牛奶中抗生素残留快速检测方法分析

利用TTC法和SNAP快速检测法对牛奶中β-内酰胺类、四环素类、大环内酯类、氨基糖苷类、氯霉素、磺胺类、氟喹诺酮类等7个类别9种代表性抗生素检测结果进行比较分析,根据检测结果认为两种检测方法均存在一定缺陷,在原料乳质量控制检测工作中单独使用都存在一定风险,但在对原料收购地区奶牛饲养用药普查基础上,可以考虑使用SNAP法来控制原料乳中β-内酰胺类抗生素残留.     

荧光定量技术快速检测生乳中磺胺类药物残留

目的 利用荧光定量技术分析检测生乳中磺胺类药物残留,评价该方法的可行性.方法 取生乳空白样品进行加标回收实验(磺胺恶唑13.50、27.00μg/L;磺胺喹恶啉5.00、10.00μg/L;磺胺嘧啶0.82、1.64μg/L),取200μL样品与金标抗体结合,50℃孵育3 min,取120μL样品加到检测卡,反应10 ...     

用阻抗分析法快速检测牛奶中抗生素残留的研究

研究立足于牛奶中抗生素的快速检测,用嗜热乳酸链球菌作为指示菌,通过“阻抗分析仪”的自动检测、分析,根据DT时间的产生,判断牛奶中抗生素的残留情况。试验表明,方法操作简单、快捷,结果易判断,全部检测过程可在2 h之内完成。该方法的检测灵敏度与GB方法相类似,可检测牛奶中的青霉素为0.04U/mL。     

近红外光谱法快速检测牛奶中氯霉素残留

本研究利用近红外透射技术和偏最小二乘法(PLS)快速测定牛奶中氯霉素残留含量, 氯霉素残留的预测值与真实值的相关系数达0.9893,预示集的平均回收率为99.77%。结果表明该方法可快速测定牛奶中氯霉素残留含量。     

基于荧光法的牛奶中单诺沙星的快速检测

采用荧光法结合化学计量学来建立牛奶中单诺沙星(DANO)残留的快速检测方法 先利用加标法制备含有不同浓度的DANO(0～56μg/L)的全脂奶作为校正集,除蛋白后经扫描得到荧光光谱,利用化学计量学技术对其进行主成分分析(PCA)并建立偏最小二乘法(PLS)和判别分析(PLSDA)模型.采用加入不同浓度DANO的4种品牌的超高温杀菌和巴氏杀菌牛奶作为预测集,验证了两种模型的准确性.实验结果表明,定性模型可以准确地将阴性与阳性样品区分,定量模型预测出的样品回收率在88％ ～ 114.4％,预测误差在可接受范围内.     

基于荧光法的牛奶中单诺沙星的快速检测

采用荧光法结合化学计量学来建立牛奶中单诺沙星(DANO)残留的快速检测方法。先利用加标法制备含有不同浓度的DANO(0～56μg/L)的全脂奶作为校正集,除蛋白后经扫描得到荧光光谱,利用化学计量学技术对其进行主成分分析(PCA)并建立偏最小二乘法(PLS)和判别分析(PLSDA)模型。采用加入不同浓度DANO的4种品牌的超高温杀菌和巴氏杀菌牛奶作为预测集,验证了两种模型的准确性。实验结果表明,定性模型可以准确地将阴性与阳性样品区分,定量模型预测出的样品回收率在88%～114.4%,预测误差在可接受范围内。      

近红外光谱技术结合化学计量学快速检测蛋黄粉掺假

目的 采用近红外光谱(Fourier transform near-infrared spectroscopy, FT-NIR)技术和化学计量学[无监督偏最小二乘判别分析(unsupervised partial least squares discriminant analysis, PLS-DA)]进行的蛋黄粉筛查指纹匹配定性方法, 用于在工厂接收环节检测蛋黄粉中潜在的食品欺诈问题。方法 通过向蛋黄粉样品中添加不同比例(质量百分比分别为5%、10%和25%)的淀粉和麦芽糊精、植脂末和大豆蛋白粉制备掺假样品, 使用FT-NIR检测收集真实样品和掺假样品的谱图, 并应用PLS-DA模型进行判别分析。结果 该方法经验证, 可用于检测蛋黄粉中淀粉和麦芽糊精、植脂末和大豆蛋白粉的含量, 质量百分比分别为5%、10%和25%。该方法不适用于含有少于5%上述潜在掺假成分的蛋黄粉。其他食品掺假成分的检出限值需要进行进一步验证。通过该方法分析的结果以“阴性”或“阳性”表示。结论 该方法适用于蛋黄粉掺假的快速检测, 可大大提高工厂接收环节检测蛋黄粉中潜在的食品欺诈效率。     

基于三维荧光光谱的多种植物油中多菌灵残留测定

目的 开发一种适用于植物油中多菌灵残留的快速准确的检测方法。方法 采用三维荧光光谱结合化学计量学方法对植物油中残留多菌灵进行定量分析。在多菌灵中添加3种不同植物油提取物来制备样本,并测其三维荧光光谱。采用平行因子（PARAFAC）、满秩平行因子（FPA-PARAFAC）和交替三线性分解（ATLD）3种算法对样本中的多菌灵进行分析,比较3种算法的选择性、灵敏度、检出限、定量限等品质因子（FOM）,并采用椭圆联合置信区间（EJCR）进行检验。结果 PARAFAC、FPA-PARAFAC和ATLD对多菌灵加标回收率分别为96.98%~112.64%,97.05%~112.36%,93.07%~104.47%,ATLD的平均回收率最接近100%。在FOM及EJCR分析中,ATLD相比其他两种算法有着更好的表现。结论 采用三维荧光光谱结合化学计量学测定植物油中残留多菌灵,可获得优秀的定量结果。     

时间分辨荧光免疫层析快速检测牛奶中地塞米松

目的 建立基于时间分辨荧光微球对牛奶中的地塞米松残留进行快速检测的方法,并对该方法性能进行评估。方法 使用地塞米松抗体标记时间分辨荧光微球,分别采用湿法和干法制备检测试纸条,比较两种方法的灵敏度,同时确定微球的最佳抗体标记量,并对试纸条的重复性、检测灵敏度进行评估。结果 以20μg抗体/mg微球的标记量,湿法制备的试纸条检测灵敏度更佳。该方法重复性检测中变异系数(coefficientof variation, CV)为8.2%,地塞米松溶液的检出限为0.07 ng/mL,检测牛奶中地塞米松的半抑制浓度(half maximal inhibitory concentration, IC50)为0.24 ng/mL。结论 该方法具有测试简单、灵敏度高等特点,制备的试纸条可满足牛奶中地塞米松残留的检测要求。     

牛奶中抗生素残留及其检测技术的研究进展

论述了牛奶中抗生素残留的原因和危害性,列举了目前国内外较流行的牛奶中抗生素的检测技术,并阐述了其检测原理。      

Application of fluorescence spectroscopy for monitoring changes in nonfat dry milk during storage

The objective of this study was to determine if fluorescence spectroscopy could be used to characterize the biochemical characteristics of nonfat dry milk (NDM) caused by manufacturing and storage conditions. Nine low-heat NDM samples were collected from 3 manufacturers and stored at 4 temperatures (4, 22, 35, and 50°C) for 8 wk. The spectra of Maillard products, tryptophan, and riboflavin were recorded and analyzed with principal components analysis. Colorimetric indices L*, a*, and b* were also determined. The before-storage NDM samples collected from each manufacturer had different fluorescent characteristics. Inconsistency was observed for the NDM samples collected from 1 manufacturer, whereas the samples from the other 2 manufacturers displayed consistent fluorescence characteristics. Biochemical reactions, such as Maillard reaction, modification of the tryptophan environment, and degradation of riboflavin occurred during the manufacturing process. For each of the data collections, discrimination of the NDM samples stored at 50°C from the samples stored at 4, 22, and 35°C was observed in the similarity maps. The factor loadings of the first 2 principal components for the fluorescence spectra of the samples before storage were similar to the principal components analysis results of the samples during storage. It appears that similar factors are responsible for the variation in the samples before storage and their changes during storage. Additionally, storage of the samples at 50°C accelerated these reactions. The results demonstrate that front-face fluorescence spectroscopy, coupled with multivariate statistical methods, can be utilized as an analytical technique to monitor variation in NDM samples from different manufacturers and changes during storage.     

前表面荧光法在牛奶美拉德反应检测中的应用

在热处理中,牛奶中的乳蛋白容易与乳糖发生美拉德反应,使牛奶的色泽、风味、营养等发生变化。与传统化学检测法相比,前表面荧光法具有快速灵敏、前处理简便等优点。为了评估前表面荧光法在检测牛奶美拉德反应程度上的准确性和适用性,本文对比了不同热处理下牛奶的美拉德反应的荧光图谱和美拉德产物的含量,分析了指标间的相关性。并以前表面荧光法和羟甲基糠醛含量建立模型对商业乳品进行预测,结果良好,为荧光检测的工业应用提供理论依据。结果显示,前表面荧光法可应用于牛奶前中期美拉德产物的无损检测。     

牛奶中多种磺胺类抗生素残留的HPLC快速分析

研究了牛奶中磺胺嘧啶、磺胺甲基嘧啶、磺胺二甲基嘧啶、磺胺甲噁唑、磺胺间甲氧嘧啶、磺胺二甲氧嘧啶六种磺胺类抗生素的多残留高效液相色谱(HPLC)分析方法。样品经氯仿-丙酮(2:1,V/V)提取两次,提取液浓缩至干。残渣用流动相甲醇-0.08%乙酸(60:40,V/V)溶解,净化后以反相C18柱,甲醇-0.08%乙酸等度洗脱,紫外检测器检测、外标法定量。结果表明,这六种抗生素在0.01～1.0mg/L浓度范围内呈线性关系,磺胺嘧啶、磺胺甲基嘧啶、磺胺二甲基嘧啶检的检出限为0.010mg/L、磺胺甲噁唑、磺胺间甲氧嘧啶、磺胺间二甲氧嘧啶检出限分别为0.015mg/L。分析的添加回收率为69.4%～123.5%,变异系数为<8%,整体分析时间小于3h。方法具有处理简单、检测快速、准确的特点。     

超高效液相色谱法测定乳及乳制品中多种磺胺类药物残留

建立了超高效液相色谱法同时测定乳及乳制品中14种磺胺类药物残留的方法.样品通过乙腈重复提取,饱和正己烷脱脂后浓缩,基质固相分散萃取技术净化,采用ACQUITY UPLCTM BEH C18柱,以甲醇和质量分数0.1％甲酸水溶液为流动相梯度洗脱,用紫外检测器于270 nm波长处检测.回收率在90.4％～104.3％,精密度(RSD)为1.09％～5.73％,检出限分别为0.04～0.09 μg/g.该方法可用于乳及乳制品中14种磺胺类药物残留的同时测定.     

Technical note: Nontargeted detection of adulterated plant proteins in raw milk by UPLC-quadrupole time-of-flight mass spectrometric proteomics combined with chemometrics

We built and validated a chemometric model to detect possible milk adulteration with plant proteins. Specifically, we extracted proteins in raw milk, treated with tryptic digestion, and obtained peptide fingerprints by UPLC-quadrupole time-of-flight-mass spectrometry with proteomics to differentiate authentic milks from their counterparts adulterated with nonmilk proteins. This approach is able to detect soybean and pea powder-adulterated milks at as low as 1% (wt/wt). Additionally, we obtained the characteristic peptide sequences for milk authentication by principal component analysis. The prediction accuracies for milk authentication by partial least-squares-discriminant analysis were greater than 95%. These results indicated that peptide fingerprints with the chemometric analysis could be successfully applied for milk quality control.     

Application of fluorescence spectroscopy and chemometrics in the evaluation of processed cheese during storage

Front face fluorescence spectroscopy is applied for an evaluation of the stability of processed cheese during storage. Fluorescence landscapes with excitation from 240 to 360 nm and emission in the range of 275 to 475 nm were obtained from cheese samples stored in darkness and light in up to 259 d, at 5, 20 and 37 degrees C, respectively. Parallel factor (PARAFAC) analysis of the fluorescence landscapes exhibits four fluorophores present in the cheese, all related to the storage conditions. The chemometric analysis resolves the fluorescence signal into excitation and emission profiles of the pure fluorescent compounds, which are suggested to be tryptophan, vitamin A and a compound derived from oxidation. Thus, it is concluded that fluorescence spectroscopy in combination with chemometrics has a potential as a fast method for monitoring the stability of processed cheese.     

综合型传感器阵列对掺杂生乳的识别

以钯、铂、金、钛、钨和银6种自制电极组为工作电极,与Ag/AgCl参比电极和铂对电极组成非选择性传感器组,再结合pH电极、电导率电极和钠度计电极3种选择性电极组成综合型传感器阵列,连接到电化学工作站和安装SPSS统计学软件电脑后,构成生乳掺杂检测系统。对荷斯坦牛生乳及掺杂不同浓度尿素和三聚氰胺,碳酸氢钠的样本乳、陈放乳、巴氏乳、酸败乳采用电化学方法进行检测,获得开路电位、交流阻抗谱、微分脉冲伏安数据,非选择性与选择性传感器组数据分别采用模式识别法进行计算,并获得各被测样本与生乳标准数据库的欧氏距离,再以不同权重得出综合欧氏距离,通过图表得到表达。结果表明,非选择性传感器阵列组对掺杂生乳具有良好的判别能力,在此基础上构建的加装有选择性传感器的综合型传感器阵列对掺杂的甑别效果优于前者。      

Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000-900 cm⁻¹) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a₃₀, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm⁻¹. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm⁻¹, 3,040 to 1,700 cm⁻¹, and 4,000 to 3,470 cm⁻¹. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a₃₀, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R² = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R² = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.