牛乳中体细胞数与乳成分和部分理化性质的相关性研究

对呼和浩特郊区一牧场30头荷斯坦乳牛进行6个月单个采样,共得452个有效样本,检测乳样包括:体细胞数、脂肪、蛋白质、乳糖、总固形物、细菌总数、比重、黏度、电导率、氯糖数、滴定酸度和pH值。结果表明,蛋白质质量分数与牛乳中的体细胞数(Somatic CellCount,SCC)SCC呈显著正相关(P<0.05);乳糖含量与SCC呈显著负相关(P<0.001);脂肪、总固形物质量分数、电导率、氯糖数与SCC呈极显著正相关(P<0.001)。细菌总数、比重、黏度、滴定酸度、pH值与SCC的相关性不显著。从5～10月,乳中体细胞数有逐渐降低趋势,9月骤然升高,其中5月和9月样品平均体细胞数较高,分别为78×104 mL-1和96×104 mL-1。10月份样品平均体细胞数最低为28×104 mL-1。     

水牛乳冰点与理化性质相关性的研究

对不同品种水牛乳进行为期一年的随机抽样测定,分析水牛乳冰点值与季节以及各主要理化性质间的相关性。结果表明,尼里-拉菲水牛乳一年中冰点均值范围为-0.536^-0.528℃之间;麽拉水牛乳为-0.537^-0.528℃之间;三品种杂交水牛乳为-0.543^-0.531℃之间;一代杂交水牛乳为-0.548^-0.533℃之间,各品种水牛乳冰点均值最低值出现在7、8月份,水牛乳的冰点值与水牛乳滴定酸度、蛋白质、脂肪、总固形物、乳糖+灰分总量存在Pearson极显著负相关性（p<0.01）,与水牛乳水分含量存在Pearson极显著正相关性（p<0.01）,与水牛乳中的体细胞数无显著相关性（p>0.05）。      

酒精阳性水牛乳乳成分及理化性质的研究

本研究连续一年观测了摩拉水牛、尼里-拉菲水牛、一代杂水牛和三品杂水牛4个种水牛乳64%的不同季节的酒精阳性发生率、乳成分、理化性质,并比较了酒精阳性乳、阴性乳与乳样总体的差异。结果表明,纯种河流型水牛(摩拉水牛、尼里-拉菲水牛)乳酒精阳性率低于两个杂交水牛(三品杂水牛、一代杂水牛),各品种水牛乳均以2~4月和8~10月的阳性率为最高。低酸度酒精阳性乳(12~18oT)占据了酒精阳性乳的52.9%~64.1%。酒精阳性乳的乳蛋白、乳固体、非脂乳固体、酸度均显著高于阴性乳和乳样总体平均值,但冰点低于乳样总体平均值。可见不同品种水牛乳不能用同一酒精浓度进行检验;酒精阳性率可反映水牛应激或营养状况;较高的乳蛋白、非脂乳固体、总乳固体、酸度以及较低的冰点是酒精阳性水牛乳的特征;酸度和冰点是品种间酒精阳性率差异的主要因素。     

牛乳体细胞数的检测方法

讨论了体细胞数与乳腺炎的关系以及体细胞数对牛乳成分及产奶量损失的影响。主要介绍了4种常用的体细胞数的检测方法，即加利福尼亚细胞数测定法(CMT)，威斯康辛乳腺炎试验(WMT)，电子体细胞计数法(DHI)和直接镜检法(CMSCC)。     

ATP生物发光技术快速检测牛乳体细胞数

探索利用ATP生物发光技术快速检测牛乳体细胞数的可行性.利用ATP生物发光技术测定牛乳体细胞ATP浓度,根据体细胞中ATP的浓度与体细胞数成正比的原理,推算出牛乳中的体细胞数,并与显微镜计数法对比,分析两种方法之间的相关性.结果表明:ATP生物发光技术的检测结果与显微镜计数法有很好的相关性,是一种快速、简便的检测牛乳体细胞的方法.     

牛乳中体细胞数与脂肪酸含量的相关性分析

目的：研究牛乳中体细胞数（somatic cell count,SCC）对乳脂肪酸含量的影响。方法：采集474 头处于泌乳早期（30～100 d）的中国荷斯坦奶牛乳样,测定乳中SCC及各种脂肪酸单体的含量,分析乳中SCC对脂肪酸相对含量的影响及相关性。结果：SCC极显著影响乳中C4∶0、C16∶1、cis9, trans11-CLA和C18∶3 n3脂肪酸单体的含量（P＜0.01）。同时,随着乳中SCC的升高,多不饱和脂肪酸（polyunsaturated fatty acid,PUFA）的相对含量也显著增加（P＜0.05）。相关性分析显示乳中SCC与PUFA含量呈极显著正相关（P＜0.01）,与短链脂肪酸含量呈显著负相关（P＜0.05）。结论：研究结果初步揭示了乳中SCC与乳脂肪酸相对含量的关系,为进一步揭示SCC对牛乳品质的影响提供了依据。     

鲜牛乳中体细胞数检测方法探讨

体细胞数是衡量鲜牛乳卫生状况的重要指标之一，体细胞数的提高会使牛乳中蛋白酶和解脂酶升高，使乳清蛋白含量升高，酪蛋白含量降低，从而使乳制品的货架期缩短，乳制品的风味发生改变。本文通过显微镜检测法、4％NaOH凝乳试验法两种方法的比较试验，探讨在实际生产中鲜牛乳体细胞敖的最佳检测方法及检测时限，以帮助乳制品生产企业加强对牧场的监管和在收购鲜牛乳的过程中快速、准确评判鲜牛乳的品质，确保生产出优质的乳制品供应市场。     

牛乳体细胞数与内源酶的关系

对某牧场30头荷斯坦奶牛的434个奶样进行体细胞数、NAG酶、过氧化物酶、过氧化氢酶、脂酶、游离脂肪酸含量的测定。结果表明,夏季牛乳中体细胞数高于秋季,九月份达到最高水平;随着牛乳体细胞数升高,NAG酶、过氧化物酶、过氧化氢酶、脂酶、游离脂肪酸含量变化极显著（P〈0.01）;除过氧化物酶与脂酶呈显著正相关（P〈0.05）外,体细胞数、其他内源酶及游离脂肪酸间均呈极显著正相关（P〈0.01）。     

牛乳乳汁电导率变化与体细胞数相关关系的研究

本试验以随机采集的奶牛乳样为研究对象,对乳样的电导率与体细胞数进行了测定与分析.结果显示, 体细胞在2×105/mL～5×105/mL区间时, 奶牛乳汁电导率值在0.40～0.55mho/m之间;体细胞在5.0×105/mL以上时, 奶牛乳汁电导率0.6mho/m以上.结果表明,牛乳电导率的变化与体细胞的含量呈正相关,可利用牛乳体细胞数与电导率变化的相关关系来准确判断奶牛是否有隐性乳房炎.     

高压对牛乳理化性质和成分的影响

高压食品加工是一种非热杀菌技术,是指在室温或低温下用100-800MPa高压处理食品。与传统的热杀菌比较,它具有很多优点,不仅能杀死微生物钝化酶类,而对食品的营养成分和感官品质改变较小。本文综述了高压处理对牛奶物理化学性质和成分的影响。     

不同品代水牛奶理化性质的研究

研究了摩拉水牛、尼里-拉菲水牛、一代杂交水牛、二代杂交水牛、高代杂交水牛等5个品代水牛奶的理化性质。结果表明,杂交水牛奶的全乳固体、乳脂肪、蛋白质、乳糖的平均值均高于纯种摩拉水牛和尼里-拉菲水牛,杂交水牛奶的灰分总体高于纯种河流型水牛,在杂交水牛中,由高到低的顺序为:一代杂、二代杂、高代杂。纯种摩拉水牛和尼里-拉菲水牛之间的全乳固体、乳脂肪、蛋白质和乳糖差异不显著(P>0.5),而杂交水牛的全乳固体、乳脂肪、蛋白质和乳糖与纯种河流型水牛相比,差异显著(P<0.05)。各品代水牛之间钙、磷含量的差异不显著(P>0.5),但从总体上看,杂交水牛的含量要高于纯种河流型水牛,杂交水牛中又以杂交一代水牛为最高。各品代水牛奶的各种氨基酸含量随蛋白质总量的变化而变化,除杂交水牛之外,各品代水牛之间的各种氨基酸比例比较接近。各品代水牛奶的密度平均值变化范围为1.028～1.032;酸度平均值变化范围是15.36～19.82°T;pH值的平均值变化范围从6.46～6.88;黏度平均值的变化范围由2.44～3.11 Pa.s。     

高体细胞牛乳的性质及对加工的影响

阐述了高体细胞牛乳化学成分及微生物的变化，论述了产生这些变化的原因以及这些变化对乳制品加工、贮藏和销售所带来的一系列不良影响。主要表现在高体细胞牛乳中脂肪氧化酶含量升高，引起游离脂肪酸含量上升，牛乳易产生酸败味；牛孔中蛋白水解酶以及血纤维蛋白溶酶含量增加，引起乳蛋白水解，造成干酪产量下降，凝固型酸乳凝乳不坚固，UHT灭菌孔保质期缩短等质量缺陷；牛乳中盐类比例失调，使牛孔热稳定性降低，凝固型酸奶的凝乳疏松且易碎裂，乳清易析出；乳中过氧化氢酶和过氧化物酶含量升高，使产品品质不稳定，风味欠佳；牛乳中有害微生物含量增加，降低产品的食用安全性；治疗乳房炎所用的抗生素残留阻碍乳酸菌的发酵过程。这些变化都可能对乳制品的生产造成巨大损失。     

体细胞数对乳的影响及其控制措施

分析了乳中体细胞升高的原因，阐述了高体细胞数对乳的组成和乳制品加工的影响，并简要的说明了降低体细胞数的控制措施。     

Differential leukocyte count method for bovine low somatic cell count milk

Whereas many differential leukocyte count methods for high somatic cell count (SCC) milk from mastitic cows are available, only a few have been developed for low SCC milk. We have developed a flow cytometric differential leukocyte count method for low SCC milk. The procedure consists of 1) 1.5 ml of diluted milk sample (30%, vol/vol dilution with PBS), 2) centrifugation, 3) leukocyte labeling with SYTO 13 and 4) flow cytometric analysis. Four major leukocyte populations can be clearly identified in the green fluorescence-side scatter dot plot: lymphocytes and monocytes (LM), polymorphonuclear neutrophils (PMN), mature macrophages (Mphi), and cells with apoptotic features based on chromatin condensation and nuclear fragmentation. The optimal processing temperature was 20 degrees C. Significant differences among samples with similar differential leukocyte counts were found. Storage of milk samples during 2 d at 7 degrees C had no effect on differential leukocyte count. Using the new method, differential leukocyte count was performed in low SCC milk samples from cows in early, mid, and late lactation. In accordance with previous studies, PMN and Mphi percentages were lower and LM percentages were higher in early lactation than in the other stages of lactation. The percentage of cells with apoptotic features was higher in early lactation than in mid and late lactation. In conclusion, a rapid, simple, accurate, and reproducible standard procedure was developed to determine the differential leukocyte count (Mphi, PMN, LM, and cells with apoptotic features) of bovine low SCC milk.     

Correlation between standard plate count and somatic cell count milk quality results for Wisconsin dairy producers

The objective of this study was to determine if a correlation exists between standard plate count (SPC) and somatic cell count (SCC) monthly reported results for Wisconsin dairy producers. Such a correlation may indicate that Wisconsin producers effectively controlling sanitation and milk temperature (reflected in low SPC) also have implemented good herd health management practices (reflected in low SCC). The SPC and SCC results for all grade A and B dairy producers who submitted results to the Wisconsin Department of Agriculture, Trade, and Consumer Protection, in each month of 2012 were analyzed. Grade A producer SPC results were less dispersed than grade B producer SPC results. Regression analysis showed a highly significant correlation between SPC and SCC, but the R² value was very small (0.02–0.03), suggesting that many other factors, besides SCC, influence SPC. Average SCC (across 12 mo) for grade A and B producers decreased with an increase in the number of monthly SPC results (out of 12) that were ≤25,000 cfu/mL. A chi-squared test of independence showed that the proportion of monthly SCC results >250,000 cells/mL varied significantly depending on whether the corresponding SPC result was ≤25,000 or >25,000 cfu/mL. This significant difference occurred in all months of 2012 for grade A and B producers. The results suggest that a generally consistent level of skill exists across dairy production practices affecting SPC and SCC.     

Estimating milk loss based on somatic cell count at the cow and herd level

There is a direct relationship between elevated somatic cell count (SCC) in an individual cow milk production and milk loss. This relationship has been used at the herd level to estimate an overall herd milk loss due to subclinical mastitis and to use recovery of this lost milk as a financial benefit to cover the cost of intervention strategies to improve milk quality. The objective of this study was to estimate the recoverable milk revenue on a per cow basis for herds moving from one herd average SCC level to a newer, lower level. Test-day records from 1,005,697 dairy cows in 3,741 herds between 2009 to 2019 were used. Milk yield loss for each cow in each herd on test day was estimated using a mixed effects regression equation, and then summed to estimated total herd milk loss. These herd average daily milk loss estimates were then related to the bulk tank SCC, and the distribution of underlying individual cow SCC were examined. The distributions in daily herd milk loss for various bulk tank SCC values were generated, and estimates of recoverable milk loss were generated to simulate a herd moving from their current bulk tank SCC to a new lower level. The results indicate that estimates of total herd milk yield loss vary with the distribution of cow-level SCC and parity within the herd, so it is imperative that milk loss be calculated on a per cow basis. Further, the recoverable milk loss estimates based on moving to a lower bulk tank SCC where milk loss is still occurring was relatively small compared with the traditional assumption that all milk loss would be recovered, and less than most herd owners and advisors would expect.     

Lactoperoxidase activity in milk is correlated with somatic cell count in dairy cows

Lactoperoxidase (LPO) is a milk protein with antimicrobial function. The present study was undertaken to examine the correlation between LPO activity and somatic cell count (SCC) in milk to use LPO activity as an indicator of mastitis. Composite milk of 36 cows and quarter milk of 3 cows were collected once per week from 0 to 300 d postpartum and twice per day for 1 wk, respectively. For the measurement of LPO activity, milk was mixed with tetramethylbenzidine solution and incubated at 37°C for 30 min, followed by the measurement of optical density. When only milk with low SCC (132 ± 12 × 10³ cells/mL) was used, a significant decrease in LPO activity was detected in primiparous cows from 0 to 4 mo postpartum. Lactoperoxidase activities of primiparous cows in mo 1, 2, and 3 postpartum were significantly higher than those in multiparous cows. When composite milk was divided based on LPO activity, the SCC was significantly higher in the groups with LPO activity >5 and from 3 to 3.9 U/mL in the second- and fourth-parity cows, respectively, compared with the group with LPO activity <2 U/mL. Extremely high SCC were found in the ≥fifth-parity cows, even in low-LPO activity groups. In the case of quarter milk, higher LPO activity was associated with increased SCC in all 3 cows. The percentage of quarter milk samples with high SCC (4,062 ± 415 × 10³ cells/mL) increased with an increase in the LPO activity. The percentage of quarter milk samples with high SCC was 50.0 to 100% in the milk with LPO activity ≥5 U/mL. These results indicate that the correlation of LPO activity to the SCC in bovine milk may point to the potential use of the former as an indicator of SCC.     

Mammary pathogens and their relationship to somatic cell count and milk yield losses in dairy ewes

A total of 9592 samples of half udder milk were collected monthly throughout lactation for bacteriological and somatic cell count (SCC) study from 1322 Churra ewe lactations from seven separate flocks enrolled in the recording scheme of the National Association of Spanish Churra Breeders in the Castile-Le6n region of Spain. Statistical analyses were carried out from a mixed model with random factor half udder or ewe for repeated measures. Test of significance of fixed effects of this mixed model showed significant effects of organisms, flock, parity, lactation stage, and birth type on SCC. Special reference must be made to novobiocin-sensitive coagulase-negative staphylococci, which represented more than 50% of the isolates and which elicited SCC geometric means of around 106/ml. In addition, the analysis of 4352 monthly test-day records for milk yield, SCC, and bacteriology showed that the ewes that were uninfected and infected by minor pathogens had the lowest SCC and the highest milk yields, whereas those infected by major pathogens had high SCC and milk yield losses between 8.8 and 10.1% according to the uni- or bilateral character of the infection. Finally, ewes infected by novobiocin-sensitive coagulase-negative staphylococci elicited SCC values similar to those of infections by major pathogens and milk yield losses ranging between those caused by minor and major pathogens. As a result, emphasis should be put on prevention of subclinical mastitis, particularly mastitis caused by novobiocin-sensitive coagulase-negative staphylococci in dairy sheep herds to improve microbiological and hygienic milk quality and to minimize losses in milk yield.     

Importance of the sampled milk fraction for the prediction of total quarter somatic cell count

This study investigated the changes in somatic cell counts (SCC) in different fractions of milk, with special emphasis on the foremilk and cisternal milk fractions. Therefore, in Experiment 1, quarter milk samples were defined as strict foremilk (F), cisternal milk (C), first 400 g of alveolar milk (A1), and the remaining alveolar milk (A2). Experiment 2 included 6 foremilk fractions (F1 to F6), consisting of one hand-stripped milk jet each, and the remaining cisternal milk plus the entire alveolar milk (RM). In Experiment 1, changes during milking indicated the importance of the sampled milk fraction for measuring SCC because the decrease in the first 3 fractions (F, C, and A1) was enormous in milk with high total quarter SCC. The decline in SCC from F to C was 50% and was 80% from C to A1. Total quarter SCC presented a value of approximately 20% of SCC in F or 35% of SCC in C. Changes in milk with low or very low SCC were marginal during milking. Fractions F and C showed significant differences in SCC among different total SCC concentrations. These differences disappeared with the alveolar fractions A1 and A2. In Experiment 2, a more detailed investigation of foremilk fractions supported the findings of Experiment 1. A significant decline in the foremilk fractions even of F1 to F6 was observed in high-SCC milk at concentrations >350 × 10³ cells/mL. Although one of these foremilk fractions presented only 0.1 to 0.2% of the total milk, the SCC was 2- to 3-fold greater than the total quarter milk SCC. Because the trait of interest (SCC) was measured directly by using the DeLaval cell counter (DCC), the quality of measurement was tested. Statistically interesting factors (repeatability, recovery rate, and potential matrix effects of milk) proved that the DCC is a useful tool for identifying the SCC of milk samples, and thus of grading udder health status. Generally, the DCC provides reliable results, but one must consider that SCC even in strict foremilk can differ dramatically from SCC in the total cisternal fraction, and thus also from SCC in the alveolar fraction.     

乳体细胞数对干酪生产的影响

论述了原料乳中体细胞数对干酪加工、成熟和产量的影响,以期为干酪生产提供理论参考.