NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.

As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and robust analytical characterization of analytes has become a pressing priority. Spectroscopic tools, like near-infrared (NIR) spectroscopy, are finding increasing use for real-time quantitative analysis. Yet detection of multiple low-concentration analytes in microbial and mammalian cell cultures remains an ongoing challenge, requiring the selection of carefully calibrated, resilient chemometrics for each analyte. The convolutional neural network (CNN) is a puissant tool for processing complex data and making it a potential approach for automatic multivariate spectral processing. This work proposes an inception module-based two-dimensional (2D) CNN approach (I-CNN) for calibrating multiple analytes using NIR spectral data. The I-CNN model, coupled with orthogonal partial least squares (PLS) preprocessing, converts the NIR spectral data into a 2D data matrix, after which the critical features are extracted, leading to model development for multiple analytes. Escherichia coli fermentation broth was taken as a case study, where calibration models were developed for 23 analytes, including 20 amino acids, glucose, lactose, and acetate. The I-CNN model result statistics depicted an average R2 values of prediction 0.90, external validation data set 0.86 and significantly lower root mean square error of prediction values ∼0.52 compared to conventional regression models like PLS. Preprocessing steps were applied to I-CNN models to evaluate any augmentation in prediction performance. Finally, the model reliability was assessed via real-time process monitoring and comparison with offline analytics. The proposed I-CNN method is systematic and novel in extracting distinctive spectral features from a multianalyte bioprocess data set and could be adapted to other complex cell culture systems requiring rapid quantification using spectroscopy.

Rapid analysis of bioactive compounds from citrus samples by direct analysis in real-time mass spectrometry combined with chemometrics.

Renowned for their nutritional benefits, citrus fruits are harvested at various stages in China for functional food production. This study introduces an innovative analytical method, DART-MS, enabling direct qualitative analysis of citrus samples without the need for preprocessing. Simultaneously, the combination of chemometrics can be applied to distinguish between three different citrus samples: Citri Reticulatae Pericarpium, Citri Reticulatae Pericarpium Viride, and Citri Reticulatae "Chachi". Notably, given the international regulatory concerns surrounding synephrine, a precise quantitative analysis method for synephrine was developed. The limit of detection (LOD) and the limit of quantification (LOQ) were 39 ng mL-1 and 156 ng mL-1, respectively. The recovery rates obtained varied from 98.46% to 100.71%. Furthermore, the intra-day and inter-day precision demonstrated robust consistency, with values spanning 5.0-6.1% and 5.03-6.08%, respectively, offering quicker results compared to those from HPLC-MS, promising a safer assessment of herbal and food products.

Holistic quality evaluation method of Epimedii Folium based on NIR spectroscopy and chemometrics.

INTRODUCTION: There are some problems in the quality control of Epimedii Folium (leaves of Epimedium brevicornum Maxim.), such as the mixed use of Epimedii Folium from different harvesting periods and regions, incomplete quality evaluation, and time-consuming analysis methods. OBJECTIVE: Near-infrared (NIR) spectroscopy was conducted to establish a rapid overall quality evaluation method for Epimedii Folium. MATERIALS AND METHODS: Quantitative models of the total solid, moisture, total flavonoid, and flavonol glycoside (Epimedin A, Epimedin B, Epimedin C, Icariin) contents of Epimedii Folium were established by partial least squares regression (PLSR). The root mean square error (RMSE) and correlation coefficient (R) were used to evaluate the performance of models. The qualitative models of Epimedii Folium from different geographic origins and harvest periods were established based on K-nearest neighbor (KNN), back-propagation neural network (BPNN), and random forest (RF). Accuracy and Kappa values were used to evaluate the performance of models. A new multivariable signal conversion strategy was proposed, which combines NIR spectroscopy with the PLSR model to predict the absorbance values of retention time points in the high-performance liquid chromatography (HPLC) fingerprint to obtain the predicted HPLC fingerprint. The Pearson correlation coefficient and cosine coefficient were used to evaluate the similarity between real and predicted HPLC fingerprints. RESULTS: Qualitative models, quantitative models, and the similarity between real and predicted HPLC fingerprints are satisfactory. CONCLUSION: The method serves as a fast and green analytical quality evaluation method of Epimedii Folium and can replace traditional methods to achieve the overall quality evaluation of Epimedii Folium.

Quality markers of Polygala fallax Hemsl decoction based on qualitative and quantitative analysis combined with network pharmacology and chemometric analysis.

INTRODUCTION: Polygala fallax Hemsl (PFH) is a widely used herbal medicine in Guangxi, China. At present, research on PFH mainly focuses on extraction technology and cultivation, lacking quality control standards for systematic evaluation. OBJECTIVES: The study aimed to assess the quality of PFH from different sources and to predict markers that would help assess quality. METHODS: Fingerprinting of 15 batches of PFH samples was performed by ultra-high performance liquid chromatography (UPLC) and similarity was assessed using hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discrimination (OPLS-DA). Differential components were screened by mathematical analysis, and a "component-target-pathway" network map was constructed in combination with network pharmacology, quality markers (Q-markers) of PFH were predicted, and quantitative analysis was performed. RESULTS: Fifteen batches were fingerprinted for PFH, with 11 common peaks, and peak 5 was identified as 4-hydroxybenzoic acid, which was generally consistent with the results of HCA, PCA, and OPLS-DA. Network pharmacology screened 18 potential compounds, 45 core targets, and 20 key pathways, integrating fingerprinting, pattern recognition, and network pharmacology methods. One of the potential Q-markers that can identify the principle of testability, efficacy, and specificity is 4-hydroxybenzoic acid, whose content ranges from 0.0188 to 1.4517 mg/g. CONCLUSION: The potential Q-markers of PFH were predicted by integrating fingerprinting, pattern recognition, and network pharmacological analysis, which provided a scientific basis for the overall control and evaluation of the quality of PFH and a theoretical reference for the study of the quality standard of multi-base traditional Chinese medicine.

Investigation of Rosa species by an optimized LC-QTOF-MS/MS method using targeted and non-targeted screening strategies combined with multivariate chemometrics.

INTRODUCTION: Plants of the Rosa genus are renowned for their pronounced and pleasant aroma and colors. OBJECTIVE: The aim of this work was to develop a novel liquid chromatographic triple quadrupole time-of-flight tandem mass spectrometric (LC-QTOF-MS/MS) method for the investigation of the bioactive fingerprint of petals of different genotypes belonging to Rosa damascena and Rosa centifolia species. METHODOLOGY: Central composite design (CCD) of response surface methodology (RSM) was used for the optimization of the LC-QTOF-MS/MS method. The method was validated and target, suspect, and non-target screening workflows were applied. Statistical analysis and chemometric tools were utilized to explore the metabolic fingerprint of the Rosa species. RESULTS: RSM revealed that the optimal extraction parameters involved mixing 11 mg of sample with 1 mL of MeOH:H2O (70:30, v/v). Target analysis confirmed the presence of 11 analytes, all of which demonstrated low limits of quantification (LOQs; as low as 0.048 ng mg-1) and sufficient recoveries (RE: 85%-107%). In total, 28 compounds were tentatively identified through suspect analysis. Non-target analysis enabled the generation of robust OPLS-DA and HCA models that classified the samples according to their species with 100% accuracy. CONCLUSIONS: A novel LC-QTOF-MS/MS method was developed and applied in the analysis of 47 R. centifolia and R. damascena flowers belonging to different genotypes.

Characterisation and critical processes identification for production of herbal preparations using 1H-NMR and chemometrics: A case study of Trichosanthis Pericarpium injection.

INTRODUCTION: Herbal preparations are extensively utilised for the treatment of diseases in Asian countries. However, the variations in origin, climate, and production processes can lead to inconsistencies in the quality of herbal preparations. Existing quality control methods only target a few components in the finished product but ignore the control in the pharmaceutical process. Therefore, this study intends to develop a comprehensive component analysis method for intermediates in the pharmaceutical process to reveal the change patterns of substances and deepen the process understanding. OBJECTIVE: This study aims to develop a rapid and comprehensive process characterisation and critical process identification method for herbal preparations. METHODS: Six batches of Trichosanthis Pericarpium injection (TPI) intermediates were collected from the production process. Proton nuclear magnetic resonance (1H-NMR) spectra were acquired for qualitative and quantitative analysis of the se intermediates. Subsequently, chemometrics were used to identify critical processes and potential chemical markers. RESULTS: A total of 39 components in intermediates were identified, and the transfer of 25 components during the production process was investigated. Column chromatography was determined as the critical process. Nine components were identified as chemical markers. CONCLUSION: The application of 1H-NMR facilitated a comprehensive reflection of the chemical composition information of process intermediates, enabling investigations into the transfer of multi-component substances and accurate identification of critical processes and chemical markers.

Quantification and discovery of quality markers from Toddalia asiatica by UHPLC-MS/MS coupled with chemometrics.

INTRODUCTION: Toddalia asiatica (TA) is a classical traditional Chinese medicine used to treat rheumatoid arthritis and contusions. However, research regarding TA quality control is currently limited. OBJECTIVE: We aimed to establish a strategy for identifying quality markers that can be used for the evaluation of the quality of TA. METHOD: A rapid and efficient ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-MS/MS) method was developed for the quantitative determination of 19 compounds in TA from different regions. Then, the extraction process of TA was successively optimized by single-factor optimization and response surface methodology. Moreover, chemometrics was employed to confirm the correlation between quality and target compounds. RESULTS: Utilizing the UHPLC-MS/MS method, separation of the 19 bioactive compounds was achieved within 14 min. The method was validated in terms of linearity (r2 > 0.9982), precision (0.08%-3.70%), repeatability (0.50%-2.54%), stability (2.26%-5.46%), and recovery (95.8%-113%). The optimal extraction process (extraction solvent, 65% ethanol aqueous solution; solid-liquid ratio, 1:20; extraction time, 25 min) was determined with the total content of 19 bioactive compounds as indicator. Significant disparities were observed in the contents of target compounds across different batches of TA. Besides, all samples could be categorized into two distinct groups, and magnoflorine, (-)-lyoniresinol, nitidine chloride, norbraylin, skimmianine, and decarine were identified as quality markers. CONCLUSION: In the present study, we developed a strategy to improve the quality control of TA. In consideration of the pharmacodynamic activity and statistical differences, six compounds are proposed as quality markers for TA.

Rapid and comprehensive quality evaluation of Huang-qin from different origins by FT-IR and NIR spectroscopy combined with chemometrics.

INTRODUCTION: Quality evaluation of Huang-qin is significant to ensure its clinical efficacy. OBJECTIVE: This study aims to establish an accurate, rapid and comprehensive Huang-qin quality evaluation method to overcome the time-consuming and laborious shortcomings of traditional herbal medicine quality assessment methods. METHODS: The contents of baicalin, baicalein and scutellarin in Huang-qin from five different origins were analyzed by FT-IR and NIR spectra combined with multivariate data technology. The quality of Huang-qin from different origins was evaluated by TOPSIS and consistency analysis based on the content of three active ingredients. The correlation between ecological factors and the accumulation of active ingredients was explored. RESULTS: Satisfactory prediction results of PLS models were obtained. Relatively, the model based on FT-IR combined with the PLS regression method has higher R2 and smaller RMSE than the NIR combined with the PLS method. TOPSIS and consistency analysis results showed that the quality of Huang-qin from different geographical origins was significantly different. The results showed that the quality of Huang-qin produced in Shanxi Province was the best among the five origins studied. The results also found that the quality of Huang-qin in different growing areas of the same origin was not completely consistent. The correlation study showed that altitude, sunshine duration and rainfall were the main factors that caused the quality difference of medicinal materials in different geographical origins. CONCLUSION: This study provides a reference for the rapid quantitative analysis of the active components of herbal medicine and the quality evaluation of them.

"UHPLC-Q-TOF/MS-chemometrics-network pharmacology" integrated strategy to discover quality markers of raw and stir-fried Fructus Tribuli and process optimization of stir-fried Fructus Tribuli.

INTRODUCTION: Fructus Tribuli, the dried ripe fruit of Tribulus terrestris L., has various beneficial effects, including liver-calming and depression-relieving effects. Raw Fructus Tribuli (RFT) and stir-fried Fructus Tribuli (SFT) are included in the Chinese Pharmacopoeia 2020 edition (Ch. P 2020). However, owing to the lack of specific regulations on SFT-processing parameters in Ch. P 2020, it is difficult to ensure the quality of commercially available SFT. OBJECTIVE: The present study aimed to screen the quality markers (Q-markers) of RFT and SFT and optimize the processing technology of SFT based on the identified Q-markers. METHODS: First, the ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) technology as well as multiple statistical analysis along with network pharmacology was used to comprehensively identify the Q-markers of RFT and SFT. Then, based on single-factor experiments, the Box-Behnken design (BBD) response surface methodology (RSM) was used to optimize the processing technology of SFT and perform process validation. RESULTS: A total of 63 components were identified in RFT and SFT extracts. Terrestrosin D and Terrestrosin K were initially considered the Q-markers of RFT and SFT, respectively. The optimum processing technology conditions were 208°C, 14 min, and 60 r·min-1. Three batches of process validation were performed, and the mean composite score was 56.87, with a relative standard deviation (RSD) value of 1.13%. CONCLUSION: The content of steroidal saponin components in RFT was significantly different before and after stir-frying. Terrestrosin D and Terrestrosin K were validated as the Q-markers of RFT and SFT, respectively. The identification of Q-markers for RFT and SFT offered a clear index for optimizing the SFT-processing technology and provided a basis for the quality control of RFT and SFT decoction pieces.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques.

INTRODUCTION: Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools. OBJECTIVES: The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources. METHODS: The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar." RESULTS: An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds. CONCLUSION: Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Quality Assessment of Reconstructed Cow, Camel and Mare Milk Powders by Near-Infrared Spectroscopy and Chemometrics.

Milk powders are becoming a major attraction for many industrial applications due to their nutritional and functional properties. Different types of powdered milk, each with their own distinct chemical compositions, can have different functionalities. Consequently, the development of rapid monitoring methods is becoming an urgent task to explore and expand their applicability. Lately, there is growing emphasis on the potential of near-infrared spectroscopy (NIRS) as a rapid technique for the quality assessment of dairy products. In the present work, we explored the potential of NIRS coupled with chemometrics for the prediction of the main functional and chemical properties of three types of milk powders, as well as their important processing parameters. Mare, camel and cow milk powders were prepared at different concentrations (5%, 10% and 12%) and temperatures (25 °C, 40 °C and 65 °C), and then their main physicochemical attributes and NIRS spectra were analyzed. Overall, high accuracy in both recognition and prediction based on type, concentration and temperature was achieved by NIRS-based models, and the quantification of quality attributes (pH, viscosity, dry matter content, fat content, conductivity and individual amino acid content) also resulted in high accuracy in the models. R2CV and R2pr values ranging from 0.8 to 0.99 and 0.7 to 0.98, respectively, were obtained by using PLSR models. However, SVR models achieved higher R2CV and R2pr values, ranging from 0.91 to 0.99 and 0.80 to 0.99, respectively.

A Comprehensive Analysis of Fel Ursi and Its Common Adulterants Based on UHPLC-QTOF-MSE and Chemometrics.

BACKGROUND: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals' bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers' rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MSE and multivariate statistical analysis were used to explore the differences in XD and six other animals' bile. METHODS: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MSE, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. RESULTS: The results showed that XD and six other animals' bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals' bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. CONCLUSIONS: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals' bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

Benchtop NMR Coupled with Chemometrics: A Workflow for Unveiling Hidden Drug Ingredients in Honey-Based Supplements.

Recently, benchtop nuclear magnetic resonance (NMR) spectrometers utilizing permanent magnets have emerged as versatile tools with applications across various fields, including food and pharmaceuticals. Their efficacy is further enhanced when coupled with chemometric methods. This study presents an innovative approach to leveraging a compact benchtop NMR spectrometer coupled with chemometrics for screening honey-based food supplements adulterated with active pharmaceutical ingredients. Initially, fifty samples seized by French customs were analyzed using a 60 MHz benchtop spectrometer. The investigation unveiled the presence of tadalafil in 37 samples, sildenafil in 5 samples, and a combination of flibanserin with tadalafil in 1 sample. After conducting comprehensive qualitative and quantitative characterization of the samples, we propose a chemometric workflow to provide an efficient screening of honey samples using the NMR dataset. This pipeline, utilizing partial least squares discriminant analysis (PLS-DA) models, enables the classification of samples as either adulterated or non-adulterated, as well as the identification of the presence of tadalafil or sildenafil. Additionally, PLS regression models are employed to predict the quantitative content of these adulterants. Through blind analysis, this workflow allows for the detection and quantification of adulterants in these honey supplements.

[Analysis of chemical compositions in different parts of Isodon japonicus using UPLC-Q-TOF-MS technique combined with chemometrics].

In order to analyze the similarities and differences of chemical compositions between the roots and stems and leaves of Isodon japonicus(IJ), this study utilized UPLC-Q-TOF-MS technology to systematically characterize its chemical compositions, analyzed and identified the structure of its main compounds, and established a method for simultaneous determination of its content by refe-rence substance. A total of 34 major compounds in IJ, including 14 reference compounds, were identified or predicted online. Moreover, an UPLC-UV content determination method was developed for 11 compounds [danshensu, caffeic acid, vicenin-2,(1S,2S)-globoidnan B, rutin,(+)-rabdosiin,(-)-rabdosiin,(1S,2S)-rabdosiin, shimobashiric acid C, rosmarinic acid, and pedalitin]. The method exhibited excellent separation, stability, and repeatability, with a wide linear range(0.10-520.00 µg·mL~(-1)) and high linearity(R~2>0.999). The average recovery rates ranged from 94.72% to 104.2%. The principal component analysis(PCA) demonstrated a clear difference between the roots and stems and leaves of IJ, indicating good separation by cluster. Furthermore, the orthogonal partial least squares discriminant analysis(OPLS-DA) model was employed, and six main differentially identified compounds were identified: rosmarinic acid, shimobashiric acid C, epinodosin, pedalitin, rutin, and(1S,2S)-rabdosiin. In summary, this study established a strategy and method for distinguishing different parts of IJ, providing a valuable tool for quality control of IJ and a basis for the ratio-nal utilization and sustainable development of IJ.

Characteristic profiling of Aconiti Lateralis Radix for distinguishing it from compatible herbal pair using UPLC-Q-TOF-MS coupled with chemometrics.

A method combining ultra-high-performance liquid chromatograph/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and chemometrics was established to evaluate the differences in chemical composition between Aconiti Lateralis Radix (Fuzi in Chinese) before and after combination with Glycyrrhizae Radix et Rhizoma (Gancao in Chinese). UPLC-Q-TOF-MS was used to characterize the chemical components before and after the combination of Fuzi with Gancao, and genetic algorithm selection variables were applied to extract important variables. Partial least square discriminant analysis was used to verify the reliability of the variables obtained by genetic algorithm selection in differentiating Fuzi and combinations with Gancao, and nine potential chemical markers were obtained. The changes in content of chemical markers in Fuzi before and after combination were visualized using a heat map and hierarchical cluster analysis. Based on the chemical markers, characteristic profiling of UPLC-Q-TOF-MS data was developed, then unsupervised principal components analysis and a supervised counter-propagation artificial neural network were used to validate the characteristic profiling approach and showed that it performed well in differentiating between Fuzi and combinations with Gancao.

Elucidating the Color of Rosé Wines Using Polyphenol-Targeted Metabolomics.

The color of rosé wines is extremely diverse and a key element in their marketing. It is due to the presence of anthocyanins and of additional pigments derived from them and from other wine constituents. To explore the pigment composition and determine its links with color, 268 commercial rosé wines were analysed. The concentration of 125 polyphenolic compounds was determined by a targeted metabolomics approach using ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode and the color characterised by spectrophotometry and CieLab parameters. Chemometrics analysis of the composition and color data showed that although color intensity is primarily determined by polyphenol extraction (especially anthocyanins and flavanols) from the grapes, different color styles correspond to different pigment compositions. The salmon shade of light rosé wines is mostly due to pyranoanthocyanin pigments, resulting from reactions of anthocyanins with phenolic acids and pyruvic acid, a yeast metabolite. Redness of intermediate color wines is related to anthocyanins and carboxypoyranoanthocyanins and that of dark rosé wines to products of anthocyanin reactions with flavanols while yellowness of these wines is associated to oxidation.

Elemental Chemometrics as Tools to Depict Stalked Barnacle (Pollicipes pollicipes) Harvest Locations and Food Safety.

The stalked barnacle Pollicipes pollicipes is an abundant species on the very exposed rocky shore habitats of the Spanish and Portuguese coasts, constituting also an important economical resource, as a seafood item with high commercial value. Twenty-four elements were measured by untargeted total reflection X-ray fluorescence spectroscopy (TXRF) in the edible peduncle of stalked barnacles sampled in six sites along the Portuguese western coast, comprising a total of 90 individuals. The elemental profile of 90 individuals originated from several geographical sites (N = 15 per site), were analysed using several chemometric multivariate approaches (variable in importance partial least square discriminant analysis (VIP-PLS-DA), stepwise linear discriminant analysis (S-LDA), linear discriminant analysis (LDA), random forests (RF) and canonical analysis of principal components (CAP)), to evaluate the ability of each approach to trace the geographical origin of the animals collected. As a suspension feeder, this species introduces a high degree of background noise, leading to a comparatively lower classification of the chemometric approaches based on the complete elemental profile of the peduncle (canonical analysis of principal components and linear discriminant analysis). The application of variable selection approaches such as the VIP-PLS-DA and S-LDA significantly increased the classification accuracy (77.8% and 84.4%, respectively) of the samples according to their harvesting area, while reducing the number of elements needed for this classification, and thus the background noise. Moreover, the selected elements are similar to those selected by other random and non-random approaches, reinforcing the reliability of this selection. This untargeted analytical procedure also allowed to depict the degree of risk, in terms of human consumption of these animals, highlighting the geographical areas where these delicacies presented lower values for critical elements compared to the standard thresholds for human consumption.

Microwave-Assisted Extraction Coupled to HPLC-UV Combined with Chemometrics for the Determination of Bioactive Compounds in Pistachio Nuts and the Guarantee of Quality and Authenticity.

Two novel microwave-assisted extraction (MAE) methods were developed for the isolation of phenols and tocopherols from pistachio nuts. The extracts were analyzed by reversed-phase high-pressure liquid chromatography coupled with a UV detector (RP-HPLC-UV). In total, eighteen pistachio samples, originating from Greece and Turkey, were analyzed and thirteen phenolic compounds, as well as α-tocopherol, (ß + γ)-tocopherol, and δ-tocopherol, were identified. The analytical methods were validated and presented good linearity (r2 > 0.990) and a high recovery rate over the range of 82.4 to 95.3% for phenols, and 93.1 to 96.4% for tocopherols. Repeatablility was calculated over the range 1.8-5.8%RSD for intra-day experiments, and reproducibility over the range 3.2-9.4%RSD for inter-day experiments, respectively. Principal component analysis (PCA) was employed to analyze the differences between the concentrations of the bioactive compounds with respect to geographical origin, while agglomerative hierarchical clustering (AHC) was used to cluster the samples based on their similarity and according to the geographical origin.

Development of a rapid polarized total synchronous fluorescence spectroscopy (pTSFS) method for protein quantification in a model bioreactor broth.

Protein quantification during bioprocess monitoring is essential for biopharmaceutical manufacturing and is complicated by the complex chemical composition of the bioreactor broth. Here we present the early-stage development and optimization of a polarized total synchronous fluorescence spectroscopy (pTSFS) method for protein quantification in a hydrolysate-protein model (mimics clarified bioreactor broth samples) using a standard benchtop laboratory fluorometer. We used UV transmitting polarizers to provide wider range pTSFS spectra for screening of the four different TSFS spectra generated by the measurement: parallel (||), perpendicular (⊥), unpolarized (T) intensity spectra and anisotropy maps. TSFS|| (parallel polarized) measurements were the best for protein quantification compared to standard unpolarized measurements and the Bradford assay. This was because TSFS|| spectra had a better analyte signal to noise ratio (SNR), due to the anisotropy of protein emission. This meant that protein signals were better resolved from the background emission of small molecule fluorophores in the cell culture media. SNR of >5000 was achieved for concentrations of bovine serum albumin/yeastolate 1.2/10 g L-1 with TSFS|| . Optimization using genetic algorithm and interval partial least squares based variable selection enabled reduction of spectral resolution and number of excitation wavelengths required without degrading performance. This enables fast (<3.5 min) online/at-line measurements, and the method had an LOD of 0.18 g L-1 and high accuracy with a predictive error of <9%.

Quality assessment of Succus Bambusae oral liquids based on gas chromatography/mass spectrometry fingerprints and chemometrics.

RATIONALE: Succus Bambusae is consumed as a kind of herbal medicine and natural beverage in China. However, the current quality standards for Succus Bambusae are low and lack safety indicators, which makes it difficult to effectively guarantee its quality. Therefore, it is of great significance to study the identification and quality control technology for the product. METHODS: We have developed a set of qualitative and quantitative methods based on gas chromatography/mass spectrometry (GC/MS) for the analysis of volatile components in Succus Bambusae oral liquid (SBOL). Combining GC/MS fingerprint analysis and related chemometrics algorithms, with similarity evaluation, Hotelling T2 and distance to Model X (DModX) as criteria, the quality consistency of different batches was evaluated, and SBOL samples from different manufacturers were differentiated. RESULTS: Twenty-nine volatile components were preliminarily identified from 40 batches of SBOL samples from six manufacturers, and six Q-markers (Quality Markers) for the SBOLs were discussed and determined using GC/MS. The products from different manufacturers were distinguished using chemometrics. CONCLUSIONS: The results showed that the quality of the SBOL samples from different batches and different manufacturers fluctuated greatly, which suggested that research into the raw materials and manufacturing techniques should be strengthened to improve the quality of SBOL and ensure its quality consistency.