Heuristic Evolving Latent Projections Research Articles

Effects of Different Steeping Temperatures on the Leaching of Aroma Components in Black Tea by SPME–GC–MS Coupled with Chemometric Method

Abstract Background: Black tea is famous for its unique aroma. The analysis of aroma components has attracted considerable attention worldwide because of its complex chemical composition and low concentration. Objective: Steeping temperature is one of the most important factors affecting the aroma of black tea. This study aims to evaluate the effects of four steeping temperatures [60, 70, 80, and 95°C (boiling water)]. Methods: Two major factors affecting extraction performance, including the type of extraction method [direct headspace injection (HS) and solid-phase microextraction (SPME)] and extraction time (50, 60, and 70 min), were optimized to enrich and analyze the aroma components of Congou black tea by GC–MS. In addition, heuristic evolving latent projection (HELP), an effective chemometric resolution method, was employed to resolve the overlapped peaks. Results: A total of 83 aroma components were tentatively identified by GC–MS, such as alcohol (42.06–50.52%), aldehyde (12.09–15.97%), and hydrocarbon (4.79–15.32%). Linalool and its oxides (25.49–36.24%) were the most abundant aroma components, followed by geraniol (2.55–8.54%), methyl salicylate (1.84–9.50%), and nerol (1.93–4.41%). Conclusions: The black tea steeped at 95°C smelled more pleasant with mild green, roast, and fruity aroma. Moreover, at 80°C, the tea had sweeter fragrance with floral aroma, while steeping at 60 and 70°C resulted in more reinforced woody and fatty aroma. Highlights: A total of 83 aroma components of black tea were tentatively identified by SPME–GC–MS. The overlapped peaks were resolved by the HELP method. Aroma characteristics of different steeping temperatures were revealed.

Effects of Different Steeping Temperatures on the Leaching of Aroma Components in Black Tea by SPME-GC-MS Coupled with Chemometric Method.

Background: Black tea is famous for its unique aroma. The analysis of aroma components has attracted considerable attention worldwide because of its complex chemical composition and low concentration. Objective: Steeping temperature is one of the most important factors affecting the aroma of black tea. This study aims to evaluate the effects of four steeping temperatures [60, 70, 80, and 95°C (boiling water)]. Methods: Two major factors affecting extraction performance, including the type of extraction method [direct headspace injection (HS) and solid-phase microextraction (SPME)] and extraction time (50, 60, and 70 min), were optimized to enrich and analyze the aroma components of Congou black tea by GC-MS. In addition, heuristic evolving latent projection (HELP), an effective chemometric resolution method, was employed to resolve the overlapped peaks. Results: A total of 83 aroma components were tentatively identified by GC-MS, such as alcohol (42.06-50.52%), aldehyde (12.09-15.97%), and hydrocarbon (4.79-15.32%). Linalool and its oxides (25.49-36.24%) were the most abundant aroma components, followed by geraniol (2.55-8.54%), methyl salicylate (1.84-9.50%), and nerol (1.93-4.41%). Conclusions: The black tea steeped at 95°C smelled more pleasant with mild green, roast, and fruity aroma. Moreover, at 80°C, the tea had sweeter fragrance with floral aroma, while steeping at 60 and 70°C resulted in more reinforced woody and fatty aroma. Highlights: A total of 83 aroma components of black tea were tentatively identified by SPME-GC-MS. The overlapped peaks were resolved by the HELP method. Aroma characteristics of different steeping temperatures were revealed.

Chemometrics-enhanced one-dimensional/comprehensive two-dimensional gas chromatographic analysis for bioactive terpenoids and phthalides in Chaihu Shugan San essential oils.

Chemometrics-enhanced one-dimensional/comprehensive two-dimensional gas chromatographic (GC/GC×GC) technologies, were used to explore the compositions of Chaihu Shugan San essential oils, that were extracted from the herbal formulae by different schemes. We have shown that chemometric resolution using gas chromatographic- mass spectrometry (GC-MS) could be used for the qualitative and quantitative analysis of the majority of Terpenoids or Phthalides from herb formulae and single herbs. A GC×GC system was further optimized to achieve the increased peak capacity and the enhanced signal of the hydro-distillation sample (CSSh). When hardware bottleneck resulted from very complex sample, chemometric tools were once again applied to recover the stained information in the second dimension (2D) matrix data. Heuristic evolving latent projections (HELP) could be used for two dimensional (2D) sub-matrixes Xi at n spectral detection channels, after three dimensional (3D) data splitting. For a real 3D data matrix, alternating trilinear decomposition (ATLD) algorithm could conduct regularization for an iterative trilinear decomposition procedure, by Moore-Penrose pseudoinverse computations based on singular value decomposition. After retention indices (RI) confirmation, 216 target analytes (terpenoids or phthalides) could be elucidated both in CSSh and in supercritical fluid extract (CSSs). Based on the obtained data, some potential quality markers (Q-markers) were identified which may affect the quality of the products. Finally, a "connectivity map" was plotted to describe the unique mechanisms of tradition Chinese medicine (TCM).

Thorough analysis of Iranian spearmint essential oil: combination of chemometrics and gas chromatography-mass spectrometry

The components of Iranian spearmint essential oil were identified and quantified using gas chromatography-mass spectrometry (GC-MS) combined with chemometric tools. A multivariate curve resolution (MCR) approach was used to overcome the problems of background, baseline offset and overlapping/embedded peaks in GC-MS. The peaks were resolved using heuristic evolving latent projection (HELP) and multivariate curve resolution-alternating least squares (MCR-ALS) techniques. A new pure variable selection method named multivariate curve resolution-objective function equal to zero (MCR-FEQZ) is introduced and was applied in this work. The performance of this technique was evaluated and confirmed using MCR-ALS. The analysis of GC-MS data with the help of MCR techniques revealed that the five most abundant constituents of the Iranian spearmint essential oil are (+)-carvone (73.20%), limonen (14.63%), β-bourbonene (1.13%), cineole (1.10%) and 3-terpinolenone (0.82%). The results show that this essential oil could be a great source of carvone and limonene.

Analysis of essential oil ofNardostachys chinensisBatal by GC-MS combined with chemometric techniques

The essential oil extracted from Nardostachys chinensis Batal (NCB) was analyzed by gas chromatography-mass spectrometry (GC-MS) combined with two chemometric resolution methods (CRM), heuristic evolving latent projections (HELP), and selective ion analysis (SIA). Qualitative analysis was performed by comparing the obtained pure mass spectra with those in National Institute of Standards and Technology (NIST) mass spectra database. Identification of some compounds was assisted by comparison of programmed temperature retention indices (PTRIs). The quantitative results were obtained by overall volume integration (OVI). A total of 69 compounds in the essential oil of N. chinensis Batal were identified, accounting for 93.98% of the total content. The major compounds were (−)-spathulenol, epiglobulol, trans-longipinocarveol, and patchouli alcohol which contribute to the antimicrobial and antioxidant activity. The results showed that the efficiency and reliability were greatly improved by use of chemometric tech...

Analysis of the Volatile Chemical Constituents of <i>Agrimonla pilosa Ledeb</i> with Gas Chromatography-Mass Spectrometry and Heuristic Evolving Latent Projections

Analysis of the volatile components in Agrimonia pilosa Ledeb with heuristic evolving latent projections (HELP) was presented. After extracted with water distillation method, the volatile components were detected by GCMS. Then the qualitative and quantitative analysis of the volatile components was completed with HELP resolving two-dimensional original data into mass spectra and chromatograms. 62 of 83 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 86.49% of the total content. The obtained information can provide foundation for further study of Agrimonia pilosa Ledeb. This developed method can also be used for quality control of Agrimonia pilosa Ledeb samples.

Multivariate curve resolution-particle swarm optimization: A high-throughput approach to exploit pure information from multi-component hyphenated chromatographic signals

Multivariate curve resolution-particle swarm optimization (MCR-PSO) algorithm is proposed to exploit pure chromatographic and spectroscopic information from multi-component hyphenated chromatographic signals. This new MCR method is based on rotation of mathematically unique PCA solutions into the chemically meaningful MCR solutions. To obtain a proper rotation matrix, an objective function based on non-fulfillment of constraints is defined and is optimized using particle swarm optimization (PSO) algorithm. Initial values of rotation matrix are calculated using local rank analysis and heuristic evolving latent projection (HELP) method. The ability of MCR-PSO in resolving the chromatographic data is evaluated using simulated gas chromatography–mass spectrometry (GC–MS) and high-performance liquid chromatography–diode array detection (HPLC–DAD) data. To present a comprehensive study, different number of components and various levels of noise under proper constraints of non-negativity, unimodality and spectral normalization are considered. Calculation of the extent of rotational ambiguity in MCR solutions for different chromatographic systems using MCR-BANDS method showed that MCR-PSO solutions are always in the range of feasible solutions like true solutions. In addition, the performance of MCR-PSO is compared with other popular MCR methods of multivariate curve resolution-objective function minimization (MCR-FMIN) and multivariate curve resolution-alternating least squares (MCR-ALS). The results showed that MCR-PSO solutions are rather similar or better (in some cases) than other MCR methods in terms of statistical parameters. Finally MCR-PSO is successfully applied in the resolution of real GC–MS data. It should be pointed out that in addition to multivariate resolution of hyphenated chromatographic signals, MCR-PSO algorithm can be straightforwardly applied to other types of separation, spectroscopic and electrochemical data.

Chemical Fingerprint Analysis for Quality Control of Herba Ephedrae Based on HPLC-DAD Combined with Chemometrics Methods

A method based on high performance liquid chromatography with photodiode array detector (HPLC-DAD) was developed for chemical fingerprinting analysis of Herba Ephedrae. The index of chromatographic fingerprint's information content was utilized to optimize the fingerprint detection conditions, which reduced the time of analysis and increased the veracity of analysis greatly. Then, the similarity analysis of fingerprints was used in quality consistency evaluation of Herba Ephedrae samples. Moreover, hierarchical clustering analysis (HCA) was applied to classify the samples according to their sources and varieties. In addition, the overlapped chromatographic peaks were resolved with the help of heuristic evolving latent projection (HELP) method in order to gain the better quantitative evaluation. The results indicated that the samples could be successfully grouped in accordance with their varieties and sources. Furthermore, five marker constituents were firstly screened out to be the main chemical markers, which importantly contribute to the classification of Herba Ephedrae samples. This investigation shows that the developed methodology can be generalized to the research of quality control of herbal medicines.

Synthetic Reaction Mechanism of Octogen by Chemometrics and Infrared Spectroscopy

Online IR spectrum was used for monitoring the reaction process of synthesizing octogen(HMX).The concentration profiles and IR spectra of reactants,intermediates and product were determined by analyzing the spectral data using multivariate curve resolution-alternating least squares(MCR-ALS) and heuristic evolving latent projection(HELP),and the reasonable mechanism was deduced.The stable geometry of intermediates was optimized at B3LYP/6-31G* theoretical level.Its vibrational frequencies and IR spectra were obtained on the basis of vibrational analysis.The results showed that the variation of intermediates could be obtained quickly with the aid of chemometric resolution and provided significant guidance to the choice of reaction.

Determination of flavor components of rice bran by GC-MS and chemometrics

The flavor composition of rice bran was investigated using solid-phase microextraction (SPME), which was selected from four extraction methods. Additionally, static headspace extraction (SHS), accelerated solvent extraction (ASE) and simultaneous distillation extraction (SDE), followed by GC-MS analysis with the help of heuristic evolving latent projections (HELP) were also used. The effects of the most important factors, including fiber coating, extraction time, and temperature of SPME, on the flavor components of rice bran were studied. Qualitative analysis of the flavor components was obtained by a mass spectra similarity search using pure mass spectra resolved by HELP with the aid of automated mass spectral deconvolution and identification system (AMDIS) software and temperature-programmed retention indices (PTRIs), while quantitative analysis was conducted using the overall volume integration (OVI) technique. A total of 43 out of 76 compounds were tentatively identified, accounting for 82.76% of the total flavor compounds. The flavor compounds were mainly esters, alkanes, alcohols, ketones, aldehydes, and fatty acids, with a composition of 22.24%, 22.16%, 17.75%, 9.06%, 5.72%, and 4.18%, respectively. Together, these results indicate that analyzing the rice bran flavor profile may be more reasonable than solely monitoring free fatty acids for understanding, evaluating and controlling the instability of rice bran.

INVESTIGATION OF CHEMICAL COMPONENTS VARIATION IN MAXING SHIGAN DECOCTION BY HPLC-DAD

Many efficacious herbal prescriptions were used to cure a variety of diseases, each herb contains different components that generate their distinctive efficacy. Maxing Shigan decoction is such an example. Its chemical components were complicated, which couldn't be analyzed by the simple qualitative and quantitative method. So, the similarity and difference of chemical components in Maxing Shigan decoction, single herbs, and disassembled prescriptions were investigated by high-performance liquid chromatography diode array detector (HPLC–DAD) combined with chemometrics methods, which include smoothing and filtering, ordinary manual linear deduction, adaptive iteratively reweighted penalized least squares (airPLS), heuristic evolving latent projections (HELP), and alternative moving window factor analysis (AMWFA). These methods possess practical value in ordinary laboratory when facing complicated components analysis. All resolved pure peaks, including ephedrine, pseudoephedrine, methylephedrine, amygdalin, liquiritin, glycyrrhizic acid, and benzoic acid in the Maxing Shigan decoction, were determined. The dissolved ratios of seven bioactive constituents and other major mutative constituents among Maxing Shigan decoction and other disassembled prescriptions were comprehensively investigated and compared. The comparative results of chemical compositions can help us better understand the chemical composition variation of Maxing Shigan decoction due to the cooking process.

Chromatographic fingerprint analysis of Fructus Aurantii Immaturus by HPLC-DAD and chemometric methods

An efficient method for quality control of Fructus Aurantii Immaturus (FAI), a famous traditional Chinese medicine (TCM) was established. A simple and reliable high-performance liquid chromatography-photodiode array detector (HPLC-DAD) procedure coupled with chemometric methods was developed for fingerprint analysis, qualitative analysis and quantitative determination of this herb. In qualitative and quantitative analyses, heuristic evolving latent projection (HELP) method was employed to resolve the overlapping peaks of the tested samples. Two bioactive components, namely hesperidin and naringin, are confirmed and determined, together with four flavonoids compounds tentatively identified including two new ones. From fingerprint analysis, the fingerprint data were processed with correlation coefficients for quantitative expression of their similarity and dissimilarity. The developed method based on an integration of chromatographic fingerprint and quantitative analysis is scientific, and the obtained results can be applied to the quality control of herb medicine.

Comparative qualitative analysis of nonylphenol isomers by gas chromatography–mass spectrometry combined with chemometric resolution

The relationship between nonylphenol (NP) isomers’ structures and their estrogenic potencies has been evaluated previously. However, due to their similarities in both chemical and physical properties, complete separation and identification remain strikingly difficult. In the present study, gas chromatography–mass spectrometry (GC–MS) is employed to separate commercial NP isomers. Both extracted ion chromatograms (EIC) based on selected ions known to be definitive for the suite of isomers, and the heuristic evolving latent projection (HELP) chemometric resolution method have been applied for the analysis and identification of the NP isomers. This method corrected the wrong identification of one isomer which was suspected based on the EIC data, and also was able to be applied for the determination of an additional isomer with low abundance. Overall, 15 NP isomers have been proposed by the HELP interpretation method. Pure component chromatograms and mass spectra have been extracted with the aid of chemometric resolution. The applicability of the commercial deconvolution software package automated mass spectral deconvolution and identification system (AMDIS) has also been tested against the HELP method for comparative presentation of pure component mass spectra.

Identification of chemical compositions in ether extracts of Ligustrum lucidum by GC-MS and chemometrics

To identify and quantify the compound compositions of ether extracts of Ligustrum lucidum. After extracted 4 hour by Soxhlet extraction with ether, the extractive were analyzed by gas chromatography and mass spectrometry (GC-MS). Furthermore, heuristic evolving latent projection (HELP) was used to resolve the overlapping peaks to obtain the pure concentration profiles and mass spectra. Subsequently, mass spectral similarity search combining with the retention index was employed for the identification of each component. Totally, 75 compounds were identified, accounting for 84.3% of that in the whole ether extracts of L. lucidum. The main compounds of L. lucidum are oleic acid, lupeol and (Z,Z) 9,12-octadecadienoic acid, whose relative content were 9.805%, 8.848%, 8.357%, respectively.

Determination of the volatile constituents in radix Flemingiae Philippinensis by GC-MS and a heuristic evolving latent projection method.

With the help of chemometric resolution methods, a technique for qualitative and quantitative determination of the volatile chemical constituents in Radix Flemingiae Philippinensis by chromatography-mass spectrometry was developed. After the overlapping chromatographic peaks were resolved into pure chromatograms and spectra using a heuristic evolving latent projections (HELP) method, qualitative analysis was performed by similarity search of the obtained pure mass spectrum of each component in the NIST library and the quantitative results were obtained by calculating the total two-way response volume. A total of 63 components were separated and 55 components were identified, accounting for 90.62% of the total content. The main components were farnesol isomer and β-caryophyllene, accounting for 31.33% and 12.60% of the total content, respectively. The obtained results can provide useful information for further study and development of Radix Flemingiae Philippinensis.

Towards obtaining more information from gas chromatography–mass spectrometric data of essential oils: An overview of mean field independent component analysis

Mean field independent component analysis (MF-ICA) along with other chemometric techniques was proposed for obtaining more information from multi-component gas chromatographic–mass spectrometric (GC–MS) signals of essential oils (mandarin and lemon as examples). Using these techniques, some fundamental problems during the GC–MS analysis of essential oils such as varying baseline, presence of different types of noise and co-elution have been solved. The parameters affecting MF-ICA algorithm were screened using a 2 5 factorial design. The optimum conditions for MF-ICA algorithm were followed by deconvolution of complex GC–MS peak clusters. The number of independent components (ICs) (chemical constituents) in each peak cluster was estimated using morphological score method. Eigenvalue profiles of evolving factor analysis (EFA) and pure variables from orthogonal projection approach (OPA) were used as initial mixing matrix (chromatograms) in iterative process. The resolved mass spectra were satisfactorily identified using NIST mass spectral search system. Finally, the results of optimized MF-ICA were compared with those obtained using multivariate curve resolution-alternating least square (MCR-ALS), multivariate curve resolution-objective function minimization (MCR-FMIN) and heuristic evolving latent projection (HELP) methods. It is demonstrated that MF-ICA can be used as an alternative method for a quick and accurate analysis of real multi-component problematic systems such as essential oils.

Determination of Essential Oil Composition from Osmanthus fragrans Tea by GC-MS Combined with a Chemometric Resolution Method

The essential oils of the Osmanthus fragrans tea (OFT), Osmanthus fragrans (OF) and green tea (GT) had been extracted by steam distillation and analyzed by gas chromatography-mass spectrometry (GC-MS) with the help of heuristic evolving latent projections (HELP), an effective chemometric resolution method (CRM). The overlapping peak clusters were resolved into pure chromatograms and pure mass spectra with HELP. The qualitative analysis was performed by similarity searches in the National Institute of Standards and Technology (NIST) mass spectra database with the obtained pure mass spectrum of each component. Identification of some compounds was also assisted by comparison of temperature-programmed retention indices (PTRI) with authentic standards included in our own laboratory database under construction. The quantitative results were obtained by overall volume integration (OVI) method. A total of 67, 73 and 53 components in essential oils of the OFT, OF and GT were identified, accounting for 90.83%, 93.65% and 89.97% total contents of the essential oil of OFT, OF and GT, respectively.

Detection and use of selective ions for providing initial estimates of the concentration vectors in iterative target transformation factor analysis

The characteristic of discreteness in mass spectral direction distinguishes GC/MS from other spectral techniques. Based on this feature, we propose a new method to construct the initial concentration vectors for iterative target transformation factor analysis (ITTFA). For each chemical component, a search for a selective ion with good signal-to-noise ratio is first conducted using evolving factor analysis (EFA) and information entropy. The corresponding chromatogram of the selective ion is subsequently applied to construct an initial concentration vector for ITTFA. Special strategies are developed to cope with chromatographic patterns with embedded peaks and complex multicomponent structure. Results from three simulated and one real mixture and comparison with results from heuristic evolving latent projections (HELP) and a previously published method for definition of the initial profiles for ITTFA, indicate that selective ion chromatogram (SIC) ITTFA represents a fast, automatic and accurate method for resolution of GC/MS data.

Comparative analysis of plant essential oils by GC-MS coupled with integrated chemometric resolution methods

The volatile components obtained from drug pair (DP) Pogostemon cablin (P. cablin)–Perilla frutescens (P. frutescens) and its single herbs were analyzed for the first time by gas chromatography–mass spectrometry (GC-MS) combined with three chemometric resolution methods, namely alternative moving window factor analysis (AMWFA), heuristic evolving latent projections (HELP) and selective ion analysis (SIA). Temperature-programmed retention indices (PTRIs) were also used together with mass spectra for tentative identification of the essential oil constituents. A total of 66, 75 and 84 volatile compounds in the essential oils of the studied samples were qualitatively and quantitatively determined, representing 84.17%, 96.19% and 93.44% of the total content, respectively. Comparative analysis between the DP and its single herbs was done, which showed that the number of essential components of the DP is a little less than the sum of the number of its two single herbs, and the major components of the volatile oil of the DP, except the compound of Patchouli alcohol coming from P. cablin's essential oil, are mainly from that of P. frutescens. The results obtained may provide a useful chemical basis for future research on the correlation between the pharmacodynamic action and chemical constituents of the DP and its single herbs. Our work demonstrated that chemometric resolution techniques and PTRIs could provide a complementary and convenient method for accurate analysis of complex systems once again.

Assessment of the co-elution problem in gas chromatography-mass spectrometry using non-linear optimization techniques

Multivariate curve resolution based on the minimization of an objective function (MCR-FMIN) defined directly from the non-fulfillment of constraints was applied for the first time as a deconvolution method to separate co-eluted gas chromatographic-mass spectrometric (GC-MS) signals. Simulated and real (standard real mixture and limon oil) GC-MS data were used to evaluate the feasibility of this method. The MCR-FMIN solutions have been obtained based on the rotation of principal component analysis (PCA) solutions using the non-linear optimization algorithms. Calculation of the initial values of R rotation matrix using model free analysis methods such as fixed-size moving window-evolving factor analysis (FSMW-EFA), evolving latent projective graphs (ELPGs), and heuristic evolving latent projection (HELP) was proposed for faster convergence and avoiding to be stuck in local minima in MCR-FMIN algorithm. The band boundaries of feasible solutions (MCR-BANDS) obtained using MCR-FMIN were calculated for simulated data to assess the reliability of the method. In addition, the results of this method were compared with those of two most common self-modeling curve resolution (SMCR) methods of multivariate curve resolution-alternating least square (MCR-ALS) and HELP. A reasonable result can be obtained by selecting proper constraints, such as non-negativity, unimodality, normalization, and selectivity. However, when the number of components or the level of noise in each peak cluster increase, the convergence of algorithm becomes difficult and the results are not reliable. For quick and accurate analysis of co-eluted multi-component problematic GC-MS data MCR-FMIN can be considered as an alternative method to the MCR-ALS and HELP methods.