Comparison of Depth-Specific Prediction of Soil Properties: MIR vs. Vis-NIR Spectroscopy.

The prediction of soil properties at different depths is an important research topic for promoting the conservation of black soils and the development of precision agriculture. Mid-infrared spectroscopy (MIR, 2500-25000 nm) has shown great potential in predicting soil properties. This study aimed to explore the ability of MIR to predict soil organic matter (OM) and total nitrogen (TN) at five different depths with the calibration from the whole depth (0-100 cm) or the shallow layers (0-40 cm) and compare its performance with visible and near-infrared spectroscopy (vis-NIR, 350-2500 nm). A total of 90 soil samples containing 450 subsamples (0-10 cm, 10-20 cm, 20-40 cm, 40-70 cm, and 70-100 cm depths) and their corresponding MIR and vis-NIR spectra were collected from a field of black soil in Northeast China. Multivariate adaptive regression splines (MARS) were used to build prediction models. The results showed that prediction models based on MIR (OM: RMSEp = 1.07-3.82 g/kg, RPD = 1.10-5.80; TN: RMSEp = 0.11-0.15 g/kg, RPD = 1.70-4.39) outperformed those based on vis-NIR (OM: RMSEp = 1.75-8.95 g/kg, RPD = 0.50-3.61; TN: RMSEp = 0.12-0.27 g/kg; RPD = 1.00-3.11) because of the higher number of characteristic bands. Prediction models based on the whole depth calibration (OM: RMSEp = 1.09-2.97 g/kg, RPD = 2.13-5.80; TN: RMSEp = 0.08-0.19 g/kg, RPD = 1.86-4.39) outperformed those based on the shallow layers (OM: RMSEp = 1.07-8.95 g/kg, RPD = 0.50-3.93; TN: RMSEp = 0.11-0.27 g/kg, RPD = 1.00-2.24) because the soil sample data of the whole depth had a larger and more representative sample size and a wider distribution. However, prediction models based on the whole depth calibration might provide lower accuracy in some shallow layers. Accordingly, it is suggested that the methods pertaining to soil property prediction based on the spectral library should be considered in future studies for an optimal approach to predicting soil properties at specific depths. This study verified the superiority of MIR for soil property prediction at specific depths and confirmed the advantage of modeling with the whole depth calibration, pointing out a possible optimal approach and providing a reference for predicting soil properties at specific depths.

Infrared analyzers for the measurement of breastmilk macronutrient content in the clinical setting.

INTRODUCTION: There is growing interest in the possibility of measuring the macronutrient content of human milk. Several studies that intend to validate commercially available human milk analyzers have been published with inconsistent results. This review will focus on currently available, verified methodologies for analyzing macronutrients in human milk. AREAS COVERED: A literature search was conducted in the PubMed database. Five milk analyzers were chosen to be included in this review: MIRIS (Uppsala, Sweden) (seven articles found), Calais (Cleveland, United States) (four articles), SpectraStar (Brookfield, United States) (four articles), MilkoScan (Hillerdo, Denmark) (two articles), and Delta LactoScope (Stockholm, Sweden) (one article). The following information was extracted from published manuscripts: measuring device, sample preparation, purpose of the study, type of macronutrients studied, results, and conclusions. EXPERT OPINION: Infrared spectroscopy can be an accurate and reliable technology for assessing the macronutrient content of human milk, specifically crude protein, and total fat. However, an optimal handling of samples, the development of standardized quality-control protocols, and an improvement in calibration procedures are required before the full implementation of infrared technology in neonatal units.

Using SLIM-Based IMS-IMS Together with Cryogenic Infrared Spectroscopy for Glycan Analysis.

The isomeric heterogeneity of glycans poses a great challenge for their analysis. While combining ion mobility spectrometry (IMS) with tandem mass spectrometry is a powerful means for identifying and characterizing glycans, it has difficulty distinguishing the subtlest differences between isomers. Cryogenic infrared spectroscopy provides an additional dimension for glycan identification that is extremely sensitive to their structure. Our approach to glycan analysis combines ultrahigh-resolution IMS-IMS using structures for lossless ion manipulation (SLIM) with cryogenic infrared spectroscopy. We present here the design of a SLIM board containing a series of on-board traps in which we perform collision-induced dissociation (CID) at pressures in the millibar range. We characterize the on-board CID process by comparing the fragments generated from a pentapeptide to those obtained on a commercial tandem mass spectrometer. We then apply our new technique to study the mobility and vibrational spectra of CID fragments from two human milk oligosaccharides. Comparison of both the fragment drift times and IR spectra with those of suitable reference compounds allows us to identify their specific isomeric form, including the anomericity of the glycosidic linkage, demonstrating the power of this tool for glycan analysis.

Milk analysis using milk analyzers in a standardized setting (MAMAS) study: A multicentre quality initiative.

BACKGROUND: Human milk analyzers are increasingly used to rapidly measure the macronutrient content in breast milk for individual target fortification, to reduce the risk of postnatal growth restriction. However, many milk analyzers are used without calibration, validation or quality assurance. AIMS: To investigate measurement quality between different human milk analyzers, to test whether accuracy and precision of devices can be improved by establishing individual calibration curves, and to assess long-term stability of measurements, following good clinical laboratory practice (GCLP). METHODS: Sets of identical breast milk samples were sent to 13 participating centres in North America and Europe, for a total of 15 devices. The study included 3 sets of samples: A) initial assessment of the device's performance consisting of 10 calibration samples with random replicates; B) long term stability and quality control consisting of 2 batches of samples to be measured every time before the device is used, over 6 months; C) ring trial consisting of 2 samples to be measured monthly. The devices tested were Unity SpectraStar (n = 5) and MIRIS Human Milk Analyzer (n = 10). RESULTS: There are significant variations in accuracy and precision between different milk analyzers' fat, protein and lactose measurements. However, the accuracy of measurements can be improved by establishing individual correction algorithms. Repeated measurements are more robust when coming from a larger batch volume. Long term stability also varies between devices. CONCLUSION: The variations in measurements between devices are clinically significant and would impact both daily dietary prescriptions, and the outcomes of clinical studies assessing the effect of targeted adjustment of nutrient intake in preterm babies. This study shows that it is crucial to follow GCLP when using milk analyzers to ensure proper measurement of macronutrients, similar to what is required of other medical devices.

Calibration of Squalene, p-Cymene, and Sunflower Oil as Standard Oxidizable Substrates for Quantitative Antioxidant Testing.

The autoxidation kinetics of stripped sunflower oil (SSO), squalene (SQ), and p-cymene ( p-C) initiated by 2,2'-azobis(isobutyronitrile) at 303 K were investigated under controlled conditions by differential oximetry in order to build reference model systems that are representative of the natural variability of oxidizable materials, for quantitative antioxidant testing. Rate constants for oxidative chain propagation ( kp) and chain termination (2 kt) and the oxidizability ( kp/√2 kt) were measured using 2,6-di- tert-butyl-4-methoxyphenol, 2,2,5,7,8-pentamethyl-6-chromanol, BHT, and 4-methoxyphenol as reference antioxidants. Measured values of kp (M-1 s-1)/2 kt (M-1 s-1)/oxidizability (M-1/2 s-1/2) at 303 K in chlorobenzene were 66.9/3.45 × 106/3.6 × 10-2, 68.0/7.40 × 106/2.5 × 10-2, and 0.83/2.87 × 106/4.9 × 10-4, respectively, for SSO, SQ, and p-C. Quercetin, magnolol, caffeic acid phenethyl ester, and 2,4,6-trimethylphenol were investigated to validate calibrations. The distinctive usefulness of the three substrates in testing antioxidants is discussed.

Quantification of active ingredients in Potentilla tormentilla by Raman and infrared spectroscopy.

The most important active compounds present in Potentilla tormentilla rhizomes were quantitatively determined on the basis of Raman, attenuated total reflection (ATR) and diffuse reflectance mid- and near- infrared spectra (DRIFTS) collected for the untreated plant material. Partial least-squares (PLS) models were constructed utilizing vibrational spectra and the results of reference high-performance liquid chromatography analyses. Applying Raman spectroscopy, total polyphenols, tannins, ellagitannins, procyanidins, agrimoniin, 3-O-galloylquininc acid and catechin were simultaneously quantified in tormentil rhizomes, with the relative standard errors of prediction in the 2.0-4.9% range for both calibration and validation sets. These error ranges were found to be slightly higher for infrared techniques and amounted to 2.7-6.5%.

Applying risk management to analytical methods for the desorbing process of ginkgo diterpene lactone meglumine injection.

Analysis errors can occur in the desorbing process of ginkgo diterpene lactone meglumine injection (GDMI) by a conventional analysis method, due to several factors, such as easily crystallized samples, solvent volatility, time-consuming sample pre-processing, fixed method, and offline analysis. Based on risk management, near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were introduced to solve the above problems with the advantage of timely analysis and non-destructive nature towards samples. The objective of the present study was to identify the feasibility of using NIR or MIR spectroscopy techniques to increase the analysis accuracy of samples from the desorbing process of GDMI. Quantitative models of NIR and MIR were established based on partial least square method and the performances were calculated. Compared to NIR model, MIR model showed greater accuracy and applicability for the analysis of the GDMI desorbing solutions. The relative errors of the concentrations of Ginkgolide A (GA) and Ginkgolide B (GB) were 2.40% and 2.89%, respectively, which were less than 5.00%. The research demonstrated the potential of the MIR spectroscopy technique for the rapid and non-destructive quantitative analysis of the concentrations of GA and GB.

A Generalized Approach to Forensic Dye Identification: Development and Utility of Reference Libraries.

While color is arguably the most important optical property of evidential fibers, the actual dyestuffs responsible for its expression in them are, in forensic trace evidence examinations, rarely analyzed and still less often identified. This is due, primarily, to the exceedingly small quantities of dye present in a single fiber as well as to the fact that dye identification is a challenging analytical problem, even when large quantities are available for analysis. Among the practical reasons for this are the wide range of dyestuffs available (and the even larger number of trade names), the low total concentration of dyes in the finished product, the limited amount of sample typically available for analysis in forensic cases, and the complexity of the dye mixtures that may exist within a single fiber. Literature on the topic of dye analysis is often limited to a specific method, subset of dyestuffs, or an approach that is not applicable given the constraints of a forensic analysis. Here, we present a generalized approach to dye identification that (1) combines several robust analytical methods, (2) is broadly applicable to a wide range of dye chemistries, application classes, and fiber types, and (3) can be scaled down to forensic casework-sized samples. The approach is based on the development of a reference collection of 300 commercially relevant textile dyes that have been characterized by a variety of microanalytical methods (HPTLC, Raman microspectroscopy, infrared microspectroscopy, UV-Vis spectroscopy, and visible microspectrophotometry). Although there is no single approach that is applicable to all dyes on every type of fiber, a combination of these analytical methods has been applied using a reproducible approach that permits the use of reference libraries to constrain the identity of and, in many cases, identify the dye (or dyes) present in a textile fiber sample.

Green and fast determination of the alcoholic content of wines using thermal infrared enthalpimetry.

An innovative use of thermal infrared enthalpimetry (TIE) is proposed for the determination of alcoholic content of red and white wines. Notwithstanding the presence of ethanol in beverages, absolute ethanol was added directly to wines, and the temperature rise caused by the heat of dilution was monitored using an infrared camera. Analytical signals were obtained in only 10 s for four samples simultaneously, and a calibration curve was constructed with hydroalcoholic reference solutions. A linear calibration curve was obtained from 3.0 to 18.0% (v/v) ethanol (R2 = 0.9987). The results showed agreement ranging from 98.2 to 104.0% with 942.06 and 969.12 methods of AOAC. Organic compounds (e.g., sugar) did not interfere in the determinations. The proposed method provided fast results, with a throughput of 480 samples per hour and negligible energy consumption (0.001 kWh). In addition, the consumption of reagents was reduced when compared with conventional method fulfilling green analytical chemistry requirements.

Determination of honey adulteration with beet sugar and corn syrup using infrared spectroscopy and genetic-algorithm-based multivariate calibration.

BACKGROUND: Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm-1 wavenumber range. RESULTS: Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values. CONCLUSION: The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. © 2018 Society of Chemical Industry.

Centrifugal ultrafiltration of human serum for improving immunoglobulin A quantification using attenuated total reflectance infrared spectroscopy.

Attenuated total reflectance infrared (ATR-IR) spectroscopy is a simple, rapid and cost-effective method for the analysis of serum. However, the complex nature of serum remains a limiting factor to the reliability of this method. We investigated the benefits of coupling the centrifugal ultrafiltration with ATR-IR spectroscopy for quantification of human serum IgA concentration. Human serum samples (n = 196) were analyzed for IgA using an immunoturbidimetric assay. ATR-IR spectra were acquired for whole serum samples and for the retentate (residue) reconstituted with saline following 300 kDa centrifugal ultrafiltration. IR-based analytical methods were developed for each of the two spectroscopic datasets, and the accuracy of each of the two methods compared. Analytical methods were based upon partial least squares regression (PLSR) calibration models - one with 5-PLS factors (for whole serum) and the second with 9-PLS factors (for the reconstituted retentate). Comparison of the two sets of IR-based analytical results to reference IgA values revealed improvements in the Pearson correlation coefficient (from 0.66 to 0.76), and the root mean squared error of prediction in IR-based IgA concentrations (from 102 to 79 mg/dL) for the ultrafiltration retentate-based method as compared to the method built upon whole serum spectra. Depleting human serum low molecular weight proteins using a 300 kDa centrifugal filter thus enhances the accuracy IgA quantification by ATR-IR spectroscopy. Further evaluation and optimization of this general approach may ultimately lead to routine analysis of a range of high molecular-weight analytical targets that are otherwise unsuitable for IR-based analysis.

MS/IR, a new MS-based hyphenated method for analysis of hexuronic acid epimers in glycosaminoglycans.

We report an original MS-based hyphenated method for the elucidation of the epimerization in GAG fragments. It consists of measuring simultaneously the MS/MS spectrum and the gas phase IR spectrum to gain direct structural information. This is possible using a customized MS instrument, modified to allow injection of a tunable IR laser inside of the instrument for in situ spectroscopy of trapped ions. The proof of principle of this approach is performed in the case of a hyaluronic acid tetrasaccharide standard. In addition, we provide the reference IR fingerprint of glucuronic and Iduronic monosaccharide standards. Remarkably, we show that the gas phase IR fingerprint of reference hexuronic acid monosaccharides proves to be transposable to oligosaccharides. Therefore, the method presented here is predictive and allows structural elucidation of unknown GAG fragments, even in the absence of referenced standards.

Manual versus Automated moNitoring Accuracy of GlucosE II (MANAGE II).

BACKGROUND: Intravascular continuous glucose monitoring (CGM) may facilitate glycemic control in the intensive care unit (ICU). We compared the accuracy of a CGM device (OptiScanner®) with a standard reference method. METHODS: Adult patients who had blood glucose (BG) levels >150 mg/dl and required insertion of an arterial and central venous catheter were included. The OptiScanner® was inserted into a multiple-lumen central venous catheter. Patients were treated using a dynamic-scale insulin algorithm to achieve BG values between 80 and 150 mg/dl. The BG values measured by the OptiScanner® were plotted against BG values measured using a reference analyzer. The correlation between the BG values measured using the two methods and the clinical relevance of any differences were assessed using the coefficient of determination (r 2) and the Clarke error grid, respectively; bias was assessed by the mean absolute relative difference (MARD). Three different standards of glucose monitoring were used to assess accuracy. Glycemic control was assessed using the time in range (TIR). Six indices of glycemic variability were calculated. RESULTS: The analysis included 929 paired samples from 88 patients, monitored for a total of 2584 hours. Reference BG values ranged between 60 and 484 mg/dl. The r 2 value was 0.89. The percentage of BG values within zones A and B of the Clarke error grid was 99.9%; the MARD was 7.7%. Using the ISO 15197 standard and Food and Drug Administration and consensus standards, respectively, 80.4% of measurements were within 15 mg/dl and 88.2% within 15% of reference values, 40% of measurements were within 7 mg/dl and 72.5% within 10% of reference values, and 65.2% of measurements were within 10 mg/dl and 82.7% within 12.5% of reference values. The TIR was slightly lower with the OptiScanner® than with the reference method. The J-index, standard deviation and maximal glucose change were the indices of glycemic variability least affected by the measurement device. CONCLUSIONS: Based on the MARD, the performance of the OptiScanner® is adequate for use in ICU patients. Because recent standards for accuracy were not met, the OptiScanner® should not be used as a sole monitor. The assessment of glycemic variability is influenced by the time interval between BG determinations. TRIAL REGISTRATION: Clinicaltrials.gov NCT01720381 . Registered 31 October 2012.

Optimization extraction of polysaccharide from Tunisian Zizyphus lotus fruit by response surface methodology: Composition and antioxidant activity.

Response surface methodology using a Box-Behnken design was employed to optimize extraction temperature, extraction time and ratio of water to material to obtain a maximum polysaccharide yield with high uronic acid content and antioxidant property from edible Zizyphus lotus fruit. The optimal conditions were: extraction time of 3h 15min, extraction temperature of 91.2°C and water to solid ratio of 39mL/g. Under these conditions, the experimental extraction yield, uronic acid content and 2,2-diphenyl-1-picrylhydrazyl scavenging ability (IC50) were 18.88%, 41.89 and 0.518mg/mL, respectively. Chemical analysis revealed that the extract was composed of 97.92% carbohydrate of which 41.89% is uronic acid. The extracted polysaccharides, with an average molecular weight of 2720kDa, are composed of arabinose, rhamnose, glucose, fructose, galactose and xylose. Moreover, the polysaccharides exhibited a significant reducing power and anti-lipid peroxidation activities.

Calibration Adjustment of the Mid-infrared Analyzer for an Accurate Determination of the Macronutrient Composition of Human Milk.

BACKGROUND: Human milk composition analysis seems essential to adapt human milk fortification for preterm neonates. The Miris human milk analyzer (HMA), based on mid-infrared methodology, is convenient for a unique determination of macronutrients. However, HMA measurements are not totally comparable with reference methods (RMs). OBJECTIVE: The primary aim of this study was to compare HMA results with results from biochemical RMs for a large range of protein, fat, and carbohydrate contents and to establish a calibration adjustment. METHODS: Human milk was fractionated in protein, fat, and skim milk by covering large ranges of protein (0-3 g/100 mL), fat (0-8 g/100 mL), and carbohydrate (5-8 g/100 mL). For each macronutrient, a calibration curve was plotted by linear regression using measurements obtained using HMA and RMs. RESULTS: For fat, 53 measurements were performed, and the linear regression equation was HMA = 0.79RM + 0.28 (R(2) = 0.92). For true protein (29 measurements), the linear regression equation was HMA = 0.9RM + 0.23 (R(2) = 0.98). For carbohydrate (15 measurements), the linear regression equation was HMA = 0.59RM + 1.86 (R(2) = 0.95). A homogenization step with a disruptor coupled to a sonication step was necessary to obtain better accuracy of the measurements. Good repeatability (coefficient of variation < 7%) and reproducibility (coefficient of variation < 17%) were obtained after calibration adjustment. CONCLUSION: New calibration curves were developed for the Miris HMA, allowing accurate measurements in large ranges of macronutrient content. This is necessary for reliable use of this device in individualizing nutrition for preterm newborns.

Fast infrared spectroscopy of protein dynamics: advancing sensitivity and selectivity.

2D-IR spectroscopy has matured to a powerful technique to study the structure and dynamics of peptides, but its extension to larger proteins is still in its infancy, the major limitations being sensitivity and selectivity. Site-selective information requires measuring single vibrational probes at sub-millimolar concentrations where most proteins are still stable, which is a severe challenge for conventional (FT)IR spectroscopy. Besides its ultrafast time-resolution, a so far largely underappreciated potential of 2D-IR spectroscopy lies in its sensitivity gain. The present paper sets the goals and outlines strategies how to use that sensitivity gain together with properly designed vibrational labels to make IR spectroscopy a versatile tool to study a wide class of proteins.

Isotope-enriched protein standards for computational amide I spectroscopy.

We present a systematic isotope labeling study of the protein G mutant NuG2b as a step toward the production of reliable, structurally stable, experimental standards for amide I infrared spectroscopic simulations. By introducing isotope enriched amino acids into a minimal growth medium during bacterial expression, we induce uniform labeling of the amide bonds following specific amino acids, avoiding the need for chemical peptide synthesis. We use experimental data to test several common amide I frequency maps and explore the influence of various factors on map performance. Comparison of the predicted absorption frequencies for the four maps tested with empirical assignments to our experimental spectra yields a root-mean-square error of 6-12 cm(-1), with outliers of at least 12 cm(-1) in all models. This means that the predictions may be useful for predicting general trends such as changes in hydrogen bonding configuration; however, for finer structural constraints or absolute frequency assignments, the models are unreliable. The results indicate the need for careful testing of existing literature maps and shed light on possible next steps for the development of quantitative spectral maps.

A novel statistical approach to detect differences in fat and protein test values among mid-infrared spectrophotometers.

Our objective was to develop a statistical approach that could be used to determine whether a handler's fat, protein, or other solids mid-infrared (MIR) spectrophotometer test values were different, on average, from a milk regulatory laboratory's MIR test values when split-sampling test values are not available. To accomplish this objective, the Proc GLM procedure of SAS (SAS Institute Inc., Cary, NC) was used to develop a multiple linear regression model to evaluate 4 mo of MIR producer payment testing data (112 to 167 producers per month) from 2 different MIR instruments. For each of the 4 mo and each of the 2 components (fat or protein), the GLM model was Response=Instrument+Producer+Date+2-Way Interactions+3-Way Interaction. Instrument was significant in determining fat and protein tests for 3 of the 4 mo, and Producer was significant in determining fat and protein tests for all 4 mo. This model was also used to establish fat and protein least significant differences (LSD) between instruments. Fat LSD between instruments ranged from 0.0108 to 0.0144% (α=0.05) for the 4 mo studied, whereas protein LSD between instruments ranged from 0.0046 to 0.0085% (α=0.05). In addition, regression analysis was used to determine the effects of component concentration and date of sampling on fat and protein differences between 2 MIR instruments. This statistical approach could be performed monthly to document a regulatory laboratory's verification that a given handler's instrument has obtained a different test result, on average, from that of the regulatory laboratory's and that an adjustment to producer payment may be required.

[Preliminary investigation on polymorphs of two traditional Chinese medicine reference substances].

Crystal structures of chemical drugs has been being investigated widely. But few attention has been paid to polymorphs-phenomena of active ingredients from Traditional Chinese Medicine(TCM). Taking anhydrous dehydroandrographolide and hydrousprim-O-glucosylcimifugin as example, differences between TCM reference substances (RSs) with different crystal structures were discussed by using microscopy, melting point determination, differential thermal analysis (DTA) and infrared (IR) methods. The results showed that different crystal structures could lead to change of melting points, thermal behaviors and IR spectrum. It's indicated that polymorphs may be considered if different physicochemical properties were obtained when applying TCM RS. Differences of chemical properties of active ingredients from TCM with different crystal structures need further investigation.

Rapid detection of whey in milk powder samples by spectrophotometric and multivariate calibration.

A rapid method for the detection and quantification of the adulteration of milk powder by the addition of whey was assessed by measuring glycomacropeptide protein using mid-infrared spectroscopy (MIR). Fluid milk samples were dried and then spiked with different concentrations of GMP and whey. Calibration models were developed using multivariate techniques, from spectral data. For the principal component analysis and discriminant analysis, excellent percentages of correct classification were achieved in accordance with the increase in the proportion of whey samples. For partial least squares regression analysis, the correlation coefficient (r) and root mean square error of prediction (RMSEP) in the best model were 0.9885 and 1.17, respectively. The rapid analysis, low cost monitoring and high throughput number of samples tested per unit time indicate that MIR spectroscopy may hold potential as a rapid and reliable method for detecting milk powder frauds using cheese whey.