Interlaboratory comparison of test results of an ordinal or nominal binary property: analysis of variation

Applications of a new statistical method Ordinal Analysis of Variance (ORDANOVA) for interlaboratory comparisons of measurement or test results of semi-quantitative (ordinal) and qualitative (binary) properties are discussed. ORDANOVA can be helpful for validation of measurement or test methods, proficiency testing of laboratories, development of reference materials with certified semi-quantitative and qualitative properties, that is, probably in every field where ANOVA is applied for quantitative properties. A statistics and criteria are proposed for performance assessment of laboratories active in semi-quantitative and qualitative testing and for other purposes of statistical analysis of such test results.     

Probability of Detection (POD) as a statistical model for the validation of qualitative methods

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.     

Validation of high-performance thin-layer chromatographic methods for the identification of botanicals in a cGMP environment

Current Good Manufacturing Practices (cGMP) for botanicals stipulates the use of appropriate methods for identification of raw materials. Due to natural variability, chemical analysis of plant material is a great challenge and requires special approaches. This paper presents a comprehensive proposal to the process of validating qualitative high-performance thin-layer chromatographic (HPTLC) methods, proving that such methods are suitable for the purpose. The steps of the validation process are discussed and illustrated with examples taken from a project aiming at validation of methods for identification of green tea leaf, ginseng root, eleuthero root, echinacea root, black cohosh rhizome, licorice root, kava root, milk thistle aerial parts, feverfew aerial parts, and ginger root. The appendix of the paper, which includes complete documentation and method write-up for those plants, is available on the J. AOAC Int. Website (http://www.atypon-link.com/AOAC/loi/jaoi).     

Comparison and improvement of commonly applied statistical approaches for identification of plant species from IR spectra

Fourier transform infrared spectroscopy (FTIR) has been studied many times in the context of identification of plant, fungal and bacterial species. Infrared spectra are commonly analyzed using multivariate statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least squares analysis (PLS) and discriminant analysis (DA). In this study, a univariate statistical method for analysis of variance (ANOVA) was used to reduce the number of variables before applying the multivariate methods. Analyzing variables using ANOVA or a combination of ANOVA with CA produced better results. Here, experiments were carried out by performing ANOVA using the first derivative of the spectra instead of the original spectra or its second derivative because using the first‐derivative variables led to improved distinction between species. Different results were obtained by applying different validation methods. The leave‐one‐out validation method gave higher results than the validation‐with‐training and validation sample sets, thus indicating the non‐objectivity of the leave‐one‐out validation method. Copyright © 2010 John Wiley & Sons, Ltd.     

Selection and authentication of botanical materials for the development of analytical methods

Herbal products, for example botanical dietary supplements, are widely used. Analytical methods are needed to ensure that botanical ingredients used in commercial products are correctly identified and that research materials are of adequate quality and are sufficiently characterized to enable research to be interpreted and replicated. Adulteration of botanical material in commerce is common for some species. The development of analytical methods for specific botanicals, and accurate reporting of research results, depend critically on correct identification of test materials. Conscious efforts must therefore be made to ensure that the botanical identity of test materials is rigorously confirmed and documented through preservation of vouchers, and that their geographic origin and handling are appropriate. Use of material with an associated herbarium voucher that can be botanically identified is always ideal. Indirect methods of authenticating bulk material in commerce, for example use of organoleptic, anatomical, chemical, or molecular characteristics, are not always acceptable for the chemist’s purposes. Familiarity with botanical and pharmacognostic literature is necessary to determine what potential adulterants exist and how they may be distinguished.     

Uncertainty of Qualitative Chemical Analysis: General Methodology and Binary Test Methods

Some general problems of qualitative chemical analysis are considered. In particular, the context of its development is outlined, the concept of hypothesis testing as a basis for the detection and identification of chemical substances is presented, a classification of the types of analysis is given, and the uncertainty (reliability, accuracy) of qualitative determinations is discussed. Various errors arising from the use of binary test methods are reviewed, and methods for estimating these errors are surveyed. The estimates are based on the false (or true) rates of positive and negative results. The concentration dependence of these rates is discussed. It is shown that the testing results become more reliable if the prior probability of the presence of the analyte in the sample is known. Another method for improving the validity of analysis is to use two test methods or to confirm the testing data by other analytical means. In these cases, the positive and negative predictive values are estimated using Bayesian statistic. The approaches to the estimation of the uncertainty of test methods widely used in medicine and toxicology are extended to qualitative chemical analysis as a whole.     

A new profile likelihood confidence interval for the mean probability of detection in collaborative studies of binary test methods

A confidence interval for the probability of detection across laboratories (LPOD) for qualitative methods, described in the AOAC INTERNATIONAL guidelines for validation of microbiological methods for food and environmental surfaces, is considered. It is demonstrated that under certain conditions, the observed confidence of this confidence interval can be rather low, so that statistical minimum requirements are not fulfilled. A new profile likelihood confidence interval based on a latent random laboratory effect approach is proposed. Observed confidence levels for this confidence interval demonstrate its applicability already for a small number of laboratories.     

On-line identification of phytochemical constituents in botanical extracts by combined high-performance liquid chromatographic-diode array detection-mass spectrometric techniques

It is necessary to determine all of the phytochemical constituents of botanical extracts in order to ensure the reliability and repeatability of pharmacological and clinical research, to understand their bioactivities and possible side effects of active compounds and to enhance product quality control. HPLC chromatographic fingerprints can be applied for this kind of documentation. Combined HPLC-diode array detection–MS techniques can provide on-line UV and MS information for each peak in a chromatogram. In most cases, direct identification of the peaks is possible, based on comparison with published data or with standard compounds. This review will primarily focus on electrospray and thermospray ionization MS and their applications for the qualitative analyses of phenolic compounds, saponins, alkaloids and other classes of natural products in botanical extracts. Twenty-one of the most commonly used herbal examples, their phytochemical analyses and characteristics of their mass spectra are described.     

Near infrared reflectance spectroscopy for the fast identification of PVC-based films

Near infrared (NIR) reflectance spectroscopy was used to develop a non-destructive and rapid qualitative method for the analysis of plastic films used by the pharmaceutical industry for blistering. Three types of films were investigated: 250 microm PVC [poly(vinyl chloride)] films, 250 microm PVC films coated with 40 g m(-2) of PVDC [poly(vinylidene dichloride)] and 250 microm PVC films coated with 5 g m(-2) of TE (Thermoelast) and 90 g m(-2) of PVDC. Three analyses were carried out using different pre-treatment options and a PLS (partial least squares) algorithm. Each analysis was aimed at identifying one type of film and rejecting all types of false sample (different thickness, colour or layer). True and false samples from four plastics manufacturers were included in the calibration sets in order to obtain robust methods that were suitable regardless of the supplier. Specificity was demonstrated by testing validation sets against the methods. The tests showed 0% of type I (false negative identification) and 1% of type II errors (false positive identification) for the PVC method, 13 and 3%, respectively, for the PVC-PVDC method and no error for the PVC-TE-PVDC method. Type II errors, mostly due to the slight sensitivity of the methods to film thickness, are easily corrected by simple thickness measurements. This study demonstrates that NIR spectroscopy is an excellent tool for the identification of PVC-based films. The three methods can be used by the pharmaceutical industry or plastics manufacturers for the quality control of films used in blister packaging.     

Differentiating the gum resins of two closely related Indian Gardenia species, G. gummifera and G. lucida, and establishing the source of dikamali gum resin using high-performance thin-layer chromatography and ultra-performance liquid chromatography-UV/MS

Dikamali is a gum resin obtained from the leaf buds of Gardenia lucida or G. gummifera. There is controversy regarding the botanical source of this gum resin with some stating it to be from G. lucida while others claim it to be from G. gummifera. Analytical methods including UPLC and HPTLC were developed for the qualitative analysis of Gardenia species and various commercial samples. The separation using a UPLC method was achieved within 12.0 min by using C18 column material, a water/acetonitrile mobile phase, both containing formic acid, a gradient system, and a temperature of 40 degrees C. Extensive studies of dikamali collected from various parts of India in comparison with the gum resins collected from G. lucida and G. gummifera clearly indicated that the botanical source of commercially available dikamali is G. lucida, not G. gummifera. The marker compounds isolated from a market sample of dikamali were present only in the gum resin of G. lucida and the compounds isolated from G. gummifera were not present in any of the dikamali samples, confirming the botanical source of dikamali. This work is of utmost importance, given the ambiguity regarding the botanical source of the gum resin dikamali. LC/MS coupled with electrospray ionization is described for the identification and confirmation of nine compounds from various samples of the gum resin. An HPTLC method was also developed for the fast chemical fingerprint analysis of Gardenia samples.     

On the identification of differentially expressed genes: improving the generalized F-statistics for Affymetrix microarray gene expression data

It has been shown that the generalized F-statistics can give satisfactory performances in identifying differentially expressed genes with microarray data. However, for some complex diseases, it is still possible to identify a high proportion of false positives because of the modest differential expressions of disease related genes and the systematic noises of microarrays. The main purpose of this study is to develop statistical methods for Affymetrix microarray gene expression data so that the impact on false positives from non-expressed genes can be reduced. I proposed two novel generalized F-statistics for identifying differentially expressed genes and a novel approach for estimating adjusting factors. The proposed statistical methods systematically combine filtering of non-expressed genes and identification of differentially expressed genes. For comparison, the discussed statistical methods were applied to an experimental data set for a type 2 diabetes study. In both two- and three-sample analyses, the proposed statistics showed improvement on the control of false positives.     

Methodology of computer-assisted identification of substances using information retrieval systems

The methodology of substance identification has been analyzed on the basis of a review of publications on computer-assisted qualitative analysis of mixtures using databases and information retrieval systems. A system of terms necessary for the development of an identification theory is proposed. The system is not oriented to any particular method. The most important aspects of the study seem to be calculations of identification criteria based on the probability theory and purposeful selection of more characteristic search attributes.     

Origin Identification of Hungarian Honey Using Melissopalynology,Physicochemical Analysis,and Near Infrared Spectroscopy

The objective of the study was to check the authenticity of Hungarian honey using physicochemical analysis, near infrared spectroscopy, and melissopalynology. In the study, 87 samples from different botanical origins such as acacia, bastard indigo, rape, sunflower, linden, honeydew, milkweed, and sweet chestnut were collected. The samples were analyzed by physicochemical methods (pH, electrical conductivity, and moisture), melissopalynology (300 pollen grains counted), and near infrared spectroscopy (NIRS:740–1700 nm). During the evaluation of the data PCA-LDA models were built for the classification of different botanical and geographical origins, using the methods separately, and in combination (low-level data fusion). PC number optimization and external validation were applied for all the models. Botanical origin classification models were >90% and >55% accurate in the case of the pollen and NIR methods. Improved results were obtained with the combination of the physicochemical, melissopalynology, and NIRS techniques, which provided >99% and >81% accuracy for botanical and geographical origin classification models, respectively. The combination of these methods could be a promising tool for origin identification of honey.     

The validation of methods for regulatory purposes in the control of residues

The topic of validation is diversified. This review outlines the validation strategies which can be found in national, international and supranational regulations, compares them with one another and aims to elaborate on the main principles. European regulations and legislation, Codex alimentarius guidelines, the official methods program of the AOAC, and naturally the relevant ISO standards, particularly the ISO 5725 series, are taken into consideration. The objective of every validation is to demonstrate fitness for purpose. This varies of course in its characteristics for the diverse uses. However, all approaches have in common the objective of harmonisation of food control by using effective and reliable methods. To this end, criteria are determined and validation models developed and made compulsory. ISO 5725 is the central basis for validations for quantitative methods with its validation specifications through method collaborative studies. On the contrary, there are no valid uniform international method specifications for qualitative methods. Collaborative studies are in opposition to single-lab-validations with different sources of error. Whereas laboratory errors are predominant in collaborative studies, the single-lab-validation or in-house validation concentrates particularly on time and processing errors (intermediate precision). In new statistical models for in-house validations, the matrix mismatch error is also considered. The validation models presented here are of a general nature and can be used in principle for all analytical methods. Correct and appropriate statistical modelling is very important.     

Measurement uncertainty of thermodynamic data

Thermodynamic quantities of chemical reactions are commonly derived from experimental data obtained by chemical analysis. The accuracy of the evaluated thermodynamic quantities is limited by the measurement uncertainty of the analytical techniques applied. Straightforward transfer of metrological rules established for determination of single analytes to the more complex process of evaluating values of thermodynamic quantities is not possible. Computer-intensive statistical methods and Monte Carlo techniques are shown to enable integration of existing metrological concepts. An initial stage of the integration of both concepts is presented, taking solubility data for Am(III) in carbonate media as an illustrative example. A cause and effect diagram is created as a means of identification of sources of uncertainty. The uncertainties are used in a resampling-based Monte Carlo study to produce a probability distribution of the value of a quantity.     

Quality control for organic trace analyses

There has been increasing emphasis in organic trace analyses on both accurate qualitative identifications and quantitative estimates of concentrations present. An understanding of the sources of random and systematic errors and application of basic statistical concepts permits more accurate analyses to be made. Capillary gas chromatography—mass spectrometry has provided for improved qualitative identification, while isotope dilution calibration and analysis has improved the accuracy of results.     

An Improved POD Model for Fast Semi-Quantitative Analysis of Carbendazim in Fruit by Surface Enhanced Raman Spectroscopy

The current detection method of carbendazim suffers from the disadvantages of complicated preprocessing and long cycle time. In order to solve the problem of rapid quantitative screening of finite contaminants, this article proposed a qualitative method based on characteristic peaks and a semi-quantitative method based on threshold to detect carbendazim in apple, and finally the method is evaluated by a validation system based on binary output. The results showed that the detection limit for carbendazim was 0.5 mg/kg, and the detection probability was 100% when the concentration was no less than 1 mg/kg. The semi-quantitative analysis method had a false positive rate of 0% and 5% at 0.5 mg/kg and 2.5 mg/kg, respectively. The results of method evaluation showed that when the added concentration was greater than 2.5 mg/kg, the qualitative detection method was consistent with the reference method. When the concentration was no less than 5 mg/kg, the semi-quantitative method is consistent between different labs. The semi-quantitative method proposed in this study can achieve the screening of finite contaminants in blind samples and simplify the test validation process through the detection probability model, which can meet the needs of rapid on-site detection and has a good application prospect.     

Qualitative and quantitative analysis of toosendanin in Melia toosendan Sieb. Et Zucc (Meliaceae) with liquid chromatography/tandem mass spectrometry

Toosendanin (TSN) is a triterpenoid derivative found in Melia toosendan Sieb. Et Zucc (Meliaceae) or chinaberry. TSN present in the medicinal plants was first isolated and established by spectroscopic methods. In this report, high-performance liquid chromatography (HPLC) separation using columns of smaller particle size with tandem mass spectrometry (MS(n)) was used for the rapid determination of TSN in botanical extracts. A comparison of different fragmentation patterns shows that the results from positive and negative ion electrospray ionization (ESI)-MS(n) are complementary. The two modes can yield structurally significant information for the characterization and rapid identification of TSN in botanical extracts. The data obtained showed that MS(3) generated more characteristic ions that are useful for the identification of TSN in unknown samples. The separation of TSN was achieved with a water/acetonitrile gradient system using a short C18 reversed-phase column with small particle size (50 x 2.0 mm, 3.5 microm). With LC/MS, the quantitative analysis of TSN in the botanical extracts was done using external standard calibration and the method precision was found to vary from 4.3 to 7.6% (RSD, n = 5) on different days.     

Characterization of a suite of ginkgo-containing standard reference materials

A suite of three ginkgo-containing dietary supplement Standard Reference Materials (SRMs) has been issued by the National Institute of Standards and Technology (NIST) with certified values for flavonoid aglycones, ginkgolides, bilobalide, and selected toxic trace elements. The materials represent a range of matrices (i.e., plant, extract, and finished product) that provide different analytical challenges. The constituents have been determined by at least two independent analytical methods with measurements performed by NIST and at least one collaborating laboratory. The methods utilized different extractions, chromatographic separations, modes of detection, and approaches to quantitation. The SRMs are primarily intended for method validation and for use as control materials to support the analysis of dietary supplements and related botanical materials. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantitative assessment of the reliability of identification by high-performance liquid chromatography-mass spectrometry

At present, mass spectrometry (MS) is the most reliable method for identification but there is not yet a quantitative equation describing this fact. In this investigation an approach to the quantitative assessment of the reliability of identification by MS is proposed which is useful for determination of the selectivity and the validation of analytical methods. Mass spectra of the analytes are presented as maps in which the characteristic ions and their intensities are used for identification. A formula for the quantitative expression of the significance of these parameters to the reliability and the identification is given. The contribution of the resolution of MS instruments or their possibilities of a multiple fragmentation to the reliability of the identification is shown. This approach makes it possible to compare the reliability of identification with different MS instruments. Despite the small contribution of the separation of the chromatographic column compared to the MS separation, the role of the column in the identification is very important to distinguish isomers because their MS spectra are similar.