0）_[12],其AIC为-3.67。Acf检验说明残差没有明显的自相关性;Ljung-Box测试显示所有的P值>0.5,表明残差为白噪声,说明此模型可用来对未来的24个月进行预测。再利用R软件的forecast函数对2016年3月~2017年2月的数据进行预测,作出预测图。从预测的结果可以看出,宁夏地区奶牛SCC整体呈现下降趋势。2017年1月SCC最少,预测值约为25.31万个/mL;2016年3月SCC最大,预测值约为43.96万个/mL。从结果也可看出,宁夏地区奶牛SCC均大于隐性乳房炎的临界值（>20万个/mL）,说明宁夏地区还应该加大对奶牛乳房炎的防制。同时,若能及时添加新的SCC数据,就能对该数据模型进行更新,使其预测值更接近真实值,对实际生产的指导意义更大。     

Predicting the Dairy Cow Somatic Cell Number of Ningxia Area Based on ARIMA Model

Through dairy herd improvement (DHI) data analysis to predict somatic cell count (SCC) of Ningxia area in time, which providing a reference for the prevention and treatment of mastitis in dairy cows, making the DHI data more effective and timely in guiding the dairy industry production. Using the difference method to make the average cow somatic cell data form September 2011 to February 2016 stabled, then used the seasonal ARIMA model to analysis, fitting and forecasting data. The auto.arima function of R software had been used to calculate the optimal time series that finally confirmed the model was ARIMA (1,1,0)(1,1,0)_[12], AIC was -3.67. The Acf test showed that the residual had no significant autocorrelation; Ljung-Box test showed that all P-value>0.5, indicating that the residual was white noise, and this model could be used to make predication for the next 24 months. The forecast function of the R software was used to predict the dairy cows SCC from March 2016 to February 2017, and the forecast map was drawn. The predicted results showed that the SCC of the entire Ningxia area were showing a downward trend. The SCC would be the least in January 2017,and the predictive value was about 253 100 per mL. It would be the largest in March 2016, was about 439 600 per mL. The results also showed that the dairy cows SCC in Ningxia was higher than the critical value of 20 million of subclinical mastitis. It suggested that the prevention and treatment of dairy cow mastitis need to be strengthened in Ningxia area. At the same time, if the data of the dairy cows SCC was added in timely, the data model should be updated to make it more close to the true value, which would be more meaningful to the actual instruction.     

我国规模牛场奶牛个体生鲜乳体细胞数水平及影响因素探析

本研究旨在探析我国规模奶牛场奶牛个体生鲜乳体细胞数（SCC）的水平、分布和影响因素。利用SAS9.0的GLM模型,统计分析覆盖16个省（市、区）,33个规模奶牛场,23 351头中国荷斯坦牛,从2007年至2009年连续3年的225 775条奶牛个体生鲜乳SCC检测记录。结果表明：奶牛个体生鲜乳SCC的总体均值为48×104cell/mL,标准差为117×104cell/mL,个体生鲜乳SCC波动范围较大;其中,77.9%的奶牛个体,其生鲜乳SCC小于50×104cell/mL,对群体混合样生鲜乳SCC的影响系数为0.26;11.3%的奶牛个体,其生鲜乳SCC介于50×104～100×104cell/mL之间,乳房处于隐性感染状态,对群体混合样生鲜乳SCC的影响系数为0.16;10.8%的奶牛个体,生鲜乳SCC大于100×104cell/mL,理论上乳房处于临床感染状态,对群体混合样生鲜乳SCC的影响系数为0.58。奶牛个体生鲜乳体细胞数评分（SCS）呈正态分布,与奶牛个体因素（产奶量、乳脂率、乳蛋白含量、胎次和泌乳阶段）和环境因素（泌乳月份、泌乳季节）差异极显著（P〈0.01）,与奶牛养殖区域、奶牛场差异不显著（P〉0.05）。我国规模奶牛场奶牛个体生鲜乳SCC主要在50×104cell/mL以下,依据影响参数能实现对生鲜乳SCC水平的调控。     

Influence of race and crossbreeding on casein micelles size

Casein (CN) micelles are colloidal aggregates of protein dispersed in milk, the importance of which in the dairy industry is related to functionality and yield in dairy products. The objective of this work was to investigate the correlation of milk CN micelles diameter from Holstein and Zebu crossbreds with milk composition (protein, fat, lactose, total and nonfat solids and milk urea nitrogen), somatic cell count (SCC), age, lactation stage and production. Average casein micelles diameters of milk samples obtained from 200 cows were measured using photon correlation spectroscopy and multiple regression analysis was used to find relationship between variables. CN micelle diameter, SCC and nonfat solids were different between animals with different Holstein crossbreed ratios, which suggests influence of genetic factors, mammary gland health and milk composition. Overall, results indicate the potential use of CN micelle diameter as a tool to select animals to produce milk more suitable to cheese production.     

线性模型对影响奶牛产奶性能的主要相关因素分析

利用一般线性模型研究各种因素对奶牛产奶性能的影响。牛场、胎次和产犊季节对奶牛产奶量影响差异极显著(P0.01),随着奶牛胎次的增加,奶牛产奶量增加;夏季产犊的奶牛产奶量最低,冬季产犊的最高;体细胞计数对奶牛产奶量没有显著性影响(P0.05),但随着体细胞数的增加,产奶量下降。牛场、胎次和体细胞计数对乳脂率有极显著的影响(P0.01),第三牛场平均乳脂率为4.38%,显著高于其他三个牛场;随着胎次的增加,乳脂率有下降趋势;随体细胞数增加,乳脂率升高;产犊季节对奶牛乳脂率没有显著影响(P0.05)。牛场、产犊季节和体细胞数对乳蛋白率的影响极显著(P0.01),体细胞数增加,乳蛋白率升高;夏季和秋季产犊的奶牛乳蛋白率较高,春季和冬季较低;胎次对乳蛋白率没有显著影响(P0.05)。表型相关分析表明:SCC与产奶量呈显著负相关(r=-0.158,P0.05),SCS与产奶量相关性接近显著水平(r=-0.140,P=0.055)。SCC/SCS与乳脂率、乳蛋白率呈正相关,但未达到显著性水平(P0.05)。     

Insights into udder health and intramammary antibiotic usage on Irish dairy farms during 2003-2010

ABSTRACT: By international standards, Ireland is a relatively small dairy producer. However, the industry plays a critical role to the national economy, accounting for approximately 3% of national gross domestic product. This paper presents insights into udder health and intramammary antibiotic usage on Irish dairy farms during 2003-2010, based on data from several sources. Three data sources were used, including data on milk recording data, intramammary antibiotic sales and animal health assessment. The milk recording data included a single unadjusted herd-level somatic cell count (SCC) value for each herd at each milk recording, being the arithmetic mean of cow-level SCC of each cow at that recording, weighted by cow-level yield. These data were used to calculate the percentage of herds each month where the unadjusted herd SCC exceeded 200,000 and 400,000 cells/mL. Two logistic generalised estimating-equations (GEE) models were developed, the outcome variable being either the probability that the monthly SCC of a herd was greater than 400,000 cells/mL or less than or equal to 200,000 cells/mL. Spring herds had a lower probability of a high SCC (> 400,000 cells/mL) during February to October compared to non-Spring herds but a higher probability between November to January. The odds of a high SCC were greater in 2005, 2006, 2009 and 2010 but less in 2007 and 2008 compared to 2004. Smaller herds had higher odds of having a high SCC compared to larger herds. We present the number of intramammary tubes and the quantity of active substance (kg) sold annually in Ireland during 2003-2010. We infer an incidence of clinical mastitis of 54.0 cases per 100 cow-years at risk, assuming 4 tubes per treatment regime, one affected quarter per cow, tubes restricted to clinical cases only and 100% of treated cases considered new cases, based on data collected on sales of in-lactation intra-mammary antibiotics. With differing assumptions, this estimate varied between 25.8 and 77.0 cases per 100 cow-years at risk. Using data on sales of dry cow therapy intra-mammary antibiotics, we also infer that most Irish dairy farmers use blanket dry cow therapy. It is important that Ireland has an objective understanding of current levels of udder health, to facilitate benchmarking and improvement into the future. Udder health is a concern on a number of Irish dairy farms. High SCC results were present throughout the year, but more marked towards the start and end of each milking season. Animal Health Ireland recently commenced a major national programme, CellCheck, in collaboration with a broad range of stakeholders, to support national SCC improvement. In this paper, relevant European and national legislation is also reviewed.     

Effect of farm characteristics and practices on hygienic quality of ovine raw milk used for artisan cheese production in central Italy

A survey on ovine dairy farms directly transforming own‐produced milk, in the Italian Marche region, was carried out to assess flock and milking practices that may influence milk hygienic‐sanitary conditions. A census survey established that 24 dairy farms were located in this region. Bulk milk samples were collected throughout the milking period in each dairy farm in 2013. Analyzed variables were: (i) chemical parameters such as fat, protein and lactose content, dry matter and pH; and (ii) total bacterial (TBC) and somatic cell counts (SCC). Chemical parameter values were in agreement with published data while, geometric mean (GM) log₁₀ SCC was 5.91 and TBC GM was 57 978 colony forming units/mL, in compliance with Eropean Union criteria. A positive correlation was found between SCC and TBC when GMs of all farm data were considered (Spearman's rho = 0.7925; P = 0.0001). Statistical analysis did not show significant correlation between SCC or TBC GM and dairy farm principal characteristics. Although SCC levels detected in the present study should suggest the need to implement mastitis control programs, Marche's dairy sheep flocks revealed a good hygienic condition level. This is an important aspect in implementing safety for end users of the final product.