Rapid method for determination of milk casein content by infrared analysis

Preliminary work was to develop a method for determination of milk casein content using commercially available infrared milk testing equipment. Fresh whole milk samples were split into two portions. One portion was tested for total protein with an infrared milk analyzer. The other portion was adjusted to pH 4.6 with a specific volume and concentration of phosphoric acid. Milk casein precipitated at pH 4.6 and was removed by filtration. Next, the noncasein protein filtrate was tested for protein content using an infrared milk analyzer. The difference between the percent protein of the original milk sample and the percent protein of the noncasein protein filtrate equals the percent milk casein. The infrared casein determination for 36 different individual herd milk samples was not significantly different from results obtained by the official International Dairy Federation casein testing method. The infrared method is faster than the chemical method and could be done with infrared milk testing equipment that is commonly available in many cheese manufacturing plants. Repeatability of the infrared method was comparable to the repeatability of the chemical method.     

Rapid determination of sodium in milk and milk products by capillary zone electrophoresis

A capillary zone electrophoresis method for the determination of Na in milk and milk products was developed and compared with an International Organization for Standardization/International Dairy Federation standard method that is based on flame atomic absorption spectrometry. The adoption of a background electrolyte consisting of 10 mM imidazole adjusted to pH 3.75 by the addition of oxalic acid allowed baseline separation of Na from other milk cations and from Li ion, which was adopted as an internal standard. Method validation was performed and the results for linearity, precision, limit of detection, limit of quantification, and recovery are presented. The procedure was tested on commercial milk samples differing in fat content (whole, semiskimmed, and skimmed) and processing conditions (pasteurization, UHT sterilization, and microfiltration). The reliability of the method was confirmed for different varieties of cheese and other milk products. The method enables the routine measurement of Na content by a rapid and accurate capillary zone electrophoresis procedure.     

Calibration of infrared milk analyzers: modified milk versus producer milk

Mid-infrared (MIR) milk analyzers are traditionally calibrated using sets of preserved raw individual producer milk samples. The goal of this study was to determine if the use of sets of preserved pasteurized modified milks improved calibration performance of MIR milk analyzers compared with calibration sets of producer milks. The preserved pasteurized modified milk sets exhibited more consistent day-to-day and set-to-set calibration slope and intercept values for all components compared with the preserved raw producer milk calibration sets. Pasteurized modified milk calibration samples achieved smaller confidence interval (CI) around the regression line (i.e., calibration uncertainty). Use of modified milk calibration sets with a larger component range, more even distribution of component concentrations within the ranges, and the lower correlation of fat and protein concentrations than producer milk calibration sets produced a smaller 95% CI for the regression line due to the elimination of moderate and high leverage samples. The CI for the producer calibration sets were about 2 to 12 times greater than the CI for the modified milk calibration sets, depending on the component. Modified milk calibration samples have the potential to produce MIR milk analyzer calibrations that will perform better in validation checks than producer milk-based calibrations by reducing the mean difference and standard deviation of the difference between instrument values and reference chemistry.     

采用近红外透射技术分析油脂碘值

近红外技术由于其快速、准确，几乎不需样品制备的优点，在谷物与食品分析领域已有多年的应用。采用近红外透射技术分别建立了油脂低碘值范围定标(6～62gI／100g)和高碘值范围定标(97～134gI／100g)，定标标准偏差分别为0．347、0．376，相关系数分另4为0．999、0．998。采用验证样品集对定标进行验证，获得验证标准偏差分别为0．446、0．572，相关系数分别为1．000、0．997，结果说明，近红外技术用于油脂碘值快速分析是完全可行的。     

Analytic validation of an infrared milk urea assay and effects of sample acquisition factors on milk urea results

The objective of this study was to determine if milk samples, as they are routinely collected by Ontario Dairy Herd Improvement, would yield accurate milk urea results with an infrared assay. This investigation involved analytic validation of the infrared assay and assessment of the effect of DHI routine sample acquisition factors on milk urea results. Analytic validation of an automated milk urea assay was performed by assessing the relative accuracy and precision of milk urea results produced by the Fossomatic 4000 Milk Analyzer, an infrared method of analysis, compared with the Eurochem test, an accepted reference method. Results indicated that, when interpreted at the group level, milk urea results between the infrared method and the reference test were in good agreement. The two tests shared a similar and high level of precision. Milk urea concentrations obtained from composite (metered) milk samples, and not quarter stripping samples, were most representative of concurrent serum urea concentrations. The addition of bronopol preservative did not result in a numerically important change in milk urea concentrations. Storage of preserved metered milk samples for up to 4 d at either room temperature or by refrigeration, or for up to 3 d by freezing, did not result in changes in milk urea concentrations. We concluded that milk samples, as they are routinely collected and handled by DHI, are suitable for measurement of milk urea concentrations with the infrared method of analysis if data are interpreted at the group level.     

The Nature of the International Dairy Federation and Opportunities

The International Dairy Federation, a nongovernmental, nonpolitical international organization, was established in 1903. The International Dairy Federation is financed mainly by the annual membership fee from the current membership of 31 countries. Membership is accorded to countries through their National Committees representing the country's dairy interests. These Committees are the link between the member country and the International Dairy Federation. The International Dairy Federation Executive Committee deals with administrative and management matters subject to the prerogatives of the supreme body of the International Dairy Federation, the General Assembly. A permanent secretariat under the direction of the Secretary General coordinates International Dairy Federation activities and carries out the business at the International Dairy Federation House, Brussels, Belgium. The technical and scientific work of the Federation, under the guidance of the Commission of Studies, is carried out in six Commissions whose varied program of work covers all aspects of interest to the dairy industry. The advantages of IDF membership are considerable and are related to degree of active involvement, thus making for a favorable benefit to cost ratio.     

Joint IDF-IUPAC-IAEA(FAO) interlaboratory validation for determining aflatoxin M1 in milk by using immunoaffinity clean-up before thin-layer chromatography.

A collaborative study was conducted under the auspices of the International Dairy Federation (IDF), the International Union of Pure and Applied Chemistry (IUPAC) and the International Atomic Energy Agency (IAEA), a collaborative Food and Agricultural Organization (FAO) body fully to validate a method combining immunoaffinity clean-up to thin-layer chromatography for the determination of aflatoxin M(1) in milk. Work was done in order to afford those laboratories not equipped with high-performance liquid chromatography, mainly from developing countries, with a simplified but fully validated method as an alternative to the European validated immunoaffinity-high performance liquid chromatography method published as an EN ISO Standard 14501, February 1999. The validation study was carried out on samples of aflatoxin M(1)-contaminated milk and milk powder at levels close to the tolerable level of 0.5 microg l(-1) as recommended by the Codex Alimentarius and to the regulatory level of 0.05 microg l(-1) as laid down by the European Commission. Fourteen laboratories representing 11 countries participated in the trial. The relative standard deviations for repeatability and reproducibility based on raw data were in the range 27-48 and 35-54%, respectively. The recovery rate varied from 32 to 120%. The mishandling of two crucial steps of the protocol such as matrix sample reconstitution and extract evaporation could explain the wide variation of the recovery rate. For this reason, data were then corrected for recovery. Consequently, the relative standard deviations for repeatability and reproducibility were recalculated after correction for recovery and were in the range 26-54 and 34-53%, respectively. The method will be published as a standard ISO/DIS 14674--IDF 190.     

近红外快速检测奶粉乳清粉成分研究

采用Perten8620近红外奶粉分析仪检测奶粉的近红外光谱特性，建立了奶粉近红外检测的校准模型。结果表明，近红外检测技术无需称重和化学试剂，可在1min以内快速检测奶粉和乳清粉的蛋白、脂肪、水分等指标，其准确性和精度可以达到在国际允许的误差范围内。根据近红外技术可能在短时间内收集大量样品的光谱图，开发了新检测项目的校准曲线。     

基于近红外光谱对牛奶中掺杂尿素的判别分析

采集40个合格的纯牛奶样品,并配制含有尿素为1～20g/L的40个牛奶样品,研究掺杂尿素牛奶的二维相关近红外特性,在此基础上选择波数4200～4800cm-1为建模区间,采用偏最小二乘法建立定性、定量模型。结果指出通过判别偏最小二乘法可以实现纯牛奶及掺杂尿素牛奶的定性鉴别,判别正确率为100%;掺杂牛奶校正集相关系数R为0.999,交叉验证均方差为0.242,对未知样品集预测相关系数R达到0.999,预测标准偏差为0.57,这表明所建模型具有较好的预测效果。     

Accuracy of Fourier transform infrared spectrometry in determination of casein in dairy cows' milk

For practical purposes the casein content of milk is often estimated from the crude protein content using a general conversion factor. This is done even though it is known that several factors can influence the percentage of casein nitrogen in the total nitrogen (casein number). The uncontrolled variation in casein number affects optimization of cheese production because casein is a limiting factor for cheese yield. Fourier transform infrared spectrometry has recently been introduced for casein determination. Using this technique we obtained a standard error of prediction (SEP) of 0.033% for casein concentrations in the range 2.1-4.0%. The true prediction error was estimated as 0.025%. The correlation between casein numbers obtained by reference analysis and infrared spectrometry could be expressed by an R2 of 0.73 and an SEP of 0.89 for casein numbers in the range 70.7-81.0.     

Quantification of individual fatty acids in bovine milk by infrared spectroscopy and chemometrics: Understanding predictions of highly collinear reference variables

Predicting individual fatty acids (FA) in bovine milk from Fourier transform infrared (FT-IR) measurements is desirable. However, such predictions may rely on covariance structures among individual FA and total fat content. These covariance structures may change with factors such as breed and feed, among others. The aim of this study was to estimate how spectral variation associated with total fat content and breed contributes to predictions of individual FA. This study comprised 890 bovine milk samples from 2 breeds (455 Holstein and 435 Jersey). Holstein samples were collected from 20 Danish dairy herds from October to December 2009; Jersey samples were collected from 22 Danish dairy herds from February to April 2010. All samples were from conventional herds and taken while cows were housed. Moreover, in a spiking experiment, FA (C14:0, C16:0, and C18:1 cis-9) were added (spiked) to a background of commercial skim milk to determine whether signals specific to those individual FA could be obtained from the FT-IR measurements. This study demonstrated that variation associated with total fat content and breed was responsible for successful FT-IR–based predictions of FA in the raw milk samples. This was confirmed in the spiking experiment, which showed that signals specific to individual FA could not be identified in FT-IR measurements when several FA were present in the same mixture. Hence, predicted concentrations of individual FA in milk rely on covariance structures with total fat content rather than absorption bands directly associated with individual FA. If covariance structures between FA and total fat used to calibrate partial least squares (PLS) models are not conserved in future samples, these samples will show incorrect and biased FA predictions. This was demonstrated by using samples of one breed to calibrate and samples of the other breed to validate PLS models for individual FA. The 2 breeds had different covariance structures between individual FA and total fat content. The results showed that the validation samples yielded biased predictions. This may limit the usefulness of FT-IR–based predictions of individual FA in milk recording as indirect covariance structures in the calibration set must be valid for future samples. Otherwise, future samples will show incorrect predictions.     

Development of a Single Kernel NIR Barley Protein Calibration and Assessment of Variation in Protein on Grain Quality

In this paper, we describe results from a preliminary experiment on the development of a near infrared reflectance (NIR) calibration for single kernel (SK) % protein content in barley. The SKNIR calibration was developed using kernels from breeding lines and commercial barley varieties with a range in protein content of 7.3% to 16.6% “as is”. The calibration model produced an R² = 0.903, while the validation set had a R² = 0.837 with a standard error of cross validation and a standard error of prediction of 0.8% for both the calibration and validation sets respectively. The calibration was then used to estimate the variation in % protein of 4,000 single kernels from a commercial variety (Gairdner at 9.3% protein) by segregating kernels into six sub‐groups (<7.8%, 7.9–8.3%, 8.4–9.0%, 9.1–9.7%, 9.8–10.4%, >10.5% “as is”). These sub‐groups then had additional grain quality tests carried out including grain size, thousand kernel weight and NIR estimates of % protein, starch, hardness and barley hot water extract (HWE). The results showed an increase in grain size, and a decrease in HWE from the low to high % protein sub‐groups. While only a single variety was used in the SKNIR protein segregation study, the results suggested SKNIR could be used to screen for the variation in grain quality traits based on variation in protein content.     

A rapid method to quantify casein in fluid milk by front-face fluorescence spectroscopy combined with chemometrics

Casein in fluid milk determines cheese yield and affects cheese quality. Traditional methods of measuring casein in milk involve lengthy sample preparations with labor-intensive nitrogen-based protein quantifications. The objective of this study was to quantify casein in fluid milk with different casein-to-crude-protein ratios using front-face fluorescence spectroscopy (FFFS) and chemometrics. We constructed calibration samples by mixing microfiltration and ultrafiltration retentate and permeate in different ratios to obtain different casein concentrations and casein-to-crude-protein ratios. We developed partial least squares regression and elastic net regression models for casein prediction in fluid milk using FFFS tryptophan emission spectra and reference casein contents. We used a set of 20 validation samples (including raw, skim, and ultrafiltered milk) to optimize and validate model performance. We externally tested another independent set of 20 test samples (including raw, skim, and ultrafiltered milk) by root mean square error of prediction (RMSEP), residual prediction deviation (RPD), and relative prediction error (RPE). The RMSEP for casein content quantification in raw, skim, and ultrafiltered milk ranged from 0.12 to 0.13%, and the RPD ranged from 3.2 to 3.4. The externally validated error of prediction was comparable to the existing rapid method and showed practical model performance for quality-control purposes. This FFFS-based method can be implemented as a routine quality-control tool in the dairy industry, providing rapid quantification of casein content in fluid milk intended for cheese manufacturing.     

Performance evaluation of an enzymatic spectrophotometric method for milk urea nitrogen

Our objective was to determine the within and between laboratory performance of an enzymatic spectrophotometric method for milk urea nitrogen (MUN) determination. This method first uses urease to hydrolyze urea into ammonia and carbon dioxide. Next, ammonia (as ammonium ions) reacts with 2-oxoglutarate, in the presence of reduced nicotinamide-adenine dinucleotide phosphate (NADPH) and the enzyme glutamate dehydrogenase (GlDH), to form l-glutamic acid, water, and NADP⁺. The change in light absorption at 340 nm due to the conversion of NADPH to NADP+ is stoichiometrically a function of the MUN content of a milk sample. The relative within (RSD_r) and between (RSD_R) laboratory method performance values for the MUN enzymatic spectrophotometric method were 0.57% and 0.85%, respectively, when testing individual farm milks. The spectrophotometric MUN method demonstrated better within and between laboratory performance than the International Dairy Federation differential pH MUN method with a much lower RSD_r (0.57 vs. 1.40%) and RSD_R (0.85 vs. 4.64%). The spectrophotometric MUN method also had similar method performance statistics as other AOAC International official validated chemical methods for primary milk component determinations, with the average of all RSD_r and RSD_R values being <1%. An official collaborative study of the enzymatic spectrophotometric MUN method is needed to achieve International Dairy Federation, AOAC International, and International Organization for Standardization official method status.     

Prediction and repeatability of milk coagulation properties and curd-firming modeling parameters of ovine milk using Fourier-transform infrared spectroscopy and Bayesian models

The aim of this study was to apply Bayesian models to the Fourier-transform infrared spectroscopy spectra of individual sheep milk samples to derive calibration equations to predict traditional and modeled milk coagulation properties (MCP), and to assess the repeatability of MCP measures and their predictions. Data consisted of 1,002 individual milk samples collected from Sarda ewes reared in 22 farms in the region of Sardinia (Italy) for which MCP and modeled curd-firming parameters were available. Two milk samples were taken from 87 ewes and analyzed with the aim of estimating repeatability, whereas a single sample was taken from the other 915 ewes. Therefore, a total of 1,089 analyses were performed. For each sample, 2 spectra in the infrared region 5,011 to 925 cm^?1 were available and averaged before data analysis. BayesB models were used to calibrate equations for each of the traits. Prediction accuracy was estimated for each trait and model using 20 replicates of a training-testing validation procedure. The repeatability of MCP measures and their predictions were also compared. The correlations between measured and predicted traits, in the external validation, were always higher than 0.5 (0.88 for rennet coagulation time). We confirmed that the most important element for finding the prediction accuracy is the repeatability of the gold standard analyses used for building calibration equations. Repeatability measures of the predicted traits were generally high (≥95%), even for those traits with moderate analytical repeatability. Our results show that Bayesian models applied to Fourier-transform infrared spectra are powerful tools for cheap and rapid prediction of important traits in ovine milk and, compared with other methods, could help in the interpretation of results.     

牛乳中二噁英类化合物标准物质的研制

研制乳粉中非添加二噁英类化合物的标准物质,加强我国二噁英类化合物实验室检测质控能力建设。方法 选择满足侯选物筛选原则和要求的牛乳样品作为候选物,经混匀、分装、冻干后,以高分辨气相色谱-高分辨质谱法同位素稀释技术测定多氯代苯并二噁英、多氯代苯并呋喃(PCDD/Fs)和二噁英样多氯联苯(dl-PCBs),经均匀性和稳定性试验后,采用多家实验室联合定值方法对样品中二噁英类化合物含量进行定值及不确定度分析。结果 经单因素方差分析和F检验,瓶间均匀性试验的检验值F均小于临界值F0.01(9,40)。室温下1年的稳定性试验结果显示,定值化合物一元线性拟合方程中斜率|b₁|均小于t(0.95,3)×s(b₁),表明特征值变化趋势无统计学意义。结论 本研究提出了二噁英类化合物定值结果,为二噁英检测提供质控参考和能力评价。     

Qualitative and quantitative analysis of phosphorylated compounds in milk by means of 31P-NMR

31P-NMR has been tested as a technique for determining the phosphorus content of milk samples in both the inorganic form (Pi) and bonded to caseins as phosphoserine (SerP). 31P-NMR made possible the simultaneous determination of Pi and SerP in approximately 1.7 h. The determination is based on measuring the area under the resonance in question and interpolating in a calibration curve prepared using external standards of known phosphorus contents and prepared in the same manner. The concentration area plots obtained were linear in the ranges 162-1993 mg P/l for Pi and 38-40.2 mg P/l for casein SerP. The repeatability of the method was good. When the same milk samples were analysed by both 31P-NMR and the classic colorimetric method the correlation was good. Polyphosphates added to commercial milk were also detected, as diphosphates. The NMR response for diphosphate was linear between 58 and 576 mg P/l and preliminary results indicated that quantitative analysis could be achieved in commercial milk.     

Modified versus producer milk calibration: mid-infrared analyzer performance validation

Our objective was to determine the validation performance of mid-infrared (MIR) milk analyzers, using the traditional fixed-filter approach, when the instruments were calibrated with producer milk calibration samples vs. modified milk calibration samples. Ten MIR analyzers were calibrated using producer milk calibration sample sets, and 9 MIR milk analyzers were calibrated using modified milk sample sets. Three sets of 12 validation milk samples with all-laboratory mean chemistry reference values were tested during a 3-mo period. Calibration of MIR milk analyzers using modified milk increased the accuracy (i.e., better agreement with chemistry) and improved agreement between laboratories on validation milk samples compared with MIR analyzers calibrated with producer milk samples. Calibration of MIR analyzers using modified milk samples reduced overall mean Euclidian distance for all components for all 3 validation sets by at least 24% compared with MIR analyzers calibrated with producer milk sets. Calibration with modified milk sets reduced the average Euclidian distance from all-laboratory mean reference chemistry on validation samples by 40, 25, 36, and 27%, respectively for fat, anhydrous lactose, true protein, and total solids. Between-laboratory agreement was evaluated using reproducibility standard deviation (s_R). The number of single Grubbs statistical outliers in the validation data was much higher (53 vs. 7) for the instruments calibrated with producer milk than for instruments calibrated with modified milk sets. The s_R for instruments calibrated with producer milks (with statistical outliers removed) was similar to data collected in recent proficiency studies, whereas the s_R for instruments calibrated with modified milks was lower than those calibrated with producer milks by 46, 52, 61, and 55%, respectively for fat, anhydrous lactose, true protein, and total solids.     

An empirical method for prediction of cheese yield

Theoretical cheese yield can be estimated from the milk fat and casein or protein content of milk using classical formulae, such as the VanSlyke formula. These equations are reliable predictors of theoretical or actual yield based on accurately measured milk fat and casein content. Many cheese makers desire to base payment for milk to dairy farmers on the yield of cheese. In small factories, however, accurate measurement of fat and casein content of milk by either chemical methods or infrared milk analysis is too time consuming and expensive. Therefore, an empirical test to predict cheese yield was developed which uses simple equipment (i.e., clinical centrifuge, analytical balance, and forced air oven) to carry out a miniature cheese making, followed by a gravimetric measurement of dry weight yield. A linear regression of calculated theoretical versus dry weight yields for milks of known fat and casein content was calculated. A regression equation of y = 1.275x + 1.528, where y is theoretical yield and x is measured dry solids yield (r2 = 0.981), for Cheddar cheese was developed using milks with a range of theoretical yield from 7 to 11.8%. The standard deviation of the difference (SDD) between theoretical cheese yield and dry solids yield was 0.194 and the coefficient of variation (SDD/mean x 100) was 1.95% upon cross validation. For cheeses without a well-established theoretical cheese yield equation, the measured dry weight yields could be directly correlated to the observed yields in the factory; this would more accurately reflect the expected yield performance. Payments for milk based on these measurements would more accurately reflect quality and composition of the milk and the actual average recovery of fat and casein achieved under practical cheese making conditions.     

Potential estimation of major mineral contents in cow milk using mid-infrared spectrometry

Milk and dairy products are a major source of minerals, particularly calcium, involved in several metabolic functions in humans. Currently, several dairy products are enriched with calcium to prevent osteoporosis. The development of an inexpensive and fast quantitative analysis for minerals is required to offer dairy farmers an opportunity to improve the added value of the produced milk. The aim of this study was to develop 5 equations to measure Ca, K, Mg, Na, and P contents directly in bovine milk using mid-infrared (MIR) spectrometry. A total of 1,543 milk samples were collected between March 2005 and May 2006 from 478 cows during the Walloon milk recording and analyzed by MIR spectrometry. Using a principal component approach, 62 milk samples were selected by their spectral variability and separated in 2 calibration sets. Five outliers were detected and deleted. The mineral contents of the selected samples were measured by inductively coupled plasma atomic emission spectrometry. Using partial least squares combined with a repeatability file, 5 calibration equations were built to estimate the contents of Ca, K, Mg, Na, and P in milk. To assess the accuracy of the developed equations, a full cross-validation and an external validation were performed. The cross-validation coefficients of determination (R²cv) were 0.80, 0.70, and 0.79 for Ca, Na, and P, respectively (n = 57), and 0.23 and 0.50 for K and Mg, respectively (n = 31). Only Ca, Na, and P equations showed sufficient R²cv for a potential application. These equations were validated using 30 new milk samples. The validation coefficients of determination were 0.97, 0.14, and 0.88 for Ca, Na, and P, respectively, suggesting the potential to use the Ca and P calibration equations. The last 30 samples were added to the initial milk samples and the calibration equations were rebuilt. The R²cv for Ca, K, Mg, Na, and P were 0.87, 0.36, 0.65, 0.65, and 0.85, respectively, confirming the potential utilization of the Ca and P equations. Even if new samples should be added in the calibration set, the first results of this study showed the feasibility to quantify the calcium and phosphorus directly in bovine milk using MIR spectrometry.