Jeffrey Moore

Nontargeted Detection of Adulteration of Skim Milk Powder with Foreign Proteins Using UHPLC–UV

Chromatographic profiles of skim milk powder (SMP) and mixtures of SMP with soy (SPI), pea (PPI), brown rice (BRP), and hydrolyzed wheat protein (HWPI) isolates were obtained by ultrahigh-performance liquid chromatography (UHPLC) with 215 nm detection. Two data analysis approaches were compared for their utility to classify samples as authentic or adulterated. The t test approach evaluated data points exceeding the 99% confidence limit of the mean authentic SMP chromatogram and used data points from the entire chromatogram. The other approach used the multivariate Q statistic from a SIMCA model of authentic samples to determine adulteration and used a selected retention window to obtain best classifications. Q-Statistic and t test correctly classified adulteration of SMP with SPI at the 1% and 3% levels, respectively, while minimizing false classifications of authentic SMP. Detection of SMP adulterated with PPI, BRP, and HWPI was possible at higher adulteration levels.

Exploring Authentic Skim and Nonfat Dry Milk Powder Variance for the Development of Nontargeted Adulterant Detection Methods Using Near-Infrared Spectroscopy and Chemometrics

A multinational collaborative team led by the U.S. Pharmacopeial Convention is currently investigating the potential of near-infrared (NIR) spectroscopy for nontargeted detection of adulterants in skim and nonfat dry milk powder. The development of a compendial method is challenged by the range of authentic or nonadulterated milk powders available worldwide. This paper investigates the sources of variance in 41 authentic bovine skim and nonfat milk powders as detected by NIR diffuse reflectance spectroscopy and chemometrics. Exploratory analysis by principal component analysis and varimax factor rotation revealed significant variance in authentic samples and highlighted outliers from a single manufacturer. Spectral preprocessing and outlier removal methods reduced ambient and measurement sources of variance, most likely linked to changes in moisture together with sampling, preparation, and presentation factors. Results indicate that significant chemical variance exists in different skim and nonfat milk powders that will likely affect the performance of adulterant detection methods by NIR spectroscopy.

Standardisation of non-targeted screening tools to detect adulterations in skim milk powder using NIR spectroscopy and chemometrics

Introduction S kim milk powder and its counterpart in the USA, non-fat dry milk, are important food ingredients and sources of nutrition—more than 8 billion pounds of these products were produced globally in 2008. Although numerous testing standards exist for skim milk powder and other milk derivatives, no authoritative testing standards currently exist to authenticate the identities and purities of these ingredients with sufficient stringency. The tragic public health consequences of the 2008 melamine adulteration underscored the vulnerability and deficiencies of the classical methods used and highlighted the urgent need for more rigorous analytical tools to be developed, validated and implemented to prevent future incidents. A workshop on this topic was convened by the United States Pharmacopeial Convention (USP) in 2009, titled “Food Protein Workshop—Developing a Toolbox of Analytical Solutions to Address Adulteration”. One of the key outcomes of the meeting was identification of a need for standardised and reliable non-targeted screening methods combined with multivariate statistical analysis tools, if necessary, to analyse food ingredients like skim milk powder in QA/QC settings. Such tools would focus on providing an estimation of similarity between fingerprints or signatures of test ingredients and materials from a library of authenticated samples that represent the range of normal or non-adulterated ingredients in commerce. This non-targeted approach should be able to characterise the intrinsic analytical signature of authentic skim milk powder rather than to prove the absence of specific adulterants. Hence such an approach has the potential to help solve the age-old problem of using targeted methods to detect adulteration—that creative criminals are constantly evolving and engineering new, previously unknown adulterants to circumvent existing targeted QA/QC methods. Near infrared (NIR) spectroscopy is one of several screening tools that are currently being investigated in a collaborative research project led by the US Pharmacopeial Convention (USP) and aimed at developing and validating a toolbox of methods to detect skim milk powder adulteration. A team of laboratories is evaluating NIR spectroscopy because of its inherent advantage of being a low-cost and high-throughput tool and because it is readily available and is used routinely in the dairy arena and in food industry QA/QC laboratories. At least two previous studies have established some feasibility for such NIR and chemometrics tools but they were limited in the number and types of adulterants and instruments investigated. The USP team is working toward developing, validating and implementing a non-targeted NIR screening tool for skim milk powder in conjunction with chemometric tools and spectral libraries. A long-term vision for this team is to develop and implement an instrument-independent model, i.e. a testing protocol and database of NIR spectra for non-adulterated skim milk powder materials that is applicable across multiple instrument platforms from different vendors. This article reports preliminary findings from the collaborative study.

Characterization of Near-Infrared Spectral Variance in the Authentication of Skim and Nonfat Dry Milk Powder Collection Using ANOVA-PCA, Pooled-ANOVA, and Partial Least-Squares Regression

Forty-one samples of skim milk powder (SMP) and nonfat dry milk (NFDM) from 8 suppliers, 13 production sites, and 3 processing temperatures were analyzed by NIR diffuse reflectance spectrometry over a period of 3 days. NIR reflectance spectra (1700–2500 nm) were converted to pseudoabsorbance and examined using (a) analysis of variance-principal component analysis (ANOVA-PCA), (b) pooled-ANOVA based on data submatrices, and (c) partial least-squares regression (PLSR) coupled with pooled-ANOVA. ANOVA-PCA score plots showed clear separation of the samples with respect to milk class (SMP or NFDM), day of analysis, production site, processing temperature, and individual samples. Pooled-ANOVA provided statistical levels of significance for the separation of the averages, some of which were many orders of magnitude below 10–3. PLSR showed that the correlation with Certificate of Analysis (COA) concentrations varied from a weak coefficient of determination (R2) of 0.32 for moisture to moderate R2 values of 0.61 for fat and 0.78 for protein for this multinational study. In this study, pooled-ANOVA was applied for the first time to PLS modeling and demonstrated that even though the calibration models may not be precise, the contribution of the protein peaks in the NIR spectra accounted for the largest proportion of the variation despite the inherent imprecision of the COA values.

Effects of the Adulteration Technique on the Near-Infrared Detection of Melamine in Milk Powder

The United States Pharmacopeial Convention has led an international collaborative project to develop a toolbox of screening methods and reference standards for the detection of milk powder adulteration. During the development of adulterated milk powder reference standards, blending methods used to combine melamine and milk had unanticipated strong effects on the near-infrared (NIR) spectrum of melamine. The prominent absorbance band at 1468 nm of melamine was retained when it was dry-blended with skim milk powder but disappeared in wet-blended mixtures, where spray-dried milk powder samples were prepared from solution. Analyses using polarized light microscopy, Raman spectroscopy, dielectric relaxation spectroscopy, X-ray diffraction, and mass spectrometry indicated that wet blending promoted reversible and early Maillard reactions with lactose that are responsible for differences in melamine NIR spectra between wet- and dry-blended samples. Targeted detection estimates based solely on dry-blended reference standards are likely to overestimate NIR detection capabilities in wet-blended samples as a result of previously overlooked matrix effects arising from changes in melamine hydrogen-bonding status, covalent complexation with lactose, and the lower but more homogeneous melamine local concentration distribution produced in wet-blended samples. Techniques used to incorporate potential adulterants can determine the suitability of milk reference standards for use with rapid detection methods.

Characterising variances of milk powder and instrumentation for the development of a non-targeted, Raman spectroscopy and chemometrics detection method for the evaluation of authenticity.

ABSTRACT There is a need to develop rapid tools to screen milk products for economically motivated adulteration. An understanding of the physiochemical variability within skim milk powder (SMP) and non-fat dry milk (NFDM) is the key to establishing the natural differences of these commodities prior to the development of non-targeted detection methods. This study explored the sources of variance in 71 commercial SMP and NFDM samples using Raman spectroscopy and principal component analysis (PCA) and characterised the largest number of commercial milk powders acquired from a broad number of international manufacturers. Spectral pre-processing using a gap-segment derivative transformation (gap size = 5, segment width = 9, fourth derivative) in combination with sample normalisation was necessary to reduce the fluorescence background of the milk powder samples. PC scores plots revealed no clear trends for various parameters, including day of analysis, powder type, supplier and processing temperatures, while the largest variance was due to irreproducibility in sample positioning. Significant chemical sources of variances were explained by using the spectral features in the PC loadings plots where four samples from the same manufacturer were determined to likely contain an additional component or lactose anomers, and one additional sample was identified as an outlier and likely containing an adulterant or differing quality components. The variance study discussed herein with this large, diverse set of milk powders holds promise for future use as a non-targeted screening method that could be applied to commercial milk powders. Graphical Abstract

Development and validation of a reversed-phase high-performance liquid chromatography method for routine identification and purity assessment of high-purity steviol glycoside sweeteners.

The widespread application of stevia-based sweeteners in food products has resulted in the need for reliable analytical methods for measuring the purity and identity of high-purity steviol glycoside ingredients. The objective of this research was to develop and validate a new reversed-phase separation method capable of separating and quantifying nine steviol glycosides present in typical high-purity stevia extract ingredients. Results of the study established the linearity of the method at a correlation factor of 1.000 for the two major components and other minor components of this food ingredient. Method accuracy values were in the range of 99.1-100.9%. The percent relative standard deviation for six independent assay determinations was 1.0%. The method was determined to be robust for minor changes in column temperature, initial acetonitrile content, flow rate, and wavelength. The validated high-performance liquid chromatography method was found to be suitable to be included by USP as a Food Chemicals Codex compendial standard for steviol glycosides.

Non-targeted detection of milk powder adulteration using Raman spectroscopy and chemometrics: melamine case study

ABSTRACT Raman spectroscopy in combination with chemometrics was explored as a rapid, non-targeted screening method for the detection of milk powder (MP) adulteration using melamine as an example contaminant. Raman spectroscopy and an unsupervised pattern-recognition method, principal component analysis (PCA), allowed for the differentiation of authentic MPs from adulterated ones at concentrations > 1.0% for dry-blended (DB) samples and > 0.30% for wet-blended (WB) ones. Soft independent modelling of class analogy (SIMCA), a supervised pattern-recognition method, was also used to classify test samples as adulterated or authentic. Combined statistics at a 97% confidence level from the SIMCA models correctly classified adulteration of MP with melamine at concentrations ≥ 0.5% for DB samples and ≥ 0.30% for WB ones, while no false-positives from authentic MPs were found when the spectra in the 600–700 cm–1 range were pre-processed using standard normal variate (SNV) followed by a gap-segment derivatisation. The combined technique of Raman spectroscopy and chemometrics proved to be a useful tool for the rapid and cost-efficient non-targeted detection of adulteration in MP at per cent spiking levels. GRAPHICAL ABSTRACT

Variance of Commercial Powdered Milks Analyzed by Proton Nuclear Magnetic Resonance and Impact on Detection of Adulterants

Proton nuclear magnetic resonance spectra for 66 commercial powdered milk samples were analyzed by principal component analysis, soft independent modeling of class analogy, and pooled, crossed analysis of variance. It was found that the sample type (skim milk powder or non-fat dry milk), the supplier, the production site, the processing temperature (high, medium, or low temperature), and the day of analysis provided statistically significant sources of variation. Interestingly, inexact alignment (deviations of ±0.002 ppm) of the spectral reference peak was a significant source of variation, and fine alignment was necessary before the variation arising from the other experimental factors could be accurately evaluated. Using non-targeted analysis, the lowest detectable adulteration for dicyandiamide, melamine, and sucrose was 0.05%, the lowest detectable adulteration for maltodextrin and urea was 0.5%, the lowest detectable adulteration for ammonium sulfate and whey was 5%, and the lowest adulteration for soy protein isolate was undetectable using methods described herein. The measurement of variance and detection of adulteration were relatively unaffected by the resolution. Similar results were obtained with unbinned data (0.0003 ppm resolution) and binning of 333 data points (0.1 ppm resolution).

Exploring the variance of authentic skim and non-fat dry milk powder spectra

investigated by the Unites States Pharmacopeia (USP) in an effort to develop a successful non-targeted solution for milk powder. A significant challenge to be faced in this study is the normal physicochemical variability of pure milk powders. The existence of these variations will have the effect of widening the boundaries for any potential non-targeted method which may have the effect of decreasing the method’s ability to detect adulterants present at low concentrations. This problem is especially true for NIR diffuse reflectance spectroscopy, with its inherent limitations in the accurate detection of chemical components which are present below approximately 0.1% w /w in a sample matrix. In this report, the variance of NIR spectra from 41 different bovine skim milk powders and non-fat dry milk powders was explored. Spectral data were examined to identify influential sources of variance using princi pal component score trends and spectral signatures in rotated principal component loadings. Chemical analysis of samples of interest was also used to support the interpretations of the rotated principal components.