Exploring the distribution of statistical feature parameters for natural sound textures.

Sounds like "running water" and "buzzing bees" are classes of sounds which are a collective result of many similar acoustic events and are known as "sound textures". A recent psychoacoustic study using sound textures has reported that natural sounding textures can be synthesized from white noise by imposing statistical features such as marginals and correlations computed from the outputs of cochlear models responding to the textures. The outputs being the envelopes of bandpass filter responses, the 'cochlear envelope'. This suggests that the perceptual qualities of many natural sounds derive directly from such statistical features, and raises the question of how these statistical features are distributed in the acoustic environment. To address this question, we collected a corpus of 200 sound textures from public online sources and analyzed the distributions of the textures' marginal statistics (mean, variance, skew, and kurtosis), cross-frequency correlations and modulation power statistics. A principal component analysis of these parameters revealed a great deal of redundancy in the texture parameters. For example, just two marginal principal components, which can be thought of as measuring the sparseness or burstiness of a texture, capture as much as 64% of the variance of the 128 dimensional marginal parameter space, while the first two principal components of cochlear correlations capture as much as 88% of the variance in the 496 correlation parameters. Knowledge of the statistical distributions documented here may help guide the choice of acoustic stimuli with high ecological validity in future research.

Revisiting the contribution of ATR-FTIR spectroscopy to characterize plant cell wall polysaccharides.

The contribution of ATR-FTIR spectroscopy to study cell wall polysaccharides (CWPs) was carefully investigated. The region 1800-800 cm-1 was exploited using principal component analysis and hierarchical clustering on a large range of different powders of CWPs based on their precise chemical characterization. Relevant wavenumbers were highlighted for each CWP: 1035 cm-1 was attributed to xylose-containing hemicelluloses, 1065 and 807 cm-1 to mannose-containing hemicelluloses, 988 cm-1 to cellulose, 1740 and 1600 cm-1 to homogalacturonans according to the degree of methylation. Some band positions were affected by macromolecular arrangements (especially hemicellulose-cellulose interactions). However, as arabinan and galactan did not reveal distinctive absorption bands, ATR-FTIR spectroscopy did not allow the discrimination of cell walls differing by the abundance of these polysaccharides, e.g., those extracted from apple and beet. Therefore, the application of ATR-FTIR could remain sometimes limited due to the complexity of overlapping spectra bands and vibrational coupling from the large diversity of CWP chemical bonds.

Comprehensive evaluation on anti-inflammatory and anti-angiogenic activities in vitro of fourteen flavonoids from Daphne Genkwa based on the combination of efficacy coefficient method and principal component analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Genkwa flos, as a traditional herb, is the dried flower buds of Daphne genkwa Sieb.et Zucc. It is used in traditional medicine for the treatment of cough, sore throats, edema. AIM OF THE STUDY: The study aimed to explore a new mathematical method for multivariate evaluation, investigate the anti-inflammatory and anti-angiogenic activities of flavonoids in Daphne Genkwa under ex vivo conditions. MATERIALS AND METHODS: The flavonoids monomers in Daphne Genkwa were separated by preparative liquid chromatography and identified by HPLC-ESI-ITMS. An in vitro inflammatory model of macrophage RAW264.7 induced by LPS and an angiogenesis model of human umbilical vein endothelial cells induced by TNF-α were established. Flavonoids were extracted and prepared for intervention to detect the amount of secretion after drug intervention to reflect the anti-inflammatory and anti-angiogenic activities of each component. In addition, a new mathematical method, which combined principal component analysis and efficacy coefficient method, was adopted in pharmacodynamic evaluation. RESULTS: Fourteen flavonoids monomers were separated by preparative liquid chromatography and identified by HPLC-ESI-ITMS including H1 (hydroxygenkwanin-5-O-ß-D-glucoside), H2 (apigenin-7-O-ß-D-glucoside), H3 (kaempferol-3-O-ß-D-glucoside), H4 (hydroxygenkwanin-5-O-ß-D-primeveroside), H5 (apigenin-5-O-ß-D-primeveroside), H6 (apigenin-7-O-ß-D-glucuronide), H7 (luteolin-5-O-ß-D-glucopyranoside), H8 (genkwain-5-O-ß-D- glucoside), H9 (luteolin), H10 (Daphnodorin G), H11 (tiliroside), H12 (apigenin), H13 (3'- hydroxygenkwain) and H14 (genkwanin). We found that most of flavonoids down-regulated VCAM and MMP-3, while H1, H8, H9, H14 reduced VEGF and ICAM was only decreased by H14. CONCLUSION: Genkwanin may be the most active anti-rheumatoid arthritis flavonoids in Daphne genkwa. Meanwhile, the new mathematical method used in the study provided a new direction for solving the problem of multi-index pharmacodynamic evaluation.

Identification of genetic factors controlling phosphorus utilization efficiency in wheat by genome-wide association study with principal component analysis.

Despite the economic importance of P utilization efficiency, information on genetic factors underlying this trait remains elusive. To address that, we performed a genome-wide association study in a spring wheat diversity panel ranging from landraces to elite varieties. We evaluated the phenotype variation for P utilization efficiency in controlled conditions and genotype variation using wheat 90 K SNP array. Phenotype variables were transformed into a smaller set of uncorrelated principal components that captured the most important variation data. We identified two significant loci associated with both P utilization efficiency and the 1st principal component on chromosomes 3A and 4A: qPE1-3A and qPE2-4A. Annotation of genes at these loci revealed 53 wheat genes, among which 6 were identified in significantly enriched pathways. The expression pattern of these 6 genes indicated that TraesCS4A02G481800, involved in pyruvate metabolism and TCA cycle, had a significantly higher expression in the P efficient variety under limited P conditions. Further characterization of these loci and candidate genes can help stimulate P utilization efficiency in wheat.

Characteristic Volatile Fingerprints and Odor Activity Values in Different Citrus-Tea by HS-GC-IMS and HS-SPME-GC-MS.

Citrus tea is an emerging tea drink produced from tea and the pericarp of citrus, which consumers have increasingly favored due to its potential health effects and unique flavor. This study aimed to simultaneously combine the characteristic volatile fingerprints with the odor activity values (OAVs) of different citrus teas for the first time by headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Results showed that the establishment of a citrus tea flavor fingerprint based on HS-GC-IMS data can provide an effective means for the rapid identification and traceability of different citrus varieties. Moreover, 68 volatile compounds (OAV > 1) were identified by HS-SPME-GC-MS, which reflected the contribution of aroma compounds to the characteristic flavor of samples. Amongst them, the contribution of linalool with sweet flower fragrance was the highest. Odorants such as decanal, ß-lonone, ß-ionone, ß-myrcene and D-limonene also contributed significantly to all samples. According to principal component analysis, the samples from different citrus teas were significantly separated. Visualization analysis based on Pearson correlation coefficients suggested that the correlation between key compounds was clarified. A comprehensive evaluation of the aroma of citrus tea will guide citrus tea flavor quality control and mass production.

Chemical Evaluation of the Effects of Storage Conditions on the Botanical Goldenseal using Marker-based and Metabolomics Approaches.

Hydrastis canadensis, commonly known as goldenseal, is a botanical native to the southeastern United States that has been used for the treatment of infection. The activity of goldenseal is often attributed to the presence of alkaloids (cyclic, nitrogen-containing compounds) present within its roots. Chemical components of botanical supplements like goldenseal may face degradation if not stored properly. The purpose of the research was to analyze the stability of known and unknown metabolites of H. canadensis during exposure to different storage conditions using mass spectrometry. Three abundant metabolites of H. canadensis, berberine, canadine, and hydrastine, were chosen for targeted analysis, and the stability of unknown metabolites was evaluated using untargeted metabolomics. The analysis and evaluation of H. canadensis samples were performed utilizing LC-MS and Principal Component Analysis (PCA). The research project focused on identifying the chemical changes in the metabolite content of H. canadensis under different temperature conditions (40°C ± 5°C, 20°C ± 5°C , and 4°C ± 5°C), different light:dark (hr:hr) cycles (16:8, 12:12, and 0:24), and different sample conditions (powdered roots versus whole roots) over a six month period. The results of this 6-month study revealed that the storage conditions evaluated had no significant effects on the chemical composition of H. canadensis roots. Hence, as long as H. canadensis roots are stored within the storage conditions tested in the study, no significant changes in chemical compositions of metabolites are expected.

The Role of Extracting Solvents in the Recovery of Polyphenols from Green Tea and Its Antiradical Activity Supported by Principal Component Analysis.

Green tea contains a variety of biologically active constituents that are widely used in the pharmaceutical and food industries. Among them, simple catechins constitute a major group of compounds that is primarily responsible for the high biologic activity of green tea extracts. Therefore, the application of optimized extraction conditions may result in obtaining high value extracts. The main purpose of the study was to compare the content of polyphenols, mainly catechins, and the antioxidant activity of green tea extracts obtained by three different extraction methods: simple maceration, ultrasound extraction and accelerated solvent extraction using six various solvent systems. The quality of the extracts was evaluated by LC-ESI-Q-TOF-MS methodologies and spectrophotometric determinations. The obtained results revealed that catechins' extraction efficiency was identical for the three techniques studied. However, larger quantitative differences among the samples were observed when using different solvents. The total content of major catechins and gallic acid was within a very wide range of 10.2-842 mg/L. Ethyl acetate was by far the least effective extractant, regardless of the extraction technique used. After all, the solvent system composed of ethanol:water (1:1 v/v) was proven to be the best to recover catechins and to deliver extracts with the highest antiradical activity.

Application of RRLC-QTOF-MS-based metabonomics and UPE for investigating Spleen-Qi deficiency syndrome with Panax ginseng treatment.

ETHNOPHARMACOLOGICAL RELEVANCE: Spleen-Qi deficiency is a syndrome of traditional Chinese medicine. Panax ginseng (ginseng) is well known as the key herb for replenishing Qi and tonifying Spleen. However, the pathogenesis of Spleen-Qi deficiency syndrome and therapeutic mechanism of ginseng on Spleen-Qi deficiency constitution have not yet been entirely elucidated. AIM OF THE STUDY: The aim of this work was to investigate the pathogenesis of Spleen-Qi deficiency syndrome and therapeutic mechanism of ginseng on Spleen-Qi deficiency constitution. MATERIALS AND METHODS: The urinary metabonomics was investigated before and after ginseng treatment in Spleen-Qi deficiency subjects by rapid resolution liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (RRLC-QTOF-MS). The spectra of metabolites were analyzed by principal component analysis (PCA) and the score showed significant difference among the three different groups. The serum biochemical parameters creatine kinases (CK), lactate dehydrogenase (LDH), interferon-γ (INF-γ), Interleukin-4 (IL-4), superoxide dismutase (SOD) and malondialdehyde (MDA) were determined by assay kits. In addition, ultraweak photon emission (UPE) intensity was measured at dazhui point in each subject. RESULTS: According to the orthogonal partial least-squares discriminant analysis (OPLS-DA) results and biochemistry databases searching, 15 potential biomarkers were identified to be involved in Spleen-Qi deficiency syndrome and ginseng influenced Spleen-Qi deficiency. The metabonomics and biological experiment data indicated that metabolism pathways were corresponding to energy metabolism, amino acid, carbohydrate, lipid and pyrimidine metabolisms, oxidative stress urea cycle, and intestinal flora metabolism. And the UPE intensity decreased significantly after the treatment. CONCLUSIONS: Ginseng could promote the related metabolisms in Spleen-Qi deficiency constitution and the metabolites and UPE intensity may be useful as potential biomarkers for diagnosing and monitoring for Spleen-Qi deficiency syndrome.

1H HR-MAS NMR and chemometric methods for discrimination and classification of Baccharis (Asteraceae): A proposal for quality control of Baccharis trimera.

Baccharis trimera is a species recognized by health agencies and recommended by the Brazilian Pharmacopoeia by having medicinal properties. In this work, HR-MAS NMR spectroscopy combined with chemometric tools, such as Principal Components Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA) and Soft Independent Modeling by Class Analogy (SIMCA), were used to evaluate the quality control and authenticity of commercial samples of Baccharis, as well as to discriminate B. trimera samples from other species of the Caulopterae section (B. articulata, B. trimera, B. junciformis, B. milleflora, and B. myriocephala). The high morphological similarity of these species makes it difficult for their identifications and discriminations, even by taxonomists. Different PCA pre-processing (autoscaling, Pareto scaling, and mean centering) allowed to discriminate B. trimera and B. myriocephala from the other species, mainly due to the presence of carquejyl acetate, indicated their chemical similarity. The 1H HR-MAS NMR spectral profile offers the possibility of tracking not only the chemical markers, such as the presence of carquejyl acetate, which can also be helpful in the B. trimera authentication/identification. The application of classification methods in standard samples revealed that PLS-DA models showed better performance on the calibration and validation sets than SIMCA model. However, PLS-DA and SIMCA applied to commercial samples showed that none of the commercial samples were classified as B. trimera, which suggested the lack of strict quality control regarding these products. The methodology developed in the present work might contribute to chemotaxonomy of the genus Baccharis.

Unified approaches to assessing treatment effect of traditional Chinese medicine based on health profiles.

Two dissimilarity indices are introduced to measure the disharmony of a human body system by mimicking the population bioequivalence and the individual bioequivalence concepts. Hypotheses for the treatment effect of a traditional Chinese medicine are formulated based on the two indices and then tested under the proposed designs by reverting an approximate confidence upper bound. The proposed methods can also be used when a drug product has multiple components or a trial has multiple endpoints.

Antihypertensive constituents in Sanoshashinto.

It has been reported that Sanoshashinto (SanHuangXieXinTang, ), which is composed of Rhei Rhizoma, Scutellariae Radix, and Coptidis Rhizoma, exhibits vasorelaxant effects in vitro and lowers blood pressure of patients. Based on this discovery, in this study, a mixture containing those three materials and combinations of them were extracted with methanol, and the extracts were fractionated into different parts. Effects of all extracts and fractions on high concentration of potassium chloride (High K+)- or noradrenaline (NA)-induced contractions of isolated rat aortic rings or helical strips were examined. Qualitative and quantitative HPLC analyses of the extracts and the fractions revealed that the contents of baicalin and berberine in Sanoshashinto methanol extract (SHXXTM) were higher than those of the other constituents. All pharmacological and HPLC data were analyzed by principal component analysis (PCA) software and the results indicated that baicalin, berberine, palmatine, baicalein, and wogonoside contributed significantly to the pharmacological activity. Furthermore, spontaneously hypertensive rats (SHRs) that were orally given SHXXTM or a baicalin-berberine combination showed significantly reduced increase in the rate of systolic blood pressure (SBP) compared to the control group. These findings suggested that Sanoshashinto has significant vasorelaxant effects in vitro and antihypertensive effects in vivo, and baicalin and berberine, which were the principal constituents of Scutellariae Radix and Coptidis Rhizoma, were the main antihypertensive constituents in Sanoshashinto. It was speculated that baicalin and berberine produced vasorelaxant effects by activating the NO/cGMP pathway and that the BKCa channel and the DAG/PKC/CPI-17 pathway were also involved.

Identification of Calculus Bovis and its mixed varieties by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) combined with the principal component analysis (PCA) method.

The method of ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) was established and combined with principal component analysis (PCA) to identify natural Calculus Bovis, in vitro cultured Calculus Bovis and artificial Calculus Bovis. PCA, which was particularly powerful in dealing with multicollinearity and variables that outnumber the samples, was used to analyze the UHPLC-MS data of the processed samples, and potential markers were analyzed and described based on orthogonal partial least-squares discriminant analysis. According to the results in this study, the approach of combining UHPLC-QTOF-MS with PCA was proven to be credible and could be used to identify Calculus Bovis from in vitro cultured Calculus Bovis and artificial Calculus Bovis and to determine if there is Calculus Bovis in patented Chinese medicines that should contained Calculus Bovis medicinal materials.

Assessment of volatile fingerprint by HS-SPME/GC-qMS and E-nose for the classification of cocoa bean shells using chemometrics.

The cocoa bean shell (CBS) is a main by-product of cocoa processing, with great potential to be used as an ingredient for functional foods because of its nutritional and flavour properties. This study aimed to characterise and classify CBSs obtained from cocoa beans of diverse cultivars and collected in different geographical origins through their volatile profile assessed using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME/GC-qMS) and E-nose combined with principal component analysis (PCA). The study provides, for the first time in a representative set of samples, a comprehensive fingerprint and semi-quantitative data for >100 volatile organic compounds (VOCs), such as aldehydes, ketones, pyrazines, alcohols, and acids. Through PCA, a clear separation of the Criollo cultivar from the other cultivars was achieved with both GC-qMS and E-nose analytical techniques because of the high content of key-aroma VOCs. Several biomarkers identified by GC-qMS, such as 2-hepanol, 2-methylpropanoic acid, and 2,3,5-trimethylpyrazine, recognized as key-aroma compounds for cocoa beans, were found suitable for the classification of CBSs according to their quality and origin. GC-qMS and E-nose appeared to be suitable analytical approaches to classify CBSs, with a high correlation between both analytical techniques. The volatile fingerprint and classification of CBSs could allow for the selection of samples with a specific flavour profile according to the food application and, therefore, constitute an interesting approach to valorise this by-product as a food ingredient.

Neuroprotective and Anti-Amyloid ß Effect and Main Chemical Profiles of White Tea: Comparison Against Green, Oolong and Black Tea.

White tea (WT) is one of six tea types originally derived from Fujian Province, China. White tea is known for its health-promoting properties. However, the neuroprotective and anti-aggregatory properties of WT against the hallmark toxic Alzheimer's protein, Aß have not been investigated. In this study, WT, green tea (GT), oolong tea (OT) and black tea (BT) were manufactured using tea leaves from the cultivar Camellia sinensis (Jin Guanyin). The protective effects of these tea extracts were then studied under oxidative stress conditions via t-bhp and H2O2 exposure, in addition to Aß treatment using a PC-12 cell model. Each tea type failed to rescue PC-12 cells from either t-bhp or H2O2-mediated toxicity, however each extract exerted significant protection against Aß-evoked neurotoxicity. Results of the Thioflavin T Kinetic (ThT) and TEM assay showed that Aß aggregate formation was inhibited by each tea type. Additionally, TEM also supported the different anti-aggregatory effect of WT by modifying Aß into an amorphous and punctate aggregate morphology. Higher accumulated precedent or potential neuroprotective compounds in WT, including ECG''3Me, 8-C-ascorbyl-EGCG, GABA and Gln, in addition to flavonol or flavone glycosides detected by using UPLC-QTOF-MS and UPLC-QqQ-MS, may contribute to a favourable anti-aggregative and neuroprotective effect of WT against Aß.

1H NMR-based metabonomic revealed protective effect of Moutan Cortex charcoal on blood-heat and hemorrhage rats.

Moutan Cortex charcoal (MCC), the processed root bark of Paeonia suff ;ruticosa Andrews (Paeoniaceae), is a kind of traditional Chinese medicine (TCM) and has been used for treating blood-heat and hemorrhage(BHH)syndrome in China for thousands of years. In order to explore potential metabolic mechanism, 1H NMR-based metabonomics technique was applied to evaluate the effect of MCC on metabolic changes in plasma and urine of BHH rat models. Serum and urine samples were obtained from male SD rats with normal group, model group and MCC group for study. Based on 1H NMR spectra obtained from plasma and urine samples, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing the three group. And the 13 pharmacodynamic biomarkers of MCC were identified in the plasma and urine. The results showed that BHH induced great metabolic disorders in plasma and urine metabolisms. However, MCC could reverse the imbalanced metabolites by alanine, aspartate and glutamate metabolism and citrate cycle (TCA cycle) pathway, and its effect was also confirmed by the general signs and pharmacodynamics assessments. The results indicated that NMR-based metabolomic profiling method is sensitive and specific enough to evaluate the MCC efficacy and mechanism of action on BHH syndromes.

Phenolic variation among Chamaecrista nictitans subspecies and varieties revealed through UPLC-ESI(-)-MS/MS chemical fingerprinting.

INTRODUCTION: Comparative analysis of metabolic features of plants has a high potential for determination of quality control of active ingredients, ecological or chemotaxonomic purposes. Specifically, the development of efficient and rapid analytical tools that allow the differentiation among species, subspecies and varieties of plants is a relevant issue. Here we describe a multivariate model based on LC-MS/MS fingerprinting capable of discriminating between subspecies and varieties of the medicinal plant Chamaecrista nictitans, a rare distributed species in Costa Rica. METHODS: Determination of the chemical fingerprint was carried out on a LC-MS (ESI-QTOF) in negative ionization mode, main detected and putatively identified compounds included proanthocyanidin oligomers, several flavonoid C- and O-glycosides, and flavonoid acetates. Principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA) and cluster analysis of chemical profiles were performed. RESULTS: Our method showed a clear discrimination between the subspecies and varieties of Chamaecrista nictitans, separating the samples into four fair differentiated groups: M1 = C. nictitans ssp. patellaria; M2 = C. nictitans ssp. disadena; M3 = C. nictitans ssp. nictitans var. jaliscensis and M4 = C. nictitans ssp. disadena var. pilosa. LC-MS/MS fingerprint data was validated using both morphological characters and DNA barcoding with ITS2 region. The comparison of the morphological characters against the chemical profiles and DNA barcoding shows a 63% coincidence, evidencing the morphological similarity in C. nictitans. On the other hand, genetic data and chemical profiles grouped all samples in a similar pattern, validating the functionality of our metabolomic approach. CONCLUSION: The metabolomic method described in this study allows a reliably differentiation between subspecies and varieties of C. nictitans using a straightforward protocol that lacks extensive purification steps.

GC-QTOF-MS as valuable tool to evaluate the influence of cultivar and sample time on olive leaves triterpenic components.

Pentacyclic triterpenes play an important role in plant defense and have demonstrated beneficial effects in human health acting in disease prevention. In the present study, the determination of triterpenes compounds in olive leaves of six different cultivars grown at four dates was assessed in order to corroborate the influence of olive growth cycle on triterpenes content and to evaluate if the highest amounts are detected in correspondence to the olive oil production period when the leaves are one of the most important by-product. A GC-QTOF-MS methodology was optimized and validated, and five triterpenes were identified and quantified in all olive leaves samples analysed. ANOVA analyses revealed quantitative differences among sampling times and cultivars. Principal Component Analyses showed a good separation among triterpenes content for the different collecting seasons and cultivars. Picual, the most commonly grown olive today for olive oil production, was the cultivar that presented the highest concentrations of triterpenes and oleanolic acid the major triterpene in all cultivars at all sampling times (54-76.5% of total triterpenes). The triterpenes concentration is higher in June than in the other sampling times. Unfortunately, the leaves sampled at the stage that corresponded to the olive oil production were not the best one in terms of triterpenes content; however the decrease was never >15.5%. Thus, the present results confirm olive leaves a suitable source of bioactive compounds that can be used to obtain high added-value products enriched in triterpenes.

Authentication and discrimination of green tea samples using UV-vis, FTIR and HPLC techniques coupled with chemometrics analysis.

Green tea is a popular beverage consumed worldwide. Its quality should be controlled adequately as the quality is influenced by several factors in addition to adulterations. This study aimed to develop a simple method for assessing the quality of green tea samples obtained from the South and the East Asian regions. The UV-vis, FTIR and HPLC data from 38 samples were subjected to multivariate analyses using the unsupervised recognition techniques comprising Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The model for their authentication was constructed and validated by applying the supervised recognition techniques as Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLS-DA). The percentages of caffeine in the identified samples were determined using a validated HPLC assay in addition to in vitro determination of their antioxidant activity using DPPH radical-scavenging capacity assay. HCA and PCA based on UV data successfully distributed the tested samples into informative clusters. However, that obtained from visible data could only differentiate samples with respect to their powdered condition. On the contrary, PCA from FTIR and HPLC data could hardly discriminate any of the samples. The models constructed using SIMCA and PLS-DA showed a good class separation between the South and the East Asian samples. The percentages of caffeine in the identified samples and the IC50 in DPPH assay are greatly diverse among all the tested samples. Thus, UV spectroscopy and chemometrics have provided a simple and quick tool for the quality control of commercial green tea samples.

MALDI- and LDI-MS saponin fingerprint of leaves and stick components of commercial yerba mate (Ilex paraguariensis).

Yerba mate (YM) is massively produced and consumed as an infusion in South America and spreading all over the world. This product is obtained from dried leaves of Ilex paraguariensis Saint Hilaire, mixed with fragments of dried branches (sticks). For its commercialization, YM must have a minimum percentage of leaves because its presence determines YM quality and price. Till today, a mechanical methodology to determine the relative amount of components (sticks, leaves, and powder) is used. There is not any modern analytical method that provides information for quick characterization of the YM components. Typical saponin fingerprints for leaves and sticks were found by using ultraviolet matrix-assisted laser desorption ionization and ultraviolet laser desorption ionization mass spectrometry. Then, their possible application as useful tools for quick characterization of components of commercial YM (leaves and sticks) is presented. Furthermore, fingerprints obtained from authentic samples of Ilex paraguariensis and Ilex dumosa are also included and discussed. Each Ilex show typical saponin fingerprints for leaves and sticks.

Evaluating green tea quality based on multisensor data fusion combining hyperspectral imaging and olfactory visualization systems.

BACKGROUND: The instrumental evaluation of tea quality using digital sensors instead of human panel tests has attracted much attention globally. However, individual sensors do not meet the requirements of discriminant accuracy as a result of incomprehensive sensor information. Considering the major factors in the sensory evaluation of tea, the study integrated multisensor information, including spectral, image and olfaction feature information. RESULTS: To investigate spectral and image information obtained from hyperspectral spectrometers of different bands, principal components analysis was used for dimension reduction and different types of supervised learning algorithms (linear discriminant analysis, K-nearest neighbour and support vector machine) were selected for comparison. Spectral feature information in the near infrared region and image feature information in the visible-near infrared/near infrared region achieved greater accuracy for classification. The results indicated that a support vector machine outperformed other methods with respect to multisensor data fusion, which improved the accuracy of evaluating green tea quality compared to using individual sensor data. The overall accuracy of the calibration set increased from 75% using optimal single sensor information to 92% using multisensor information, and the overall accuracy of the prediction set increased from 78% to 92%. CONCLUSION: Overall, it can be concluded that multisensory data accurately identify six grades of tea. © 2018 Society of Chemical Industry.