Fast identification of Echinacea purpurea dried roots using near-infrared spectroscopy

Natural complex substances: From molecules to the molecular complexes. Analytical and technological advances for their definition and differentiation from the corresponding synthetic substances

Natural complex substances (NCSs) are a heterogeneous family of substances that are notably used as ingredients in several products classified as food supplements, medical devices, cosmetics and traditional medicines, according to the correspondent regulatory framework. The compositions of NCSs vary widely and hundreds to thousands of compounds can be present at the same time. A key concept is that NCSs are much more than the simple sum of the compounds that constitute them, in fact some emerging phenomena are the result of the supramolecular interaction of the constituents of the system. Therefore, close attention should be paid to produce and characterize these systems. Today many natural compounds are produced by chemical synthesis and are intentionally added to NCSs, or to formulated natural products, to enhance their properties, lowering their production costs. Market analysis shows a tendency of people to use products made with NCSs and, currently, products made with ingredients of natural origin only are not conveniently distinguishable from those containing compounds of synthetic origin. Furthermore, the uncertainty of the current European regulatory framework does not allow consumers to correctly differentiate and identify products containing only ingredients of natural origin. The high demand for specific and effective NCSs and their high-cost offer on the market, create the conditions to economically motivated sophistications, characterized by the addition of a cheap material to a more expensive one, just to increase profit. This type of practice can concern both the addition of less valuable natural materials and the addition of pure artificial compounds with the same structure as those naturally present. In this scenario, it becomes essential for producers of natural products to have advanced analytical techniques to evaluate the effective naturalness of NCSs. In fact, synthetically obtained compounds are not identical to their naturally occurring counterparts, due to the isotopic composition or chirality, as well as the presence of different trace metabolites (since pure substances in nature do not exist). For this reason, in this review, the main analytical tests that can be performed to differentiate natural compounds from their synthetic counterparts will be highlighted and the main analytical technologies will be described. At the same time, the main fingerprint techniques useful for characterizing the complexity of the NCSs, also allowing their identification and quali-quantitative evaluation, will be described. Furthermore, NCSs can be produced through different manufacturing processes, not all of which are on the same level of quality. In this review the most suitable technologies for green processes that operate according to physical extraction principles will be presented, as according to the authors they are the ones that come closest to creating more life-cycle compatible NCSs and that are well suited to the European green deal, a strategy with the aim of transforming the EU into a sustainable and resource-efficient society by 2050.

Botanical Ingredient Forensics: Detection of Attempts to Deceive Commonly Used Analytical Methods for Authenticating Herbal Dietary and Food Ingredients and Supplements

Botanical ingredients are used widely in phytomedicines, dietary/food supplements, functional foods, and cosmetics. Products containing botanical ingredients are popular among many consumers and, in the case of herbal medicines, health professionals worldwide. Government regulatory agencies have set standards (collectively referred to as current Good Manufacturing Practices, cGMPs) with which suppliers and manufacturers must comply. One of the basic requirements is the need to establish the proper identity of crude botanicals in whole, cut, or powdered form, as well as botanical extracts and essential oils. Despite the legal obligation to ensure their authenticity, published reports show that a portion of these botanical ingredients and products are adulterated. Most often, such adulteration is carried out for financial gain, where ingredients are intentionally substituted, diluted, or "fortified" with undisclosed lower-cost ingredients. While some of the adulteration is easily detected with simple laboratory assays, the adulterators frequently use sophisticated schemes to mimic the visual aspects and chemical composition of the labeled botanical ingredient in order to deceive the analytical methods that are used for authentication. This review surveys the commonly used approaches for botanical ingredient adulteration and discusses appropriate test methods for the detection of fraud based on publications by the ABC-AHP-NCNPR Botanical Adulterants Prevention Program, a large-scale international program to inform various stakeholders about ingredient and product adulteration. Botanical ingredients at risk of adulteration include, but are not limited to, the essential oils of lavender (Lavandula angustifolia, Lamiaceae), rose (Rosa damascena, Rosaceae), sandalwood (Santalum album, Santalaceae), and tea tree (Melaleuca alternifolia, Myrtaceae), plus the extracts of bilberry (Vaccinium myrtillus, Ericaceae) fruit, cranberry (Vaccinium macrocarpon, Ericaceae) fruit, elder (Sambucus nigra, Viburnaceae) berry, eleuthero (Eleutherococcus senticosus, Araliaceae) root, ginkgo (Ginkgo biloba, Ginkgoaceae) leaf, grape (Vitis vinifera, Vitaceae) seed, saw palmetto (Serenoa repens, Arecaceae) fruit, St. John's wort (Hypericum perforatum, Hypericaceae) herb, and turmeric (Curcuma longa, Zingiberaceae) root/rhizome, among numerous others.

Authentication of Herbal Medicines Based on Modern Analytical Technology Combined with Chemometrics Approach: A Review

Since ancient times, herbal medicines (HMs) have been widely popular with consumers as a "natural" drug for health care and disease treatment. With the emergence of problems, such as increasing demand for HMs and shortage of resources, it often occurs the phenomenon of shoddy exceed and mixing the false with the genuine in the market. There is an urgent need to evaluate the quality of HMs to ensure their important role in health care and disease treatment, and to reduce the possibility of threat to human health. Modern analytical technology is can be analyzed for analyzing chemical components of HMs or their preparations. Reflecting complex chemical components' characteristic curves in the analysis sample, and the comprehensive effect of active ingredients of HMs. In this review, modern analytical technology (chromatography, spectroscopy, mass spectrometry), chemometrics methods (unsupervised, supervised) and their advantages, disadvantages, and applicability were introduced and summarized. In addition, the authentication application of modern analytical technology combined with chemometrics methods in four aspects, including origin, processing methods, cultivation methods, and adulteration of HMs have also been discussed and illustrated by a few typical studies. This article offers a general workflow of analytical methods that have been applied for HMs authentication and explains that the accuracy of authentication in favor of the quality assurance of HMs. It was provided reference value for the development and application of modern HMs.

Exploring the phytochemical variation of non-volatile metabolites within three South African Salvia species using UPLC-MS fingerprinting and chemometric analysis

The South African Salvia species, Salvia africana-lutea, S. lanceolata and S. chamelaeagnea, are widely used to treat fever and inflammation associated with skin and lung infections. The aim of this study was to explore the non-volatile secondary metabolites and the phytochemical variation within these lesser known species, to support product development and commercialisation. Chemical profiles of the methanol extracts of 81 wild-harvested samples were obtained using ultra performance-quadrupole-Time-of-Flight-mass spectrometry (UPLC-qToF-MS). Forty-one compounds, including caffeic acid, rosmarinic acid, carnosol, carnosic acid and ursolic acid, were detected and confirmed across the three species. Nineteen compounds were tentatively identified of which 14 have not been reported in these species. Principal component analysis revealed distinct clusters corresponding to the three species, confirming chemical differences. Marker compounds for each species were revealed using orthogonal projection to latent structures-discriminant analysis. Further chemometric analysis reflected a degree of intraspecies variation, although the chemistry within populations was mostly conserved. Potential chemotypes for each species were identified through unique compounds associated with each group. The concentrations of medicinally important metabolites, namely, rosmarinic acid, carnosol, carnosic acid and ursolic acid, were determined, using validated UPLC-PDA methods. Ursolic acid was present at levels up to 38.2 mg/g, confirming that these species are a rich source of this compound. No similar studies combining liquid chromatography with chemometric analysis, and utilising a large sample size from various habitats, have been reported for these three Salvia species. The results will guide selection of cultivars with the best attributes for the intended therapeutic application, thereby protecting wild populations from over-exploitation.

Non-Targeted Detection of Adulterants in Almond Powder Using Spectroscopic Techniques Combined with Chemometrics

Methods that combine targeted techniques and chemometrics for analyzing food authenticity can only facilitate the detection of predefined or known adulterants, while unknown adulterants cannot be detected using such methods. Therefore, the non-targeted detection of adulterants in food products is currently in great demand. In this study, FT-IR and FT-NIR spectroscopic techniques were used in combination with non-targeted chemometric approaches, such as one-class partial least squares (OCPLS) and data-driven soft independent modeling of class analogy (DD-SIMCA), to detect adulterants in almond powder adulterated with apricot and peanut powders. The reflectance spectra of 100 pure almond powder samples from two different varieties (50 each) were collected to develop a calibration model based on each spectroscopic technique; each model was then evaluated for four independent sets of two varieties of almond powder samples adulterated with different concentrations of apricot and peanut powders. Classification using both techniques was highly sensitive, the OCPLS approach yielded 90-100% accuracy in different varieties of samples with both spectroscopic techniques, and the DD-SIMCA approach achieved the highest accuracy of 100% when used in combination with FT-IR in all validation sets. Moreover, DD-SIMCA, combined with FT-NIR, achieved a detection accuracy between 91% and 100% for the different validation sets and the misclassified samples belong to the 5% and 7% adulteration sets. These results suggest that spectroscopic techniques, combined with one-class classifiers, can be used effectively in the high-throughput screening of potential adulterants in almond powder.

FT-NIR characterization with chemometric analyses to differentiate goldenseal from common adulterants

Goldenseal (Hydrastis canadensis L.) has been a popular herb since the 1970s, with a US market share of over $32 million in 2014. Wild goldenseal has been listed in the Convention on International Trade in Endangered Species for decades. Limits in supply and greed for profit have led to adulteration with similar but more accessible and inexpensive plant materials. Fourier transform near-infrared spectroscopy (FT-NIR) coupled with three different chemometric models, partial least squares (PLS) regression, soft independent modeling of class analogy (SIMCA), and moving window principal component analysis (MW-PCA) provide fast, simple, nondestructive approaches to differentiating pure goldenseal from 4 common pure adulterants (yellow dock, yellow root, coptis, Oregon grape). All three models successfully differentiated authentic goldenseal from adulterants. The models were t-tested for detection of goldenseal intentionally mixed with individual adulterants at 2% to 95% theoretical levels made computationally. The PLS model was unable to detect adulterants mixed with goldenseal at any level. The SIMCA model was the best for detection of yellow root and Oregon grape adulteration in goldenseal, as low as 10%. The MW-PCA model proved best for detection of yellow dock at ≥ 15% and coptis adulteration ≥5% in goldenseal. This study demonstrates that NIR spectroscopy coupled with chemometric analyses is a good tool for industry and investigators to implement for rapid detection of goldenseal adulteration in the marketplace, but also indicates that the specific approach to chemometric analysis must be evaluated and selected on a case-by-case basis in order to achieve useful sensitivity and specificity.

An analysis of Echinacea chloroplast genomes: Implications for future botanical identification

Echinacea is a common botanical used in dietary supplements, primarily to treat upper respiratory tract infections and to support immune function. There are currently thought to be nine species in the genus Echinacea. Due to very low molecular divergence among sister species, traditional DNA barcoding has not been successful for differentiation of Echinacea species. Here, we present the use of full chloroplast genomes to distinguish between all 9 reported species. Total DNA was extracted from specimens stored at the National Museum of Natural History, Smithsonian Institution, which had been collected from the wild with species identification documented by experts in the field. We used Next Generation Sequencing (NGS) and CLC Genomics Workbench to assemble complete chloroplast genomes for all nine species. Full chloroplasts unambiguously differentiated all nine species, compared with the very few single nucleotide polymorphisms (SNPs) available with core DNA barcoding markers. SNPs for any two Echinacea chloroplast genomes ranged from 181 to 910, and provided robust data for unambiguous species delimitation. Implications for DNA-based species identification assays derived from chloroplast genome sequences are discussed in light of product safety, adulteration and quality issues.

The Importance of Method Selection in Determining Product Integrity for Nutrition Research

The American Herbal Products Association estimates that there as many as 3000 plant species in commerce. The FDA estimates that there are about 85,000 dietary supplement products in the marketplace. The pace of product innovation far exceeds that of analytical methods development and validation, with new ingredients, matrixes, and combinations resulting in an analytical community that has been unable to keep up. This has led to a lack of validated analytical methods for dietary supplements and to inappropriate method selection where methods do exist. Only after rigorous validation procedures to ensure that methods are fit for purpose should they be used in a routine setting to verify product authenticity and quality. By following systematic procedures and establishing performance requirements for analytical methods before method development and validation, methods can be developed that are both valid and fit for purpose. This review summarizes advances in method selection, development, and validation regarding herbal supplement analysis and provides several documented examples of inappropriate method selection and application.

DNA barcoding: an efficient tool to overcome authentication challenges in the herbal market

The past couple of decades have witnessed global resurgence of herbal-based health care. As a result, the trade of raw drugs has surged globally. Accurate and fast scientific identification of the plant(s) is the key to success for the herbal drug industry. The conventional approach is to engage an expert taxonomist, who uses a mix of traditional and modern techniques for precise plant identification. However, for bulk identification at industrial scale, the process is protracted and time-consuming. DNA barcoding, on the other hand, offers an alternative and feasible taxonomic tool box for rapid and robust species identification. For the success of DNA barcode, the barcode loci must have sufficient information to differentiate unambiguously between closely related plant species and discover new cryptic species. For herbal plant identification, matK, rbcL, trnH-psbA, ITS, trnL-F, 5S-rRNA and 18S-rRNA have been used as successful DNA barcodes. Emerging advances in DNA barcoding coupled with next-generation sequencing and high-resolution melting curve analysis have paved the way for successful species-level resolution recovered from finished herbal products. Further, development of multilocus strategy and its application has provided new vistas to the DNA barcode-based plant identification for herbal drug industry. For successful and acceptable identification of herbal ingredients and a holistic quality control of the drug, DNA barcoding needs to work harmoniously with other components of the systems biology approach. We suggest that for effectively resolving authentication challenges associated with the herbal market, DNA barcoding must be used in conjunction with metabolomics along with need-based transcriptomics and proteomics.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination.

A Review of Optical Nondestructive Visual and Near-Infrared Methods for Food Quality and Safety

This paper is a review of optical methods for online nondestructive food quality monitoring. The key spectral areas are the visual and near-infrared wavelengths. We have collected the information of over 260 papers published mainly during the last 20 years. Many of them use an analysis method called chemometrics which is shortly described in the paper. The main goal of this paper is to provide a general view of work done according to different FAO food classes. Hopefully using optical VIS/NIR spectroscopy gives an idea of how to better meet market and consumer needs for high-quality food stuff.

Application of chemometrics in authentication of herbal medicines: a review

INTRODUCTION

Herbal medicines (HM) and their preparations have been widely used for hundreds of years all over the world. However, they have not been officially recognised due to a lack of adequate or accepted research methodology for their evaluation.

OBJECTIVE

To present a concise overview of the recent applications of chemometrics in solving the ambiguity of herbal medicine authentication during the last two decades.

METHODOLOGY

Studies involving the applications of chemometric analysis in combination with different analytical methods were classified according to the method of analysis used including chromatographic (HPLC, GC and CE), spectroscopic (NMR, IR, UV and ICP) and genetic analysis (RAPD). The purpose of each of these studies was classified into one of three main categories: taxonomic discrimination, quality assessment or classification between plants of different geographic origins.

RESULTS

This review comprises over 150 studies, covering the past two decades, emphasising the significance of chemometric methods in the discrimination of many herbs from closely related species and from adulterants, based on the principal bioactive components and phytochemical diversity. Furthermore, the differentiation between varieties and hybrids was achieved in addition to the prediction of the active components by quantitative methods of analysis. Discrimination according to geographical origin and localities, processing methods, DNA profiling and metabolomics were also efficiently investigated.

CONCLUSION

Chemometric methods have provided an efficient and powerful tool for the quality control and authentication of different herbs.

Use of FTIR for rapid authentication and detection of adulteration of food

Fourier transform infrared (FTIR) spectroscopy is an appealing technology for the food industry because simple, rapid, and nondestructive measurements of chemical and physical components can be obtained. Advances in FTIR instrumentation combined with the development of powerful multivariate data analysis methods make this technology ideal for large volume, rapid screening and characterization of minor food components down to parts per billion (ppb) levels. Because of the use of FTIR techniques in quality and process control applications, the food industry is already familiar with the technology and its potential to expand to monitoring for food adulteration. The aim of this review is to compile the current research on applications of near infrared (NIR) and mid-infrared (MIR) spectroscopy for rapid authentication and detection of adulteration in food.

Enhanced chromatographic fingerprinting of herb materials by multi-wavelength selection and chemometrics

A strategy for multi-wavelength chromatographic fingerprinting of herbal materials, using high performance liquid chromatography with a UV-Vis diode array detector is presented. Valeriana officinalis was selected to show the proposed methodology since it is a widely used commercially available herbal drug, and because misfit with other valerian species is a current issue. The enhanced fingerprints were constructed by compiling into a single data vector the chromatograms from four wavelengths (226, 254, 280 and 326 nm), at which characteristic chemical constituents of studied herbs presented maximum absorbance. Chromatographic data pretreatment included baseline correction, normalization and correlation optimized warping. A simplex optimization was performed to retrieve the optimal values of the parameters used in the warping. General success rates of a classification above 90% were achieved by soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The sensitivity and specificity of constructed models were above 94%. Tests on laboratory-made mixtures showed that it is possible to detect adulterations or counterfeits with 5% foreign herbal material, even if it is from the Valerianaceae family. The results suggest that the proposed enhanced fingerprinting approach can be used to authenticate herb materials with complex chromatographic profiles.

Analysis of alkylamides in Echinacea plant materials and dietary supplements by ultrafast liquid chromatography with diode array and mass spectrometric detection

Alkylamides are a class of compounds present in plants of the genus Echinacea (Asteraceae), which have been shown to have high bioavailability and immunomodulatory effects. Fast analysis to identify these components in a variety of products is essential to profile products used in clinical trials and for quality control of these products. A method based on ultrafast liquid chromatography (UFLC) coupled with diode array detection and electrospray ionization mass spectrometry was developed for the analysis of alkylamides from the roots of Echinacea angustifolia (DC.) Hell., Echinacea purpurea (L.) Moench, and commercial dietary supplements. A total of 24 alkylamides were identified by LC-MS. The analysis time for these components is 15 min. Compared to the alkylamide profiles determined in the Echinacea root materials, the commercial products showed a more complex profile due to the blending of root and aerial parts of E. purpurea. This versatile method allows for the identification of alkylamides in a variety of Echinacea products and presents the most extensive characterization of alkylamides in E. angustifolia roots so far.

Construction of an efficacious model for a nondestructive identification of traditional Chinese medicines Liuwei Dihuang pills from different manufacturers using near-infrared spectroscopy and moving window partial least-squares discriminant analysis

This paper reports on the construction of an efficacious model for a non-invasive identification of traditional Chinese medicines, Liuwei Dihuang pills from different manufacturers, on the basis of near-infrared spectra (NIRS) coupled with moving window partial least-squares discriminant analysis (MWPLSDA). Considering the continuity of near-infrared spectral measurements, MWPLSDA is used to identify continuous and highly classification-related information intervals, a simple, yet effective classification model that can be developed for identifying accurate 150 Liuwei Dihuang pills from five different manufacturers. Meanwhile, the method is compared with some traditional pattern-recognition methods including principal component analysis (PCA), linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLSDA). The obtained results show that the method not only can reduce the operation time, but also significantly improves the classification accuracy. Hence, the nondestructive method can be expected to be promising for more practical applications on quality control and the discrimination of traditional Chinese medicine.

A strategy for evaluating antipyretic efficacy of Chinese herbal medicines based on UV spectra fingerprints

ETHNOPHARMACOLOGICAL RELEVANCE

Quality analysis and control of Chinese herbal medicines (CHM) or herbal medicines (HM) are being more and more investigated based on fingerprint analysis, and there are also some researches on correlating fingerprints of CHM to their efficacy. Multi-component analysis methods together with fingerprints are considered potential useful tools to select candidate herbal drugs from extracts of herbs in pharmacological/bio-prospecting investigations.

AIM OF THE STUDY

To explore a strategy for evaluating efficacy strength of CHM samples based on their spectra fingerprints and validate it.

METHODOLOGY

Radix bupleuri (RB), a typical Chinese medicinal herb for relieving exterior syndrome, and Flos lonicerae (FL), Fructus forsythiae (FF), and Radix isatidis (RI) that are widely applied Chinese herbs for heat clearing and detoxifying, were selected as herbal sources. The aqueous extracts, volatile oils and mixtures of the extracts and oils of the four herbs, plus Ibuprofen suspension (IS), Shuanghuanglian oral liquid (SHL), mixture of SHL and the volatile oils of FL and FF, were used for subject samples to do antipyretic experiments on rats. Ultraviolet spectra were used as the spectra fingerprints to represent chemical characteristics of the samples. Principal component analysis (PCA) and canonical correlation analysis (CCA) were adopted as evaluation tools to establish the correlation between pharmacological and spectra data, from which a spectral index for evaluating antipyretic effects of CHM samples was constructed. Furthermore, four compound samples were designed by mixing 50% volatile oils and 50% aqueous extracts of the four herbs with different ratios to validate the strategy.

RESULTS

Efficacy sequence of the 15 calibrating and 4 validating CHM samples, defined by the first canonical correlative variable U(1) of their UV spectra, was consistent with that given by pharmacological experiments.

CONCLUSIONS

The strategy proposed in this study could be applied to evaluate efficacy strength of CHM and helpful for screening candidate herbal drugs from different herbs or prepared by different technologies.

Pattern recognition of Chinese flue-cured tobaccos by an improved and simplified K-nearest neighbors classification algorithm on near infrared spectra

In tobacco industry of China, tobacco leaves are classified and managed in terms of their cultivation areas and plant parts of tobacco-stalks. However, sometimes intentionally or involuntary mislabeling cultivation areas, blending tobacco plant parts would occur into tobacco market. The error will affect the style and quality of cigarettes. In the present work, more than 1000 Chinese flue-cured tobacco leaf samples, which have 12 genotypes and cultivated from 5 to 10 regions of China in 2003 and 2004, have been discriminated by means of an improved and simplified KNN classification algorithm (IS-KNN) based on near infrared (NIR) spectra. An original method of optimizing number of significant principal components (PCs) based on analysis of error and cross-validation was advanced. Compared with conventional pattern recognition methods KNN, NN, LDA and PLS-DA, IS-KNN exhibits good adaptability in discrimination of complicated Chinese flue-cured tobaccos. The practice in this work shows that optimized number of PCs and performance of classification models are closely relative to complicated extent of samples but not to number of categories or samples. The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method for the authentication and identification of tobacco leaves or other kinds of powder samples.

Quantitative determination of soybean meal content in compound feeds: comparison of near-infrared spectroscopy and real-time PCR

Standard methods for determining the raw material content of compound feed are little exploited, except for the identification of meat and bone meal in feeds. In this work, near-infrared (NIR) spectroscopy and real-time polymerase chain reaction (PCR) were applied in order to establish new and fast methods for quantification of soybean meal content in compound feeds. The best prediction quality was achieved by using a model based on NIR spectroscopy (R2 = 0.9857, standard error of cross-validation 1.1065). Furthermore, a sensitive qualitative detection method by using the real-time PCR was developed (R2 = 0.976, slope -3.7599). Finally, the differences between the real-time PCR result and the NIR spectroscopy result for a given sample were also treated, and we found that the NIR spectroscopy method provided quite accurate results which approach closely those of the real-time PCR method.

Analysis of berberine and total alkaloid content in cortex phellodendri by near infrared spectroscopy (NIRS) compared with high-performance liquid chromatography coupled with ultra-visible spectrometric detection

This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of cortex phellodendri (CP), cortex phellodendri chinensis (PCS) and cortex phellodendri amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all cortex phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R=0.996 for the berberine and R=0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.

Application of near-infrared spectroscopy in quality control and determination of adulteration of African essential oils

An evaluation has been made of the potential of near-infrared (NIR) technologies in the assessment of essential oil components and in the identification of individual essential oils. The results showed that cross-validation models are able to predict accurately almost all of the components of essential oils. In different cinnamon (Cinnamomum zeylanicum) and clove (Syzygium aromaticum) essential oils, which showed a similar composition, 23 components (representing 97.8-99.9% of the oil) were accurately predicted, as well as 20 components (93.0-99.1%) in Cinnamomum camphora (ravintsara), 32 components (92.3-98.1%) in Ravensara aromatica (ravensara), and 26 components (96.6-98.4%) in Lippia multiflora. For almost all of the components, the modelled and reference values obtained by GC-FID were highly correlated (r2 > or = 0.985) and exhibited a low variance (less than 5%). The model was also able to discriminate between the ravintsara and ravensara essential oils. It was shown that two commercial oils labelled as R. aromatica were actually ravintsara (C. camphora), revealing the misidentification of these essential oils in the marketplace. The study demonstrates the application of NIR technology as a quality control tool for the rapid identification of individual essential oils, for product authentication, and for the detection of adulteration.

Continuous Wavelet Transform Applied to Removing the Fluctuating Background in Near-Infrared Spectra

A novel method based on continuous wavelet transform (CWT) was proposed as a preprocessing tool for the near-infrared (NIR) spectra. Due to the property of the vanishing moments of the wavelet, the fluctuating background of the NIR spectra can be successfully removed through convolution of the spectra with an appropriate wavelet function. The vanishing moments of a wavelet and the scale parameter are two key factors that govern the result of the background elimination. The result of its application to both the simulated spectra and the NIR spectra of tobacco samples demonstrates that CWT is a competitive tool for removing fluctuating background in spectra.

Application of near-infrared spectroscopy to the determination of the sites of manufacture of proprietary products

Reflectance near-infrared (NIR) spectroscopy has been investigated as a method to distinguish between the sites of manufacture of a number of proprietary tablets. As test samples, parallel imports which are pharmaceutically equivalent products manufactured at different sites have been used. Three products: Aremis/Besitran, Renitec and Voltarol Retard originating from two or more sites and Adalat from a single site were examined. The principal component analysis (PCA) score plots showed that spectra of tablets originating from different sites of manufacture often gave rise to statistically different populations. PCA loadings indicated that the differences were related to moisture content and excipients. Spectra were used to construct a library for the classification of tablets to predict the site of manufacture based on the method of residual variance of the principal components. Where a large data set was available (Aremis/Besitran tablets) prediction rates for the successful identification of the two sites of manufacture, Madrid and Barcelona, were 95.7 and 98.1%, respectively for the validation set with all errors encountered of Type I.

Development and validation of a near-infrared method for the quantitation of caffeine in intact single tablets

A near-infrared spectroscopic method was developed and validated for determining the caffeine concentration of single and intact tablets in a Finnish pharmaceutical product containing 58.82% (m/m) caffeine.The spectral region of interest contained a total of 474 data points. The second derivative of Savitsky-Golay, a standard normal variate, and mean centering were used as spectral preprocessing options. The feasibility study showed nonuniformity of caffeine repartition within each tablet. Thus, spectra were recorded from both faces of the tablets, and the analysis result for a single tablet was reported as the average of both face determinations. Precision of the method was validated because the relative standard deviations from repeatability and intermediate precision tests were below 0.75% (m/m). Accuracy validation proved that the NIR results were not significantly different (P = 0.09, n = 12) from the results obtained with the reference HPLC method. The limit of quantification for caffeine was 13.7% (m/m) in the tablets. The method was found to be unaffected by NIR source replacement, but the repeatability of the results was affected if the sample holder was not placed in the correct position in the light beam. Routine NIR analysis of caffeine in tablet form was found to be more flexible and much faster than that performed with the HPLC method.