Chemometric Analysis Evidencing the Variability in the Composition of Essential Oils in 10 Salvia Species from Different Taxonomic Sections or Phylogenetic Clades.

Essential oil (EO) of Salvia spp. has been widely used for culinary purposes and in perfumery and cosmetics, as well as having beneficial effects on human health. The present study aimed to investigate the quantitative and qualitative variations in EOs in wild-growing and cultivated pairs of samples from members in four Salvia sections or three clades, namely S. argentea L. (Sect. Aethiopis; Clade I-C), S. ringens Sm. (Sect. Eusphace; Clade I-D), S. verticillata L. (Sect. Hemisphace; Clade I-B), S. amplexicaulis Lam., and S. pratensis L. (Sect. Plethiosphace; Clade I-C). Furthermore, the natural variability in EO composition due to different genotypes adapted in different geographical and environmental conditions was examined by employing members of three Salvia sections or two phylogenetic clades, namely S. sclarea L. (six samples; Sect. Aethiopis or Clade I-C), S. ringens (three samples; Sect. Eusphace or Clade I-D), and S. amplexicaulis (five samples; Sect. Plethiosphace or Clade I-C). We also investigated the EO composition of four wild-growing species of two Salvia sections, i.e., S. aethiopis L., S. candidissima Vahl, and S. teddii of Sect. Aethiopis, as well as the cultivated material of S. virgata Jacq. (Sect. Plethiosphace), all belonging to Clade I-C. The EO composition of the Greek endemic S. teddii is presented herein only for the first time. Taken together, the findings of previous studies are summarized and critically discussed with the obtained results. Chemometric analysis (PCA, HCA, and clustered heat map) was used to identify the sample relationships based on their chemical classes, resulting in the classification of two distinct groups. These can be further explored in assistance of classical or modern taxonomic Salvia studies.

A novel headspace solid-phase microextraction arrow method employing comprehensive two-dimensional gas chromatography-mass spectrometry combined with chemometric tools for the investigation of wine aging.

BACKGROUND: Omics is used as an analytical tool to investigate wine authenticity issues. Aging authentication ensures that the wine has undergone the necessary maturation and developed its desired organoleptic characteristics. Considering that aged wines constitute valuable commodities, the development of advanced omics techniques that guarantee aging authenticity and prevent fraud is essential. RESULTS: Α solid phase microextraction Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry was developed to identify volatiles in red wines and investigate how aging affects their volatile fingerprint. The method was optimized by examining the critical parameters that affect the solid phase microextraction Arrow extraction (stirring rate, extraction time) process. Under optimized conditions, extraction took place within 45 min under stirring at 1000 rpm. In all, 24 monovarietal red wine samples belonging to the Xinomavro variety from Naoussa (Imathia regional unit of Macedonia, Greece) produced during four different vintage years (1998, 2005, 2008 and 2015) were analyzed. Overall, 237 volatile compounds were tentatively identified and were treated with chemometric tools. Four major groups, one for each vintage year were revealed using the Hierarchical Clustering Analysis. The first two Principal Components of Principal Component Analysis explained 86.1% of the total variance, showing appropriate grouping of the wine samples produced in the same crop year. A two-way orthogonal partial least square - discriminant analysis model was developed and successfully classified all the samples to the proper class according to the vintage age, establishing 17 volatile markers as the most important features responsible for the classification, with an explained total variance of 88.5%. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, based on their volatile fingerprint. SIGNIFICANCE: The developed methodology in combination with chemometric techniques allows to trace back and confirm the vintage year, and is proposed as a novel authenticity tool which opens completely new and hitherto unexplored possibilities for wine authenticity testing and confirmation.

Infrared spectroscopy combined with chemometrics in transflectance mode: An alternative approach in the photodiagnosis of COVID-19 using saliva.

The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has required the search for sensitive, rapid, specific, and lower-cost diagnostic methods to meet the high demand. The gold standard method of laboratory diagnosis is real-time reverse transcription polymerase chain reaction (RT-PCR). However, this method is costly and results can take time. In the literature, several studies have already described the potential of Fourier transform infrared spectroscopy (FTIR) as a tool in the biomedical field, including the diagnosis of viral infections, while being fast and inexpensive. In view of this, the objective of this study was to develop an FTIR model for the diagnosis of COVID-19. For this analysis, all private clients who had performed a face-to-face collection at the Univates Clinical Analysis Laboratory (LAC Univates) within a period of six months were invited to participate. Data from clients who agreed to participate in the study were collected, as well as nasopharyngeal secretions and a saliva sample. For the development of models, the RT-PCR result of nasopharyngeal secretions was used as a reference method. Absorptions with high discrimination (p < 0.001) between GI (28 patients, RT-PCR test positive to SARS-CoV-2 virus) and GII (173 patients who did not have the virus detected in the test) were most relevant at 3512 cm-1, 3385 cm-1 and 1321 cm-1 after 2nd derivative data transformation. To carry out the diagnostic modeling, chemometrics via FTIR and Discriminant Analysis of Orthogonal Partial Least Squares (OPLS-DA) by salivary transflectance mode with one latent variable and one orthogonal signal correction component were used. The model generated predictions with 100 % sensitivity, specificity and accuracy. With the proposed model, in a single application of an individual's saliva in the FTIR equipment, results related to the detection of SARS-CoV-2 can be obtained in a few minutes of spectral evaluation.

Non-destructive detection of single corn seed vigor based on visible/near-infrared spatially resolved spectroscopy combined with chemometrics.

Seed vigor is an essential quality evaluation index for seed selection. However, accurately detecting the vigor of a single corn seed is challenging. In this study, we constructed a single-fiber spatially resolved detection device using visible/near-infrared spectroscopy to investigate the patterns and correlations between spatially resolved spectroscopy (SRS) at 500-1000 nm and seed vigor. The device collected spectral data at a light source-detector distance of 5-6.6 mm on the embryo side (S1) and endosperm side (S2) of the corn seeds. The proposed spectral ratio method based on SRS and spectral combination analysis achieved an improvement in the detection accuracy of different corn seed vigor. Modeling by SG-CARS-PLSDA using the ratio method showed further improvement in the prediction ability. The highest accuracy for both S1 and S2 in the Zhengdan 958 variety was 91.67 %, while those of S1 and S2 for the Shaandan 650 variety were 86.67 % and 88.33 %, respectively. In addition, SRS was found to be more advantageous in S2 acquisition, verifying the potential of SRS in the non-destructive testing of seed vigor. This provides a favorable reference for the comprehensive evaluation of other internal quality indices of seeds.

Chemometric Optimization of SPE for the Determination of Multiclass Pesticides in Portable Water Samples by UHPLC-MS/MS.

This study aimed on the development of a SPE-UHPLC-MS/MS method for the simultaneous determination of pesticide residues in drinking water samples. A chemometric approach was applied to optimize the efficiency of the SPE pretreatment procedure. This study involved (i) the application of a Full Factorial Design for the screening of the significant factors, (ii) the application of a Central Composite Design for the determination of the optimal conditions and (iii) the evaluation and validation of the significance of the statistically proposed models. Oasis HLB cartridges were used for the extraction. The optimum sample volume was 300 mL and the elution solvent 3 mL of the mixture of methanol:ethylacetate 70:30 v/v. The method was validated according to the international guidelines. Recoveries were ranged from 63 to 116% and the detection limits were between 0.1 and 1.5 pg mL- 1. The validated method could be used in routine analysis for pesticides screening.

The chemometrics analysis and integrated pharmacology approach to decipher the effect and mechanism between raw and processed cistanche tubulosa.

ETHNOPHARMACOLOGICAL RELEVANCE: Cistanche tubulosa (CT) is the dried fleshy stem with scaly leaves of Cistanche tubiflora (Schenk) Wight, which has the effects of tonifying the kidney-yang, benefiting the vital essence and blood, and moisturizing the intestines and laxatives. There are differences in the activity of CT before and after processing, but the mechanism of processing is not clear. AIM OF THE STUDY: The study aimed to compare the strength of action of CT before and after yellow-wine processing in the treatment of constipation and kidney yang deficiency and to identify the active ingredients responsible for the differences in activity before and after yellow-wine processing. MATERIALS AND METHODS: This study established the fingerprints of CT and PCT using HPLC to identify their shared components. Then efficacy of KYDS and FC were carried out to compare the differences between CT and PCT in terms of efficacy. Next, this study established the spectrum-effect relationship between the shared chemical components and the medical effects of CT and PCT using the gray correlation analysis and entropy methods. Ultimately, the activity of the analyzed chemical components was verified using the zebrafish model. RESULTS: CT was more effective than PCT in promoting intestinal peristalsis, regulating gastrointestinal hormone levels, and thus treating FC. PCT was more effective than CT in improving the level of hormone indexes of the hypothalamus-pituitary-target gland axis, replenishing blood, and enhancing immunity. Through the analysis of the spectrum-effect relationship, it was finally found that 5, 6, 12 (tubuloside A), and 13 (isoacteoside) might be more closely related to the activity of tonifying kidney yang, and peaks 9, 10, and 11 (acteoside) are more closely associated with the treatment of constipation, and peaks 3 (salidroside), 4, 1, 2 (geniposidic acid), and 8 (echinacoside) were associated with both kidney yang tonic and treatment of constipation. At the same time, an activity verification experiment showed that echinacoside, geniposidic acid, and salidroside were effective in the treatment of FC and KYDS, while acteoside was very effective in the treatment of FC, and tubuloside A was significant in supplementing the blood, which validated the spectrum-effect relationship analysis. CONCLUSION: This study proved that the raw CT had a better laxative effect, while the yellow-wine processed CT had a better kidney-yang tonic effect; moreover, spectrum-effect relationships were established to analyze the chemical components leading to changes in the activity of CT before and after yellow-wine processing.

Fast Discrimination and Quantification Analysis of Atractylodis rhizoma Using NIR Spectroscopy Coupled with Chemometrics Tools.

In this study, near-infrared (NIR) spectroscopy and high-performance liquid chromatography (HPLC) combined with chemometrics tools were applied for quick discrimination and quantitative analysis of different varieties and origins of Atractylodis rhizoma samples. Based on NIR data, orthogonal partial least squares discriminant analysis (OPLS-DA) and K-nearest neighbor (KNN) models achieved greater than 90% discriminant accuracy of the three species and two origins of Atractylodis rhizoma. Moreover, the contents of three active ingredients (atractyloxin, atractylone, and ß-eudesmol) in Atractylodis rhizoma were simultaneously determined by HPLC. There are significant differences in the content of the three components in the samples of Atractylodis rhizoma from different varieties and origins. Then, partial least squares regression (PLSR) models for the prediction of atractyloxin, atractylone, and ß-eudesmol content were successfully established. The complete Atractylodis rhizoma spectra gave rise to good predictions of atractyloxin, atractylone, and ß-eudesmol content with R2 values of 0.9642, 0.9588, and 0.9812, respectively. Based on the results of this present research, it can be concluded that NIR is a great nondestructive alternative to be applied as a rapid classification system by the drug industry.

Chemometric profiling and anti-arthritic activity of aerial parts of Glinus oppositifolius (L.) Aug. DC.

ETHNOPHARMACOLOGICAL RELEVANCE: Glinus oppositifolius (L.) Aug. DC. belongs to the family Molluginaceae, an annual prostrate herb traditionally used to treat inflammations, arthritis, malarial, wounds, fevers, diarrhoea, cancer, stomach discomfort, jaundice, and intestinal parasites. However, the anti-arthritic activity of the aerial part has still not been reported. AIM OF THE STUDY: To investigate the antioxidant and anti-arthritic activity of G. oppositifolius in Complete Freund's Adjuvant (CFA) induced rats. MATERIALS AND METHODS: The dried aerial parts of this plant material were defatted with n-hexane and extracted by methanol using a soxhlet apparatus. The in vitro anti-arthritic activity of methanolic extract of G. oppositifolius (MEGO) was evaluated in protein denaturation, membrane stabilization, and inhibition of proteinase assay at 25, 50, 100, 200, and 400 µg/ml concentrations. Female Wistar rats were immunized sub-dermally into the right hind paw with 0.1 ml of CFA. Rats were administered with MEGO at doses of 200 and 400 mg/kg once daily for fourteen days after arthritis induction. Assessment of arthritis was performed by measuring paw diameter, arthritic index, arthritic score, body weight, organ weight, and hematological and biochemical parameters, followed by the analysis of pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6), interleukin-1-beta (IL-1ß), cyclooxygenase-2 (COX-2), interleukin 13 (IL-13) and interleukin 10 (IL-10) and histopathological study. In vivo antioxidant effect was investigated in enzymatic assays. The presence of phytoconstituents was analyzed by Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS), respectively. In silico molecular docking study of the compounds was carried out against COX-2, IL-1ß, IL-6, and TNF-α using AutoDock 4.2 and BIOVIA-Discovery Studio Visualizer software. RESULTS: MEGO's in vitro anti-arthritic activity showed dose-dependent inhibition of protein denaturation, membrane stabilization, and proteinase inhibition, followed by significant in vivo anti-arthritic activity. The rats treated with MEGO showed tremendous potential in managing arthritis-like symptoms by restoring hematological, biochemical, and histological changes in CFA-induced rats. MEGO (200 and 400 mg/kg) showed a significant alleviation in the levels of hyper expressed inflammatory mediators (TNF-α, IL-1ß, and IL-6) and oxidative stress (SOD, CAT, GSH, and LPO) in CFA-induced rats. Spergulagenin-A as identified by LC-MS analysis, exhibited the highest binding affinity against COX-2 (-8.6), IL-1ß (7.2 kcal/mol), IL-6 (-7.4 kcal/mol), and TNF-α (-6.5 kcal/mol). CONCLUSIONS: Provided with the comprehensive investigation, methanolic extract of G. oppositifolius against arthritic-like condition is a proof of concept that revalidates its ethnic claim. The presence of Spergulagenin-A might be responsible for the anti-arthritic activity.

Comparison of autoclaving and γ-radiation impact on four spices aroma profiles and microbial load using HS-SPME GC-MS and chemometric tools.

Herbal spices are widely consumed as food additives owing to their distinct aroma and taste as well as a myriad of economic and health value. The aroma profile of four major spices including bay leaf, black pepper, capsicum, and fennel was tested using HS-SPME/GC-MS and in response to the most widely used spices´ processing methods including autoclaving and γ-radiation at low and high doses. Additionally, the impact of processing on microbial contamination of spices was tested using total aerobic count. GC-MS analysis led to the identification of 22 volatiles in bay leaf, 34 in black pepper, 23 in capsicum, and 24 in fennel. All the identified volatiles belonged to oxides/phenols/ethers, esters, ketones, alcohols, sesquiterpene and monoterpene hydrocarbons. Oxides/phenol/ethers were detected at high levels in all tested spices at ca. 44, 28.2, 48.8, 61.1%, in bay leaves, black pepper, capsicum, and fennel, respectively of the total blend and signifying their typical use as spices. Total oxides/phenol/ethers showed an increase in bay leaf upon exposure to γ-radiation from 44 to 47.5%, while monoterpene hydrocarbons were enriched in black pepper upon autoclaving from 11.4 in control to reach 65.9 and 82.6% for high dose and low dose of autoclaving, respectively. Cineole was detected in bay leaf at 17.9% and upon exposure to autoclaving at high dose and γ-radiation (both doses) its level increased by 29-31%. Both autoclaving and γ-radiation distinctly affected aroma profiles in examined spices. Further, volatile variations in response to processing were assessed using multivariate data analysis (MVA) revealing distinct separation between autoclaved and γ-radiated samples compared to control. Both autoclaving at 115 °C for 15 min and radiation at 10 kGy eliminated detected bioburden in all tested spices i.e., reduced the microbial counts below the detection limit (< 10 cfu/g).

Fast identification of the BmNPV infected silkworms by portable NIR spectroscopy and chemometrics.

A convenient, low-cost, and rapid detection of BmNPV-infected silkworms is of great significance for the safety of the sericulture industry. In this study, a portable NIR system was used to collect the spectra of normal silkworms and the infected silkworms induced by the administration of Bombyx mori nuclear polyhedrosis virus (BmNPV). Different spectral pretreatment methods were applied, then principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares discriminant analysis (PLSDA) were used for the classification analysis. The results showed that PCA and LDA were unable to achieve the purpose. For the PLSDA calibration, after the pretreatment of SNV combining 2nd derivative, it had a high identification performance, and obtained low classification errors of 0.023, 0.033, and 0.030 for the calibration set, cross-validation set, and test set, respectively, with higher sensitivity and specificity. Therefore, the BmNPV-infected silkworms can be identified by portable NIR spectroscopy, which will effectively reduce losses for the sericulture industry.

Characterization and classification of oleogels and edible oil using vibrational spectroscopy in tandem with one-class and multiclass chemometric methods.

Oleogel represents a promising healthier alternative to act as a substitute for conventional fat in various food products. Oil selection is a crucial factor in determining the technological properties and applications of oleogels due to their distinct fatty acid composition, molecular weight, and thermal properties, as well as the presence of antioxidants and oxidative stability. Hence, the relevance of monitoring oleogel properties by non-destructive, eco-friendly, portable, fast, and effective techniques is a relevant task and constitutes an advance in the evaluation of oleogels quality. Thus, the present study aims to classify oleogels rapidly and reliably, without the use of chemicals, comparing two handheld near infrared (NIR) spectrometers and one portable Raman device. Furthermore, two different multivariate methods are compared for oleogel classification according to oil type. Three types of oleogels were prepared, containing 95 % oil (sunflower, soy, olive) and 5 % beeswax as a structuring agent, melted at 90 °C. Polarized light microscopy (PLM) images were acquired, and fatty acid composition, peroxide index and free fatty acid content were determined using official methods. A total of 240 oleogel and 92 oil spectra were obtained for each instrument. After spectra pretreatment, Principal Component Analysis (PCA) was performed, and two classification methods were investigated. The Data Driven - Soft Independent Modelling of Class Analogy (DD-SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA) models demonstrated 95 % to 100 % of accuracy for the external test set. In conclusion, the use of vibrational spectroscopy using handheld and portable instruments in tandem with chemometrics showed to be an efficient alternative for classifying oils and oleogels and could be extended to other food samples. Although the classification of vegetable oils by NIR is widely used and known, this work proposes the classification of different types of oil in oleogel matrices, which has not yet been explored in the literature.

Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics.

Paw San rice, also known as "Myanmar pearl rice", is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice. In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice. The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.

Identification of lentils (Lens culinaris Medik) from Eglouvi (Lefkada, Greece) based on rare earth elements profile combined with chemometrics.

An analytical approach has been developed to verify the authenticity of premium lentils originating from Eglouvi, Lefkada, Greece. The method relies on the digestion of samples followed by the analysis of their rare earth elements (REEs) content. Lentils originating from Eglouvi exhibit higher content in most REEs compared to lentils from other regions as well as distinct Sc/Y and Sc/Yb concentration ratios. Principal component analysis effectively segregates "Eglouvi" lentils into a distinct cluster. Soft Independent Modelling of Class Analogy (SIMCA) successfully models "Eglouvi" lentils. Significant enhancement in model specificity was achieved upon inclusion of Sc/Y and Sc/Yb concentration ratios as additional variables. The model is capable of detecting adulteration in blends of Eglouvi lentils, with a minimum rejection threshold of 4.6% w/w for Greek lentil adulterants and 6.0% w/w for imported lentil adulterants.

Powdered plant beverages obtained by spray-drying without carrier addition-physicochemical and chemometric studies.

Plant-based beverages (PBs) are currently gaining interest among consumers who are seeking alternative sustainable options to traditional dairy drinks. The study aimed to obtain powdered plant beverages without the addition of carriers by spray drying method to implement them in the future as an alternative to the liquid form of dairy drinks. Some of the most well-known commercial beverages sources like soy, almond, rice and oat were analyzed in this work. The effect of different treatments (concentration, addition of oat fiber) and two approaches od spray drying (conventional high temperature spray drying-SD, and dehumidified air spray drying at low temperature-DASD) were presented. Moreover, moisture content, water activity, particle morphology and size of obtained powders were analyzed. It was possible to obtain PBs without the addition of carriers, although the drying yield of four basic beverages was low (16.1-37.4%). The treatments and change in spray drying approach enhanced the drying yield, especially for the concentrated beverage dried using DASD (59.2%). Additionally, Fourier Transform Infrared (FTIR) spectroscopy was applied to evaluate the differences in chemical composition of powdered PBs. FTIR analysis revealed differences in the range of the absorption frequency of amide I, amide II (1700-1500 cm-1) and carbohydrate region (1200-900 cm-1). Principal component analysis (PCA) was carried out to study the relationship between spray dried plant beverages samples based on the fingerprint region of FTIR spectra, as well as the physical characteristics. Additionally, hierarchical cluster analysis (HCA) was employed to explore the clustering of the powders.

Nondestructive identification and classification of starch types based on multispectral techniques coupled with chemometrics.

Starch is the main source of energy and nutrition. Therefore, some merchants often illegally add cheaper starches to other types of starches or package cheaper starches as higher priced starches to raise the price. In this study, 159 samples of commercially available wheat starch, potato starch, corn starch and sweet potato starch were selected for the identification and classification based on multispectral techniques, including near-infrared (NIR), mid-infrared (MIR) and Raman spectroscopy combined with chemometrics, including pretreatment methods, characteristic wavelength selection methods and classification algorithms. The results indicate that all three spectral techniques can be used to discriminate starch types. The Raman spectroscopy demonstrated superior performance compared to that of NIR and MIR spectroscopy. The accuracy of the models after characteristic wavelength selection is generally superior to that of the full spectrum, and two-dimensional correlation spectroscopy (2D-COS) achieves better model performance than other wavelength selection methods. Among the four classification methods, convolutional neural network (CNN) exhibited the best prediction performance, achieving accuracies of 99.74 %, 97.57 % and 98.65 % in NIR, MIR and Raman spectra, respectively, without pretreatment or characteristic wavelength selection.

A novel approach using ATR-FTIR spectroscopy and chemometric analysis to distinguish male and female human hair samples.

This article presents an attempt to discriminate between human male and female hair samples using a single strand of scalp hair. The methodology involves the non-destructive application of ATR-FTIR spectroscopy coupled with chemometric analysis. A total of 96 hair samples, evenly distributed between 48 male and 48 female volunteers from India, were collected. Spectral analysis revealed subtle differences between the two groups, and reliance on visual interpretation might introduce biasness. To avoid subjective biases, chemometric techniques such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were employed for enhanced data visualization and separation. PCA results revealed that the first 10 principal components accounted for 93% of the total variance, with three significant PCs. The PLS-DA model demonstrated a remarkable sensitivity and specificity in sex discrimination from hair samples, establishing its efficacy as a robust classification tool. Furthermore, the proposed model exhibited 100% accuracy in predicting unknown samples, underscoring its potential applicability in real-world scenarios. These outcomes affirm the viability of our approach for non-invasive classification of human male and female hair based on single-strand scalp hair analysis.

Application of UV-Vis-NIR and FTIR spectroscopy coupled with chemometrics for quality prediction of katsuobushi based on the number of smoking treatments.

Katsuobushi, a smoked, dried skipjack tuna, is a traditional Japanese food additive with a unique flavor and taste. Gas chromatography mass spectrometry (GC-MS), fourier transform infrared (FTIR), and ultraviolet-visible-near infrared spectroscopy (UV-Vis-NIR) combined with chemometric methods were evaluated the quality of katsuobushi according to the number of smoking treatments. Using GC-MS, 46 metabolites were identified and five metabolites were selected as key compounds. All samples were classified according to their smoking number via principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) of the FTIR and NIR spectra. Partial least squares regression (PLSR) analysis revealed that the FTIR and NIR spectra were highly correlated with the metabolites by GC-MS. These results demonstrated the potential of using the FTIR and NIR spectroscopy combined with chemometrics to assess the quality of katsuobushi based on the smoking treatments, with NIR spectroscopy showed particularly promising.

Rapid identification of Radix Astragali origin by using fluorescence probe combined with chemometrics.

Fluorescent probes for metal ion recognition can be divided into selective probes, weakly selective probes, and non-selective probes roughly. Weakly selective probes are not often used for quantitative analysis of metal ions due to their overlapping spectra resulting from simultaneous interactions with multiple metal ions. Conversely, the different metal ions contained in herbal medicine extracts from different geographical origins will produce corresponding fluorescence fingerprint profiles after interaction with weakly selective fluorescence probes. The performance can be used in the study of origin tracing of food or Chinese herbal medicine. Weakly selective fluorescent probes of benzimidazole derivatives have been synthesized and attempted to be used in the origin tracing of Radix Astragali in this work. Radix Astragali from different origins will produce different fluorescence fingerprint spectra due to the difference of metal ions and content in combination with the probe. Excitation-emission matrix (EEM) fluorescence spectroscopy in conjunction with N-way partial least squares discriminant analysis (N-PLS-DA), and unfolded partial least squares discriminant analysis (U-PLS-DA) were used to identify the origin of 150 Radix Astragali samples from five geographical origins. The prediction results showed that the correct recognition rates of the U-PLS-DA model and N-PLS-DA model are 95.92% and 93.88%, respectively. In comparison, the results of U-PLS-DA are slightly better than those of N-PLS-DA. These findings indicate that EEM fluorescence spectroscopy based on weakly selective fluorescent probes combined with multi-way chemometrics provides a good idea for the origin tracing of traditional Chinese medicine.

Polar licit and illicit ingredients in dietary supplements: chemometric optimization of extraction and HILIC-MS/MS analysis.

Many dietary supplements claim the ability to enhance sports performance and to improve the fitness of the consumers. Occasionally, along with legal ingredients, illicit compounds may be added without being labelled, leading to unintended doping. Hence, the aim of this study was to develop an analytical method to determine a set of 12 polar (logDpH=7 from -2.0 to +0.3) compounds including diuretics, stimulants, ß2-agonists, methylxanthines, and sweeteners. Hydrophilic interaction liquid chromatography was chosen as separation strategy, coupled with tandem mass spectrometry. The instrumental method was optimized using a two-step design of experiments (DoE). Firstly, a Plackett-Burman (PB) DoE was performed to identify the more influencing variables affecting peak areas and chromatographic resolution among temperature, water percentage in the mobile phase, and flow rate, as well as type and concentration of buffers. Secondly, a D-optimal DoE was set, considering only the most significant variables from the PB-DoE results, achieving a deeper understanding of the retention mechanism. Sample processing by salt-assisted liquid-liquid extraction was studied through DoE as well, and the whole method showed recoveries in the range 40-107% and procedural precision ≤11% for all analytes. Finally, it was applied to real samples, in which the four methylxanthines and two artificial sweeteners were detected and quantified in the range of 0.02-192 mg g-1. These values were compared to the quantities declared on the DS labels, when possible. Furthermore, a sequence of MS/MS scans allowed detection of a signal in one of the samples, structurally similar to the ß2-agonist clenbuterol.

A Box-Behnken design-based chemometric approach to optimize the sono-photodegradation of hydroxychloroquine in water media using the Fe(0)/S2O82-/UV system.

The huge utilization of hydroxychloroquine in autoimmune infections led to an abnormal increment in its concentration in wastewater, which can pose a real risk to the environment, necessitating the development of a pretreatment technique. To do this, we are interested in researching how hydroxychloroquine degrades in contaminated water. The main goal of this investigation is to optimize the operating conditions for the sono-photodegradation of hydroxychloroquine in water using an ultrasound-assisted Fe(0)/ S 2 O 8 2 - /UV system. To get adequate removal of HCQ, a chemometric method based on the Box-Behnken design was applied to optimize the influence of the empirical parameters selected, including Fe(0) dose, S 2 O 8 2 - concentration, pH, and initial HCQ concentration. The quadratic regression model representing the HCQ removal rate (η(%)) was evolved and validated by ANOVA. The optimal conditions as a result of the above-mentioned trade-off between the four input variables, with η(%) as the dependent output variable, were captured using RSM methodology and the composite desirability function approach. For HCQ full decomposition, the optimal values of the operating factors are as follows: S 2 O 8 2 - dose, 194.309 mg/L; Fe(0) quantity, 198.83 mg/L; pH = 2.017, and HCQ initial dose of 296.406 mg/L. Under these conditions, the HCQ removal rate, achieved after 60 min of reaction, attained 98.95%.