我国生牛乳蛋白质含量现状及影响因素调查

目的研究我国当前生牛乳的蛋白质含量和影响因素。方法分析覆盖17个省(市、自治区)18个乳品企业2014年1月—2015年2月连续12个月共30 531份生牛乳样品蛋白质含量数据,利用SPSS 19.0软件进行数据处理。结果生牛乳中蛋白质的平均含量为(3.14±0.15)g/100 g,规模化牧场、养殖小区和散户的生牛乳中蛋白质平均含量分别为(3.18±0.14)、(3.07±0.12)和(3.00±0.14)g/100 g,南方、西部、华北、东北内蒙古和大城市周边地区生牛乳蛋白质平均含量分别为(3.17±0.14)、(3.16±0.14)、(3.14±0.17)、(3.09±0.17)和(3.09±0.10)g/100 g,春、夏、秋、冬季生牛乳蛋白质平均含量分别为(3.09±0.13)、(3.07±0.13)、(3.21±0.13)、(3.20±0.14)g/100 g。结论我国生牛乳的蛋白质含量有八成以上达到3.0 g/100 g。养殖模式、养殖区域、季节和月份均会影响生牛乳中的蛋白质含量。乳脂肪、非脂乳固体、相对密度与乳蛋白含量呈正相关。     

超高压杀菌工艺对生牛乳中微生物的影响

超高压技术不但可以达到热力杀菌同样的效果,而且可以最大限度保留牛乳中的营养成分。试验研究了超高压杀菌工艺对牛乳品质的影响。在100～600 MPa压力下对牛乳采用连续式加压和交变式加压方式处理一段时间后,测定其微生物和理化指标的变化,并与巴氏杀菌工艺进行对比。结果表明,压力越高,保压时间越长,以灭菌压力、保压时间为变量,研究了超高压处理对生牛乳中菌落总数及大肠菌群的杀灭效果。结果表明,当低压200MPa,低压保压时间5 min,高压500 MPa,高压保压时间30 min时,大肠菌群全部被杀灭,菌落总数致死率达99.91%。因此,超高压处理生牛乳对生牛乳中的微生物有很好的杀灭作用。     

食品安全国家标准中菌落总数测定方法影响因素分析

目的 对GB 4789.2-2016菌落总数测定方法的重要影响因素进行了系统分析。方法 使用大肠埃希氏菌ATCC25922、金黄色葡萄球菌ATCC6538和枯草芽孢杆菌ATCC6633的新鲜菌株和冻干样品评价PCA培养基的倾注温度(45 ℃和50 ℃)、已处理样品放置时间(0~90 min)、培养基倾注体积(12~20 mL)、培养基品牌(7种, 编号A-G)的差异对菌落总数计数结果的影响。结果 已处理样品放置90 min后, 菌落总数的计数结果显著性低于放置0 min(P=0.023)和15 min(P=0.021)样品的计数结果; 使用品牌B培养基得到的菌落计数结果显著性低于使用品牌F培养基得到的结果(P=0.024)。PCA培养基倾注温度(45 ℃和50 ℃)和倾注体积(12~ 20 mL)对菌落总数计数结果的影响未见显著性(P>0.05)。结论 需细化国标菌落总数测定方法检验流程, 研发并引入可靠的参比培养基, 对检验过程予以高度规范化, 以保障检验数据稳定、可靠。     

超高压处理对生牛乳中微生物的影响

作为非热杀菌技术的一种,超高压技术在保证灭菌效率的同时能有效保留牛乳中的营养物质.本实验主要以工作压力、保压时间和保温时间3个因素为变量,通过单因素和正交试验,研究不同条件下超高压处理对生牛乳中微生物的杀灭效果.结果表明,超高压处理能够显著杀灭生牛乳中的微生物,且灭菌效果会随着工作压力和保压时间的增加而有所提升,保温时...     

阻抗法快速分析牛奶中的菌落总数

以电导、总阻抗、双电层电容、培养介质电容、阻抗角作为检测参数,比较含初始菌数不同的阻抗测试管的阻抗变化率曲线,结果阻抗角不适于作为阻抗法快速分析牛奶中菌落总数的检测参数。将检出时间DT值和平板计数法得到的菌落总数的对数值lgC用SAS做线性回归,结果电导、总阻抗、双电层电容之间存在线性相关。用Δ=lg(C0/CSPC)=lg(C0)-lg(CSPC)值分析阻抗法的检测误差,结果由电导、总阻抗作为检测参数得到的菌落总数值符合实际情况。用阻抗法快速分析牛奶中的菌落总数时,分析FPR、FNR随DTTH的变化趋势,DTTH值分别选440min(电导和总阻抗)和410min(双电层电容)。     

白砂糖中菌落总数超标原因分析

通过实验分析白砂糖中菌落总数指标超标的原因,并制定控制措施。     

食品微生物检验中菌落总数测定的分析

菌落总数是评价食品等许多产品的卫生情况、新鲜程度及污染程度的最常用的指标之一。通过菌落总数的测定可以在一定程度上判断产品卫生情况的优劣,在科学发展和检验技术进步的今天,对检验数据的准确性和可靠性提出了更高的要求。要保证检测结果的准确性和可靠性,真实准确的反映所检样品中细菌污染的程度,检验过程的每一环节都至关重要。     

食品中菌落总数和大肠菌群检验研讨

在对食品安全进行检验的工作中,菌落总数与大肠菌群的检验是重点工作内容,只有不断提高检验效率与质量,才能有效保证食品安全.因此,食品检测人员必须重视对菌落总数与大肠菌群的检验,明确检验工作目标与方向,提高检验操作的科学性与合理性,促进菌落总数与大肠菌群检验水平的提升.本文将对食品中菌落总数和大肠菌群的检验要求进行分析,探...     

红肠不同生产环节中菌落总数和大肠菌群数量变化规律初步研究

目的 研究红肠不同生产环节、不同环境中菌落总数和大肠菌群数的变化规律。方法 用国标方法检测红肠各个工序不同环境中的菌落总数和大肠菌群数, 并用统计学软件SSPS处理结果。结果 建立菌落总数和大肠菌群数量变化规律模型。红肠加工不同环境中菌落总数变化规律的非线性拟合方程为 大肠菌群数变化规律的非线性拟合方程为 结论 本研究对于控制红肠中微生物数量, 保证其安全卫生具有重要意义。     

牦牛屠宰过程中菌落总数和大肠菌群污染状况的分析

为了掌握牦牛屠宰过程中菌落总数和大肠菌群的污染状况,本实验对甘肃玛曲某牦牛屠宰场在牦牛屠宰过程中的屠宰前、屠宰中和分割后三个阶段以及牦牛胴体等14个采样点进行采样,进行菌落总数和大肠菌群的测定。研究发现,屠宰前的各采样点中,菌落总数在5.45logCFU/g以上,大肠菌群在3.25logCFU/g以上;屠宰中的各采样点中,菌落总数在3.37logCFU/cm2以上,大肠菌群在1.63logMPN/100cm2以上;在分割后的各采样点中,菌落总数在3.68logCFU/cm2以上,大肠菌群在1.74logMPN/100cm2以上;在胴体的剥皮、劈半和分割三个时期中,分割后的菌落总数(3.49logCFU/cm2)和大肠菌群(1.61 logMPN/100cm2)污染最严重,剥皮后的菌落总数(2.47logCFU/cm2)和大肠菌群(1.53logMPN/100cm2)污染最小。结果表明,屠宰前环境污染最严重,胴体随着剥皮、劈半和分割的进行,菌落总数显著增加,分割后胴体的大肠菌群显著高于剥皮和劈半。      

不同体细胞数的原料乳品质变化的比较研究

通过分析比较5组不同体细胞数(SCC)原料乳的主要成分和特性(蛋白质、脂肪含量、酪蛋白的含量等)、脂肪分解情况(脂肪酶活力、游离脂肪酸及其占总脂肪的比例)以及蛋白质水解程度(水溶性氮、非蛋白氮占总氮的比例以及酪蛋白构成)的变化情况,探讨不同SCC对原料乳品质的影响。结果表明：当SCC小于4.0×105个/mL时,原料乳的成分没有显著的差异(P＞0.05);随着SCC的增大,原料乳的脂肪水解程度增强,但SCC小于4.0×105个/mL的两组原料乳的脂肪水解程度没有显著差异(P＞0.05);不同SCC原料乳的酪蛋白构成表现不同,其蛋白质水解程度(WSN/TN,NPN/TN)随SCC的增大而增加,但SCC在4.0×105 个/mL以下的两组原料乳的蛋白水解程度没有显著差异(P＞0.05)。     

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.     

对GB 19301-2010《生乳》中蛋白质和菌落总数的指标验证和建议

目的完成\"GB 19301-2010《生乳》跟踪评价项目\"。方法 对陕西省7家乳企使用的原料生乳进行了7次采样,样本量为111份,其中夏季51份,冬季60份,采用GB 5009.5和GB 4789.2分别对样本中的蛋白质和菌落总数进行了测定。结果 所有样本的蛋白质含量都是合格的,冬季、夏季生乳蛋白质含量分别均不低于3.6 g/100 g、2.8 g/100 g,其中16%的夏季生羊乳蛋白质检测值为2.8 g/100 g,是\"生乳蛋白质指标\"的界限值。所有样本中,只有夏季4份样本的菌落总数超过了2.0×106CFU/m L的指标界限值,冬季、夏季生乳菌落总数平均值分别低于1.0×105CFU/m L、1.0×106CFU/m L。结论 GB 19301规定的生乳蛋白质、菌落总数指标值是科学合理的,建议将夏季生羊乳的蛋白质指标修订为≥2.6 g/100 g。     

平板显色法同时计数生乳中的大肠菌群和菌落总数

为提高大肠菌群和菌落总数的计数效率,选用2-硝基苯基-β-D-吡喃半乳糖苷作为平板培养基中的显色底物,利用大肠菌群lacZ基因编码的β-半乳糖苷酶将其分解产生黄色化合物,使得大肠菌群菌落区分于其他菌株,实现大肠菌群和菌落总数的同时计数,优化该培养基配方,评估培养基的特异性、准确性以及在生乳中的应用效果。最终确定该培养基配方：胰蛋白胨12.5 g/L、酵母浸粉2.5 g/L、磷酸氢二钾2.75 g/L、磷酸二氢钾1.75 g/L、氯化钠5.0 g/L、琼脂15.0 g/L,2-硝基苯基-β-D-吡喃半乳糖苷0.1 g/L,pH值为7.0。在此基础上,添加0.05 g/L异丙基-β-D-硫代半乳糖苷或2.0 g/L乳糖均能够增强菌落显色效果,而葡萄糖则会抑制黄色化合物生成。特异性实验中,仅大肠菌群菌落颜色呈黄橙色,其他菌株则呈乳白色。在生乳样本中,该培养基与国标方法对于大肠菌群和菌落总数的计数结果基本一致。因此,该复合显色培养基能够大大提高大肠菌群和菌落总数的计数效率,降低检测成本,为生乳的卫生指标检测提供一种可行方案。     

Application of a new portable microscopic somatic cell counter with disposable plastic chip for milk analysis

The somatic cell count (SCC) is one of the international standards for monitoring milk quality, and it is a useful indicator of mastitis. The current reference method for determining the SCC in raw milk is direct microscopic analysis, but this method requires well-trained staff to maintain its accuracy and reproducibility. To overcome these inconveniences, we developed a portable system (the C-reader system) that utilizes the capillary flow of a microfluidic chamber by surface modification of the hydrophilicity. The microfluidic technology of disposable microchips allows for low consumption of reagents, and a combination of ready-to-use reagents makes the daily work easier. The repeatability test of the C-reader using 10 composite bovine milk samples satisfied the recommended values for SCC equipment. In addition, an acceptable accuracy level of the natural logarithmic-transformed SCC [ln(SCC/1,000): ± 0.059 to 0.112] was achieved using composite raw milk samples and various somatic cell standard solutions from the American Eastern Laboratory and the Korean National Veterinary Research and Quarantine Service. After testing 875 composite milk samples, the C-reader showed a high correlation coefficient (R² = 0.935 to 0.964) and a low mean difference value in log-transformed SCC (−0.088 to 0.004) compared with 3 automatic commercialized somatic cell counters (Fossomatic 4000, Somacount 150, and Somascope). In conclusion, the C-reader system is a new, easy-to-use automatic on-farm method with acceptable repeatability and accuracy for measuring SCC in large dairies and smaller laboratories.     

生物发光快速测定生乳菌落总数的方法

为消除利用ATP生物发光法测定生乳菌落总数时非细菌ATP对测定结果的干扰,建立了一种样品前处理方法。利用ATP生物发光法对经过前处理的生乳样品进行检测,结果表明,生乳菌落总数对数值与生乳细菌ATP发光对数值呈现较好的线性关系(R2=0.982),相关程度为显著相关(P<0.01),说明该前处理方法能够有效排除非细菌ATP的干扰,有利于提高ATP生物发光法定量测定生乳菌落总数准确性。     

Short communication: Comparison of bulk milk, yield-corrected, and average somatic cell counts as parameters to summarize the subclinical mastitis situation in a dairy herd

In this study, the correlation was determined between the prevalence of high cow-level somatic cell count (SCC >250,000 cells/mL), a summary of the subclinical mastitis situation in a dairy herd, and 3 average herd SCC parameters: bulk milk SCC (BMSCC), yield-corrected test-day SCC (CHSCC), and the arithmetic average test-day SCC (HSCC) of the lactating herd. The herd prevalence of cows with an SCC of >250,000 cells/mL was calculated by using Dairy Herd Improvement data. Herds were included if BMSCC was sampled within 2 d of the Dairy Herd Improvement test day and if the BMSCC did not exceed 400,000 cells/mL. The interval between sampling, 0, 1, or 2 d, did not significantly influence the correlation between BMSCC and the prevalence of high SCC. The correlations between the prevalence of high SCC and BMSCC, yield-corrected test-day SCC, and HSCC, examined by using a linear regression model, were 0.64, 0.78, and 0.89, respectively. Therefore, it can be concluded that, based on the highest correlation, HSCC is a more appropriate parameter than BMSCC to summarize the average herd subclinical mastitis situation in a dairy herd.     

生乳中体细胞数对乳品质量安全的影响研究进展

体细胞数增加会改变乳成分、影响牛乳风味及缩短乳制品货架期,并且使乳中抗生素和药物残留的风险增加。乳中体细胞数是衡量乳畜健康、乳品质量与安全的标准,也是国际判定隐形乳房炎的重要指标。为了保障乳品质量和安全,许多国家规定了生乳中体细胞数的限量。本文从体细胞数和乳品质量与安全的关系、不同国家对生乳中体细胞数的限量及影响体细胞数的因素和体细胞数的检测方法等方面作一综述。     

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.     

Changes of protein content and its fractions in bovine milk from different breeds subject to somatic cell count

Global milk production is undeniably dominated by 2 dairy breeds recognized worldwide: Holstein-Friesian and Jersey. A third breed, Simmental, serves as a dual-purpose breed. The objective of the present research was to establish potential changes in the fractional components of bovine milk protein (mainly whey) in relation to the health status of a dairy cow's mammary glands, which is closely determined by somatic cell count (SCC). The milk of 3 breeds was studied: Polish Holstein-Friesian (Black and Red-White varieties), Simmental, and Jersey. The cows were housed in freestall barns and fed according to the total mixed ration feeding system for both winter and summer periods. Milk samples were collected individually from each cow twice a year, in the winter and summer seasons. A total of 1,822 milk samples were evaluated (946 in winter and 876 in summer). The milk was examined for SCC, crude protein, casein, and whey fraction proteins (α-lactalbumin, β-lactoglobulin, lactoferrin, BSA, and lysozyme). The research material for each breed was split into 4 groups based on SCC (group I: ≤100,000 cells/mL; group II: 101,000 to 400,000 cells/mL; group III: 401,000 to 500,000 cells/mL; and group IV: 501,000 to 1,000,000 cells/mL). It was found that an increase of SCC promulgated a progressive decline in the daily yield of milk, which was significantly true for the Polish Holstein-Friesian. The level of crude protein decreased slightly as SCC increased, and casein concentration (r = −0.591) also followed this trend of decline. Elevation of SCC produced a decrease of major albumins (i.e., α-lactalbumin and β-lactoglobulin). However, SCC increase induced an increase in the immunoactive proteins (lactoferrin and lysozyme) as well as BSA. The interactions of a breed with increased SCC, which can be measured based on the BSA content of the milk, has indicated various levels of susceptibility to the increase in different breeds. This is confirmed by different values of correlation coefficients for these relationships: 0.71 in the Holstein-Friesian, 0.58 in Simmental, and 0.47 in the Jersey cows. Holstein-Friesian cows are more sensitive to mammary gland infections causing a greater decline of their daily milk yields, which, in turn, is reflected in an increase of the negative value of the correlation coefficients between SCC and milk efficiency (−0.24). In the other 2 breeds, the correlations were also negative, but substantially lower (−0.12 and −0.15).