Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data

Recent Advances and Applications of Rapid Microbial Assessment from a Food Safety Perspective

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to "translate" measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses.

Quality assessment of fried licorice based on fingerprints and chemometrics

Fried licorice is obtained by frying licorice without using any auxiliary materials, and it is widely used both as food and medicine in China. To explore the influence of licorice origin on the quality of fried licorice, a method based on fingerprinting and chemometrics was developed. Twenty batches of licorice were selected from four locations. The reference chromatograms of each location were established via similarity analysis. Chemometric methods, such as cluster, principal component, and orthogonal partial least squares discriminant analyses were used to evaluate the changes in the composition of fried licorice, predict its origin, and reflect its quality. Mass spectrometry was used to identify the chemical components. Finally, an origin prediction function was established via discriminant analysis to trace the origin of licorice. The model was demonstrated to be stable, reliable, and accurate in predicting licorice origin and to provide a reference for origin traceability.

Comprehensive Evaluation of Amino Acids and Polyphenols in 69 Varieties of Green Cabbage (Brassica oleracea L. var. capitata L.) Based on Multivariate Statistical Analysis

The biological activities of the primary metabolites and secondary metabolites of 69 green cabbage varieties were tested. The LC-MS detection method was used to determine the content of 19 free amino acids (lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine, valine, arginine, asparagine, glycine, proline, tyrosine, glutamine, alanine, aspartic acid, serine, and glutamate). The content of 10 polyphenols (chlorogenic acid, gallic acid, 4-coumaric acid, ferulic acid, gentisic acid, cymarin, erucic acid, benzoic acid, rutin, and kaempferol) was determined by the HPLC detection method. Considering the complexity of the data obtained, variance analysis, diversity analysis, correlation analysis, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were used to process and correlate amino acid or polyphenol data, respectively. The results showed that there were significant differences between the different amino acids and polyphenols of the 69 cabbage varieties. The most abundant amino acids and polyphenols were Glu and rutin, respectively. Both amino acids and polyphenols had a high genetic diversity, and multiple groups of significant or extremely significant correlations. The 69 cabbage varieties were divided into two groups, according to 19 amino acid indexes, by PCA. Among them, seven varieties with high amino acid content all fell into the fourth quadrant. The HCA of amino acids also supports this view. Based on 10 polyphenols, the 69 cabbage varieties were divided into two groups by HCA. Based on 29 indexes of amino acids and polyphenols, 69 cabbage varieties were evaluated and ranked by PCA. Therefore, in this study, cabbage varieties were classified in accordance with the level of amino acids and polyphenols, which provided a theoretical basis for the genetic improvement of nutritional quality in cabbage.

Assessing the Fatty Acid, Carotenoid, and Tocopherol Compositions of Seeds from Apple Cultivars (Malus domestica Borkh.) Grown in Norway

Apple production generates large amounts of apple pomace including seeds, leading to high transportation costs, public health hazards and undesirable odor. A new reuse strategy of this kind of waste could solve environmental issues and/or create unconventional sources of health beneficial products. In total, seeds from 75 apple cultivars grown in Norway (both domestic and international) have been analyzed for the first time for oil content and fatty acid profile together with tocopherols and carotenoids quantification in defatted seeds. Seeds from cultivar Håkonseple had the highest oil content (22.10%), with linoleic, oleic acid, and palmitic acid as the most abundant fatty acids. The levels of β-carotene and lycopene carotenoids and α-tocopherol were the highest in defatted seeds of the cultivar Sureple Grøn. Principal component analysis separated cultivars according to the total oil content. The Norwegian apple cultivars Håkonseple, Kviteple, Tolleivseple, Vinterrosenstrips, and Tokheimseple are recommended for obtaining vegetable oil due to their high oil contents, while cultivar Sureple Grøn can be separated due to its high levels of β-carotene, lycopene and total tocopherols.

ATR-FTIR Spectroscopy, HPLC Chromatography, and Multivariate Analysis for Controlling Bee Pollen Quality in Some Algerian Regions

Bee pollen collected by honeybees (Apis mellifera) is one of the bee products, and it is as valuable as honey, propolis, royal jelly, or beebread. Its quality varies according to its geographic location or plant sources. This study aimed to apply rapid, simple, and accurate analytical methods such as attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-performance liquid chromatography (HPLC) along with chemometrics analysis to construct a model aimed at discriminating between different pollen samples. In total, 33 samples were collected and analyzed using principal component analysis (PCA), hierarchical clustering analysis (HCA), and partial least squares regression (PLS) to assess the differences and similarities between them. The PCA score plot based on both HPLC and ATR-FTIR revealed the same discriminatory pattern, and the samples were divided into four major classes depending on their total content of polyphenols. The results revealed that spectral data obtained from ATR-FTIR acquired in the region (4000-500 cm^-1) were further subjected to a standard normal variable (SNV) method that removes scattering effects from spectra. However, PCA, HCA, and PLS showed that the best PLS model was obtained with a regression coefficient (R ²) of 0.9001, root-mean-square estimation error (RMSEE) of 0.0304, and root-mean-squared error cross-validation (RMSEcv) of 0.036. Discrimination between the three species has also been possible by combining the pre-processed ATR-FTIR spectra with PCA and PLS. Additionally, the HPLC chromatograms after pre-treatment (SNV) were subjected to unsupervised analysis (PCA-HCA) and supervised analysis (PLS). The PLS model confers good results by factors (R ² = 0.98, RMSEE = 8.22, and RMSEcv = 27.86). Prospects for devising bee pollen quality assessment methods include utilizing ATR-FTIR and HPLC in combination with multivariate methods for rapid authentication of the geographic location or plant sources of bee pollen.

Effects of tissue pre-degassing followed by ultrasound-assisted freezing on freezing efficiency and quality attributes of radishes

The rapid freezing technique for porous foods using tissue pre-degassing followed by ultrasound-assisted freezing (UF) was developed, and its effects on quality attributes of radishes including tissue air volume, hardness, total calcium contents, bonded calcium contents, retention rates of bonded calcium and microstructures were investigated. To evaluate the freezing efficiency, parameters including total freezing time, phase transition time, and the increases of freezing rate and phase transition rate were determined. Besides, multivariate statistical analyses including principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed to visualize and further analyze the quality differences of radishes under different treatments. Results suggested that decreasing tissue air volumes can significantly shorten the phase transition time of UF. Samples treated by pre-degassing for 5 min at -0.09 MPa followed by UF (D_-0.09MPa^5min-UF) showed the freezing rate and phase transition rate increased by 28.8% and 29.8%, respectively, as compared with the same pre-degassed samples frozen by immersion freezing (D_-0.09MPa^5min-IF). Retention rates of bonded calcium positively correlated with the sample hardness, announcing the importance of bonded calcium maintenance during radish freezing. Both PCA and HCA indicated that D_-0.09MPa^5min-UF endowed radishes with quality attributes more similar to the fresh ones, which was further verified by microstructure analysis, showing remarkably alleviated plasma membrane puncture, cell separation and deformation in D_-0.09MPa^5min-UF samples. The current study proved that the technique of tissue pre-degassing followed by UF could effectively improve the freezing efficiency and quality attributes of frozen radishes, and thus have great potentials in rapid freezing of porous foods.

Finding specific peaks (markers) using fuzzy divisive hierarchical associative-clustering based on the chromatographic profiles of medicinal plant extracts obtained at various detection wavelengths

Advanced chemometric methods, such as fuzzy c-means (FCM), a fuzzy divisive hierarchical clustering algorithm (FDHC), and fuzzy divisive hierarchical associative-clustering (FDHAC), which offer the excellent possibility to associate each fuzzy partition of samples with a fuzzy set of characteristics (features), have been successfully applied in this study. FDHAC, a method that utilizes specific regions of chromatographic fingerprints or specific peaks as a fuzzy set of characteristics, was effectively applied to the characterization and classification of medicinal plant extracts according to their antioxidant capacities, using their chromatographic profiles monitored at 242, 260, 280, 320, 340, and 380 nm via HPLC with a multistep isocratic and gradient elution system and diode array detection (HPLC-DAD). What is quite new is the partitioning of the chromatographic retention time ranges and peaks (markers) and their association with different plant extract samples with high, moderate or low antioxidant capacity. Furthermore, the degrees of membership of fingerprints (fuzzy markers) are highly relevant with respect to the (dis)similarity of samples because they indicate both the positions and degrees of association of chromatographic peaks from different classes or individual samples. The obtained results clearly demonstrate the efficiency and information power of these advanced fuzzy methods for medicinal plant characterization and authentication, and this study generates the premise for a new chemometrics approach with high-impact for use in analytical chemistry and other fields.

Use of visible spectrophotometric fingerprint and chemometric approaches for the differentiation of Mimosa scabrella Bentham honeydew honey

Honeydew honeys, including bracatinga (Mimosa scabrella Bentham) honeydew honey, are highly appreciated due to its nutritional and sensory properties. Therefore, fast and inexpensive methods must be developed to differentiate this distinct class of honey. Although methods using the visible spectrophotometric fingerprint (VSF) have never been used to differentiate bracatinga honeydew honey and blossom honey, this technique appears to be a viable alternative, successfully used in the differentiation and fraud detection of various foods, including honeys from other botanical sources. In this sense, the present study aimed to verify the existence of a specific VSF for bracatinga honeydew honey and blossom honey and differentiate both type of honeys using the VSF associated with chemometric analysis. The VSF of 30 bracatinga honeydew honeys harvested in three different years (2014, 2016, and 2018) and 21 blossom honeys (harvested in 2016) were evaluated. The existence of a different VSF for bracatinga honeydew honeys and blossom honeys allowed the satisfactory differentiation of both types of honeys. Additionally, bracatinga honeydew honey presented a unique VSF, independent of the year of harvest, which can be exploited as a fingerprint of this type of honey, contributing to its authenticity.

Shelf-life and quality attributes in fresh-cut pear cv. Shahmive treated with different kinds of antioxidants

Synthetic antioxidants can reduce postharvest losses, but consumers are concerned about chemical residues in the product. There is a growing interest in using natural compounds for the preservation of foods. In this study, the efficiency of juices or extracts obtained from three fruit species with high antioxidant activity as browning inhibitors was measured and then compared with that obtained from pomegranate by-product (PBP). The aim was to offer the most significant contributions concerning fresh-cut fruit preservation, using 'Shahmive' pear as the fruit model. Slices of pear were dipped in pomegranate juice (PJ) or extract (PE), kiwifruit juice (KJ) or extract (KE), grape juice (GJ) or extract (GE), PBP and chitosan before being stored at 4 °C. The total phenolic content of solutions ranged from 11 to 127.5 mg gallic acid/100 mL. Extracts of pomegranate peel and grape had the uppermost and the lowermost antioxidant activity (%DPPH), respectively. In comparison with other treatments including the control one, the minimum peroxidase (POD) activity, the maximum ascorbic acid content and the retention of firmness were seen in the fruit which was treated with kiwifruit extract. PJ + GJ treatment decreased POD and polyphenol oxidase activity and improved L* and a* values in the slices. The use of fruit juice or extracts had no adverse effect on the sensory quality of slices, with the exception of samples subjected to PJ or GJ + KJ treatments. Improving antioxidant capacity of fresh cut pear treated with KE and PJ + GJ would have a big advantage of preventing enzymatic browning.

The impact of the order of derivative spectra on the performance of pattern recognition methods. Classification of medicinal plants according to the phylum

Data pre-processing is an important strategy in chemometrics and related fields because in many cases the transformation of data has a great effect on the performance of the method (model). However, a careful examination of the literature clearly points out that only very few systematic studies are dedicated to the effect of the derivative spectra on the performance of the pattern recognition methods. This comprehensive study compares the impact of the order of derivative spectra and other data pre-processing procedures (normalization and standardization) on the performance of cluster analysis, principal component analysis and discriminant analysis applied for characterization and classification of medicinal plants according to their phylum using UV spectra. The efficiency of the pre-processing methods was estimated by comparing the accuracy of classification and prediction measured by internal cross-validation. Derivatization method (1st order) resulted in the best classification (100%) of medicinal plants according to their phylum (Pteridophyte, Magnoliophyte and Spermatophyte) as compared to other pre-processing methods (normalized spectra-71.4%, standardized spectra-76.2% and original spectra-78.6%).

Chemometric Assessment of Chromatographic Methods for Herbal Medicines Authentication and Fingerprinting

Nowadays, increasingly more individuals turn to supplementation of the diet with herbal medicines and many such products are marketed lately. Thus the problem that this article focuses on is that these products are not subjected to rigorous quality control like synthetic drugs are, which rises a constant debate whether the supplements actually contain the herb or mixture of herbs that the manufacturer claims they do. As a solution, micellar electrokinetic chromatography and high performance liquid chromatography were investigated in order to fingerprint and authenticate herbal medicines. For this purpose, minimal sample pre-treatment was applied to several fruit based herbal medicines, which were compared with the ethanolic extract of the respective fruit. The holistic evaluation of the electropherograms and chromatograms was made by using appropriate chemometric tools, such as principal component analysis (PCA), cluster analysis and a combination of PCA and linear discriminant analysis (PCA-LDA). The results suggest that the developed method was able to successfully discriminate between different herbal medicines, based on their raw material content. Moreover, this simple and efficient methodology might also be used for routine screening and authenticity control of different products and could be implemented in any quality control laboratory.

Characterization of Clinically Relevant Fungi via SERS Fingerprinting Assisted by Novel Chemometric Models

Nonculture-based tests are gaining popularity and upsurge in the diagnosis of invasive fungal infections (IFI) fostered by their main asset, the reduced analysis time, which enables a more rapid diagnosis. In this project, three different clinical isolates of relevant filamentous fungal species were discriminated by using a rapid (less than 5 min) and sensitive surface-enhanced Raman scattering (SERS)-based detection method, assisted by chemometrics. The holistic evaluation of the SERS spectra was performed by employing appropriate chemometric tools-classical and fuzzy principal component analysis (FPCA) in combination with linear discriminant analysis (LDA) applied to the first relevant principal components. The efficiency of the proposed robust algorithm is illustrated on the data set including three fungal isolates (Aspergillus fumigatus sensu stricto, cryptic A. fumigatus complex species, and Rhizomucor pusillus) that were isolated from patient materials. The accurate and reliable discrimination between species of common fungal pathogen strains suggest that the developed method has the potential as an alternative, spectroscopic-based routine analysis tool in IFI diagnosis.

Application of chemometrics in quality control of Turmeric (Curcuma longa) based on Ultra-violet, Fourier transform-infrared and 1H NMR spectroscopy

Turmeric (Curcuma longa L.) belongs to the family Zingiberaceae that is widely used as a spice in food preparations in addition to its biological activities. UV, FT-IR, ¹H NMR in addition to HPLC were applied to construct a metabolic fingerprint for Turmeric in an attempt to assess its quality. 30 samples were analyzed, and then principal component analysis (PCA) and hierarchical clustering analysis (HCA) were utilized to assess the differences and similarities between collected samples. PCA score plot based on both HPLC and UV spectroscopy showed the same discriminatory pattern, where the samples were segregated into four main groups depending on their total curcuminoids content. The results revealed that UV could be utilized as a simple and rapid alternative for HPLC. However, FT-IR failed to discriminate between the same species. By applying ¹H NMR, the metabolic variability between samples was more evident in the essential oils/fatty acid region.

A Comprehensive and Comparative Study of Wolfiporia extensa Cultivation Regions by Fourier Transform Infrared Spectroscopy and Ultra-Fast Liquid Chromatography

Nowadays, Wolfiporia extensa as a popular raw material in food and medicine industry has received increasing interests. Due to supply shortage, this species of edible and medicinal mushroom has been cultivated in some provinces of China. In the present study, cultivated W. extensa collected from six regions in Yunnan Province of China were analyzed by an integrated method based on Fourier transform infrared (FT-IR) spectroscopy and ultra-fast liquid chromatography (UFLC) coupled with multivariate analysis including partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) in order to investigate the differences and similarities in different origins and parts. In the tested mushroom samples, characteristic FT-IR spectra were obtained for acquiring comprehensive fuzz chemical information and pachymic acid was determinated as a biomarker in the meantime. From the results, the comparison of samples was achieved successfully according to their geographical regions and different parts. All the samples displayed regional dependence and the inner parts showed better quality consistency. In addition, the chemical constituents of cultivated W. extensa could be also affected by the cultivation methods. Meanwhile, there was an interesting finding that the soil properties of cultivation regions may have a relationship with the chemical constituents of the epidermis of soil-cultured W. extensa, rather than the inner parts. Collectively, it demonstrated that the present study could provide comprehensive chemical evidence for the critical complement of quality evaluation on the cultivated W. extensa. Moreover, it may be available for the further researches of complicated mushrooms in practice.

Induction of stress volatiles and changes in essential oil content and composition upon microwave exposure in the aromatic plant Ocimum basilicum

Exposure to sustained low intensity microwaves can constitute a stress for the plants, but its effects on plant secondary chemistry are poorly known. We studied the influence of GSM and WLAN-frequency microwaves on emissions of volatile organic compounds and content of essential oil in the aromatic plant Ocimum basilicum L. hypothesizing that microwave exposure leads to enhanced emissions of stress volatiles and overall greater investment in secondary compounds. Compared to the control plants, microwave irradiation led to decreased emissions of β-pinene, α-phellandrene, bornyl acetate, β-myrcene, α-caryophyllene and benzaldehyde, but increased emissions of eucalyptol, estragole, caryophyllene oxide, and α-bergamotene. The highest increase in emission, 21 times greater compared to control, was observed for caryophyllene oxide. The irradiation resulted in increases in the essential oil content, except for the content of phytol which decreased by 41% in the case of GSM-frequency, and 82% in the case of WLAN-frequency microwave irradiation. The strongest increase in response to WLAN irradiation, >17 times greater, was observed for hexadecane and octane contents. Comparisons of volatile compositions by multivariate analyses demonstrated a clear separation of different irradiance treatments, and according to the changes in the volatile emissions, the WLAN-frequency irradiation represented a more severe stress than the GSM-frequency irradiation. Overall, these results demonstrating important modifications in the emission rates, essential oil content and composition indicate that microwave irradiation influences the quality of herbage of this economically important spice plant.

HPLC Fingerprint Combined with Quantitation of Phenolic Compounds and Chemometrics as an Efficient Strategy for Quality Consistency Evaluation of Sambucus nigra Berries

Sambucus nigra L. berries have been traditionally used as culinary and medicinal ingredients. To ensure the highest quality of elderberry plant products for consumers, the objective of this study was to develop a HPLC fingerprint procedure for quality consistency evaluation of S. nigra berries obtained from various herbal manufacturers in Poland. The HPLC profiles of thirteen batches of elderberries showed more than sixty peaks in each chromatogram, including fourteen well-resolved common peaks. Four of these were assigned to caffeic acid, syringic acid, myricetin and quercetin. Based on the chromatographic profiles of all the samples, the reference HPLC fingerprint and similarity values were calculated by Matlab 9.1 software. Quantitation of phenolic compounds (flavonols and phenolic acids) revealed that the S. nigra samples with the highest quantity differ to a small extent with regard to the mean content of phenolic compounds. On the other hand, in batches of elderberries with lower similarity values, higher differences in the mean phenolic compound content were observed. The results of hierarchical cluster and principal component analyses showed that samples classified into one group are associated with a similar chemical composition, reflected in fourteen common HPLC peaks and similarity values. Chromatographic fingerprint combined with quantitation of plant bioactive compounds and unsupervised data analysis techniques can be a useful and efficient strategy for monitoring the quality consistency of elderberry fruits.

Ultraviolet spectroscopy combined with ultra-fast liquid chromatography and multivariate statistical analysis for quality assessment of wild Wolfiporia extensa from different geographical origins

A quality assessment system comprised of a tandem technique of ultraviolet (UV) spectroscopy and ultra-fast liquid chromatography (UFLC) aided by multivariate analysis was presented for the determination of geographic origin of Wolfiporia extensa collected from five regions in Yunnan Province of China. Characteristic UV spectroscopic fingerprints of samples were determined based on its methanol extract. UFLC was applied for the determination of pachymic acid (a biomarker) presented in individual test samples. The spectrum data matrix and the content of pachymic acid were integrated and analyzed by partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA). The results showed that chemical properties of samples were clearly dominated by the epidermis and inner part as well as geographical origins. The relationships among samples obtained from these five regions have been also presented. Moreover, an interesting finding implied that geographical origins had much greater influence on the chemical properties of epidermis compared with that of the inner part. This study demonstrated that a rapid tool for accurate discrimination of W. extensa by UV spectroscopy and UFLC could be available for quality control of complicated medicinal mushrooms.

In vivo/ex vivo targeting of Langerhans cells after topical application of the immune response modifier TMX-202: confocal Raman microscopy and histology analysis

The increased ability of TMX-202 (derivative of imiquimod) to penetrate the intact stratum corneum (SC) and the follicular orifices of porcine ear skin was shown ex vivo using confocal Raman microscopy and laser scanning microscopy. Moreover, to assess whether TMX-202 is able to reach the immune cells, Langerhans cells extracted from pretreated human skin were investigated ex vivo using confocal Raman microscopy combined with multivariate statistical methods. Tracking the Raman peak of dimethyl sulfoxide centered at 690  cm(−1), the absorption of TMX-202 containing formulation by Langerhans cells was shown. To answer the question whether the TMX-202 active ingredient is able to reach Langerhans cells, the attraction of immune cells to TMX-202 containing formulation treated skin was measured in the in vivo rodent model Mastomys coucha. The results show that TMX-202 active ingredient is able to reach Langerhans cells after penetrating through the intact skin and subsequently attract immune cells. Both the intercellular/transcellular as well as the follicular pathways allow the penetration through the intact barrier of the SC.

Confocal Raman microscopy and multivariate statistical analysis for determination of different penetration abilities of caffeine and propylene glycol applied simultaneously in a mixture on porcine skin ex vivo

Propylene glycol is one of the known substances added in cosmetic formulations as a penetration enhancer. Recently, nanocrystals have been employed also to increase the skin penetration of active components. Caffeine is a component with many applications and its penetration into the epidermis is controversially discussed in the literature. In the present study, the penetration ability of two components - caffeine nanocrystals and propylene glycol, applied topically on porcine ear skin in the form of a gel, was investigated ex vivo using two confocal Raman microscopes operated at different excitation wavelengths (785nm and 633nm). Several depth profiles were acquired in the fingerprint region and different spectral ranges, i.e., 526-600cm(-1) and 810-880cm(-1) were chosen for independent analysis of caffeine and propylene glycol penetration into the skin, respectively. Multivariate statistical methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) combined with Student's t-test were employed to calculate the maximum penetration depths of each substance (caffeine and propylene glycol). The results show that propylene glycol penetrates significantly deeper than caffeine (20.7-22.0μm versus 12.3-13.0μm) without any penetration enhancement effect on caffeine. The results confirm that different substances, even if applied onto the skin as a mixture, can penetrate differently. The penetration depths of caffeine and propylene glycol obtained using two different confocal Raman microscopes are comparable showing that both types of microscopes are well suited for such investigations and that multivariate statistical PCA-LDA methods combined with Student's t-test are very useful for analyzing the penetration of different substances into the skin.

Comparative analysis of volatiles difference of Yunnan sun-dried Pu-erh green tea from different tea mountains: Jingmai and Wuliang mountain by chemical fingerprint similarity combined with principal component analysis and cluster analysis

BACKGROUND

Modern instrumental analysis technology can provide various chemical data and information on tea samples. Unfortunately, it remains difficult to extract the useful information. We describe the use of chemical fingerprint similarities, combined with principal component and cluster analyses, to distinguish and recognize Pu-erh green teas, which from two tea mountains, Wuliang and Jingmai, in the Pu-erh district of Yunnan province. The volatile components of all 20 Pu-erh green teas (10 Wuliang and 10 Jingmai teas) were extracted and identified by headspace solid-phase micro extraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS).

RESULTS

Sixty-three volatiles (including alcohols, hydrocarbons, ketones, and aldehydes) were identified in the 20 Pu-erh green teas, and differences in compound compositions between them were also observed. Through fingerprint similarity, combined with principal component and cluster analyses, the 20 Pu-erh green teas were differentiated successfully based on their volatile characteristics.

CONCLUSIONS

This study demonstrates that the GC-MS combined with chemical fingerprint and unsupervised pattern recognition method is suitable for the investigation of the volatile profiling and evaluating the quality and authenticity of teas related to the different origins.Graphical abstractDifferentiate Pu-erh green teas from different tea mountains by using chemical fingerprint similarity and multivariate statistical methods.

Extraction of heavy metals characteristics of the 2011 Tohoku tsunami deposits using multiple classification analysis

Tsunami deposits accumulated on the Tohoku coastal area in Japan due to the impact of the Tohoku-oki earthquake. In the study reported in this paper, we applied principal component analysis (PCA) and cluster analysis (CA) to determine the concentrations of heavy metals in tsunami deposits that had been diluted with water or digested using 1 M HCl. The results suggest that the environmental risk is relatively low, evidenced by the following geometric mean concentrations: Pb, 16 mg kg(-1) and 0.003 ml L(-1); As, 1.8 mg kg(-1) and 0.004 ml L(-1); and Cd, 0.17 mg kg(-1) and 0.0001 ml L(-1). CA was performed after outliers were excluded using PCA. The analysis grouped the concentrations of heavy metals for leaching in water and acid. For the acid case, the first cluster contained Ni, Fe, Cd, Cu, Al, Cr, Zn, and Mn; while the second contained Pb, Sb, As, and Mo. For water, the first cluster contained Ni, Fe, Al, and Cr; and the second cluster contained Mo, Sb, As, Cu, Zn, Pb, and Mn. Statistical analysis revealed that the typical toxic elements, As, Pb, and Cd have steady correlations for acid leaching but are relatively sparse for water leaching. Pb and As from the tsunami deposits seemed to reveal a kind of redox elution mechanism using 1 M HCl.

Nuclear Magnetic Resonance (NMR) Spectroscopy For Metabolic Profiling of Medicinal Plants and Their Products

NMR spectroscopy has multidisciplinary applications, including excellent impact in metabolomics. The analytical capacity of NMR spectroscopy provides information for easy qualitative and quantitative assessment of both endogenous and exogenous metabolites present in biological samples. The complexity of a particular metabolite and its contribution in a biological system are critically important for understanding the functional state that governs the organism's phenotypes. This review covers historical aspects of developments in the NMR field, its applications in chemical profiling, metabolomics, and quality control of plants and their derived medicines, foods, and other products. The bottlenecks of NMR in metabolic profiling are also discussed, keeping in view the future scope and further technological interventions.

Variations in chemical fingerprints and major flavonoid contents from the leaves of thirty-one accessions of Hibiscus sabdariffa L

The leaves of Hibiscus sabdariffa L. have been used as traditional folk medicines for treating high blood pressure and fever. There are many accessions of H. sabdariffa L. throughout the world. To assess the chemical variations of 31 different accessions of H. sabdariffa L., fingerprinting analysis and quantitation of major flavonoids were performed by high‐performance liquid chromatography (HPLC). The HPLC method was validated for linearity, sensitivity, precision, repeatability and accuracy. A quadrupole‐time‐of‐flight mass spectrometry (Q‐TOF‐MS) was applied for the characterization of major compounds. A total of 9 compounds were identified, including 6 flavonoids and 3 phenolic acids. In the fingerprint analysis, similarity analysis (SA) and principal component analysis (PCA) were used to differentiate the 31 accessions of H. sabdariffa L. Based on the results of PCA and SA, the samples No. 15 and 19 appeared much different from the main group. The total content of five flavonoids varied greatly among different accessions, ranging from 3.35 to 23.30 mg/g. Rutin was found to be the dominant compound and the content of rutin could contribute to chemical variations among different accessions. This study was helpful to understand the chemical variations between different accessions of H. sabdariffa L., which could be used for quality control. © 2015 The Authors Biomedical Chromatography Published by John Wiley & Sons Ltd.

Rapid Discrimination of Apple Varieties via Near-Infrared Reflectance Spectroscopy and Fast Allied Fuzzy C-Means Clustering

Discrimination of apple varieties plays an important role in apple post-harvest commercial processing. A fast allied fuzzy c-means (FAFCM) clustering algorithm was proposed to classify the apple varieties using near-infrared reflectance (NIR) spectroscopy technology and orthogonal linear discriminant analysis (OLDA) which was used as feature extraction and dimensionality reduction method. Our classification method: the high-dimensional NIR data were reduced to three-dimensional data by OLDA at first, and the FAFCM clustering algorithm was implemented to classify the reduced data. Furthermore, the principal component analysis (PCA) and linear discriminant analysis (LDA) combined with k-nearest neighbor classifier (KNNC), fuzzy c-means (FCM) clustering and unsupervised possibilistic clustering algorithm (UPCA), formed the other four classification methods to classify apple samples in comparison with our proposed method. The experimental results showed that FAFCM achieved the best performance of classification.

Application of gas chromatography-mass spectrometry and chemometrics methods for assessing volatile profiles of Pu-erh tea with different processing methods and ageing years

A method was developed based on head-space solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) combined with multivariate statistical methods to assess volatile profiles in different types of Pu-erh teas.

Characteristic Fingerprint Based on Low Polar Constituents for Discrimination of Wolfiporia extensa according to Geographical Origin Using UV Spectroscopy and Chemometrics Methods

The fungus species Wolfiporia extensa has a long history of medicinal usage and has also been commercially used to formulate nutraceuticals and functional foods in certain Asian countries. In the present study, a practical and promising method has been developed to discriminate the dried sclerotium of W. extensa collected from different geographical sites based on UV spectroscopy together with chemometrics methods. Characteristic fingerprint of low polar constituents of sample extracts that originated from chloroform has been obtained in the interval 250-400 nm. Chemometric pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were applied to enhance the authenticity of discrimination of the specimens. The results showed that W. extensa samples were well classified according to their geographical origins. The proposed method can fully utilize diversified fingerprint characteristics of sclerotium of W. extensa and requires low-cost equipment and short-time analysis in comparison with other techniques. Meanwhile, this simple and efficient method may serve as a basis for the authentication of other medicinal fungi.

Adulteration and cultivation region identification of American ginseng using HPLC coupled with multivariate analysis

American ginseng (Panax quinquefolius) is originally grown in North America. Due to price difference and supply shortage, American ginseng recently has been cultivated in northern China. Further, in the market, some Asian ginsengs are labeled as American ginseng. In this study, forty-three American ginseng samples cultivated in the USA, Canada or China were collected and 14 ginseng saponins were determined using HPLC. HPLC coupled with hierarchical cluster analysis and principal component analysis was developed to identify the species. Subsequently, an HPLC-linear discriminant analysis was established to discriminate cultivation regions of American ginseng. This method was successfully applied to identify the sources of 6 commercial American ginseng samples. Two of them were identified as Asian ginseng, while 4 others were identified as American ginseng, which were cultivated in the USA (3) and China (1). Our newly developed method can be used to identify American ginseng with different cultivation regions.

Bioactive compounds and the antioxidant capacity in new kiwi fruit cultivars

The aim of this investigation was to find the best among seven different kiwi fruit cultivars ('Hayward', 'Daheung', 'Haenam', 'Bidan', 'Hort16A', 'Hwamei' and 'SKK12') for human consumption and to classify them as groups. Therefore, the contents of bioactive compounds and the level of antioxidant capacities of these cultivars were determined in four different extracts and compared. It was found that the contents of the bioactive compounds and the level of antioxidant capacities in different extracts differ significantly (P<0.05). Bioactive compounds and the antioxidant capacities were significantly higher in 'Bidan' and 'SKK12' cultivars than in other studied samples. The ethanol and water extracts of these cultivars exhibited high binding properties with human serum albumin (HSA) in comparison with catechin. In conclusion, based on fluorescence profiles the seven new kiwi fruit cultivars can be classified for three groups: 'Hayward' (including 'Daheung', 'Haenam', Hwamei' and 'SKK12'), 'Bidan' and 'Hort 16A'. In MS - profiles some differences in the peaks were found between the cultivar groups. All studied fruits could be a valuable addition to known disease preventing diets.