Differentiation of Cymbopogon species based on attenuated total reflectance (ATR) – Fourier transform infrared (FTIR) spectroscopy coupled with chemometric analysis

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Essential oils are highly volatile, aromatic concentrated extracts from plants with wide applications. In this study, fast, easy-to-use attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) was combined with chemometric techniques to verify essential oils’ taxonomy and purity. Principal component analysis (PCA) clustered 30 essential oil samples into three different groups based on plant botanical family and concentration. The first group contained highly concentrated oils from the Asteraceae family, the second group contained highly concentrated oils from the Lamiaceae family, while the last group contained three highly concentrated essential oils from different botanical families and commercial-grade essential oils. Thus, commercial-grade oil samples did not cluster with the corresponding concentrated oil samples despite their similar spectral patterns or botanical family. A loading plot identified infrared (IR) bands that correspond to carbonyl, vinyl, methyl and methylene group vibrations as the most important spectral bands that can be used as marker bands for discrimination between different botanical plant family groups. Hierarchical cluster analysis (HCA) confirmed the results obtained by PCA. ATR-FTIR spectroscopy combined with chemometric algorithms provides a direct and non-destructive method for chemotaxonomic classification of medicinal and aromatic essential oils and an assessment of their purity.

Influence of post-harvesting period on quality of thyme and spearmint essential oils

This study applied differential scanning calorimetry (DSC) coupled with chemometric analysis, specifically, Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR), for the detection of fat adulteration in butter. Adulteration was simulated by adding varying concentrations (2–30%, w/w) of palm stearin and coconut oil to butter. Thermograms acquired from DSC were subjected to chemometric analysis to detect alterations in the butter melting pattern. The results showed that DSC is a highly sensitive technique for detecting even small changes in the butter melting pattern. Discriminant analysis performed using K-Nearest Neighbors (kNN) on 11 distinct butter samples, adulterated with palm and coconut oils at concentration of 10, 20 and 30% (w/w), achieved an accuracy rate higher than 92.1 % in differentiating authentic from adulterated samples. Hierarchical cluster analysis (HCA) enabled the discrimination of the type of adulterant—palm stearin versus coconut oil—at concentrations exceeding 5% (w/w). Compared to traditional methods, DSC coupled with chemometric analysis presents a simple yet effective tool for screening adulterated butter samples, thereby offering potential applications in quality control within the food industry.

Clerodendrum viscosum leaves are used in indigenous systems of medicines of mainland and maritime Southeast Asian countries for the treatment of fever, pain, dysentery, colic, and removal of Ascarids. The Clerodendrum species under study exhibit various phytochemical and morphological similarities. Therefore, it is very challenging to distinguish raw powdered materials used for therapeutic purposes. A validated high-performance thin-layer chromatography (HPTLC) method with 4 key markers, viz., 24β-ethylcholesta-5,22E,25-triene-3β-O-D-glucoside, clerodinin-A, 24β-ethylcholesta-5,22E,25-triene-3β-ol, and lupeol coupled with a chemometric analysis was used to distinguish 3 closely related Clerodendrum species, viz., C. inerme, C. multiforum, and C. viscosum. PRISMA approach was applied for effective HPTLC fingerprint development. The HPTLC—densitometry method was validated following the current International Conference on Harmonisation (ICH) guidelines. Taxonomic differentiation was established by fingerprint-based similarity analysis, a chemotaxonomic study using hierarchical clustering analysis (HCA), and principal component analysis (PCA) was done. HPTLC chromatogram similarity was calculated as correlation coefficient and congruence coefficient values, demonstrating poor similarities (0.26–0.86). However, PCA has resulted in 2 principal component (PC) loadings. PC1 separated C. multiforum, explaining 85.48% of variance mainly due to distribution of 2 triterpenoids. The present HPTLC method is coupled to marker-based quality determination of raw plants as well as discrimination of Clerodendrum species. Chemometric analysis based on 4 metabolites clearly establishes a practical identification of Clerodendrum species intended for therapeutic use.

This work was sparked by the reported identification of man-made cellulosic fibers (rayon/viscose) in the marine environment as a major fraction of plastic litter by Fourier transform infrared (FT-IR) transmission spectroscopy and library search. To assess the plausibility of such findings, both natural and man-made fibers were examined using FT-IR spectroscopy. Spectra acquired by transmission microscopy, attenuated total reflection (ATR) microscopy, and ATR spectroscopy were compared. Library search was employed and results show significant differences in the identification rate depending on the acquisition method of the spectra. Careful selection of search parameters and the choice of spectra acquisition method were found to be essential for optimization of the library search results. When using transmission spectra of fibers and ATR libraries it was not possible to differentiate between man-made and natural fibers. Successful differentiation of natural and man-made cellulosic fibers has been achieved for FT-IR spectra acquired by ATR microscopy and ATR spectroscopy, and application of ATR libraries. As an alternative, chemometric methods such as unsupervised hierarchical cluster analysis, principal component analysis, and partial least squares-discriminant analysis were employed to facilitate identification based on intrinsic relationships of sample spectra and successful discrimination of the fiber type could be achieved. Differences in the ATR spectra depending on the internal reflection element (Ge versus diamond) were observed as expected; however, these did not impair correct classification by chemometric analysis. Moreover, the effects of different levels of humidity on the IR spectra of natural and man-made fibers were investigated, too. It has been found that drying and re-humidification leads to intensity changes of absorption bands of the carbohydrate backbone, but does not impair the identification of the fiber type by library search or cluster analysis.

Bee pollen collected by honeybees (Apis mellifera) is one of the bee products, and it is as valuable as honey, propolis,royal jelly, or beebread. Its quality varies according to its geographiclocation or plant sources. This study aimed to apply rapid, simple,and accurate analytical methods such as attenuated total reflectanceFourier transform infrared spectroscopy (ATR–FTIR) and high-performanceliquid chromatography (HPLC) along with chemometrics analysis to constructa model aimed at discriminating between different pollen samples.In total, 33 samples were collected and analyzed using principal componentanalysis (PCA), hierarchical clustering analysis (HCA), and partialleast squares regression (PLS) to assess the differences and similaritiesbetween them. The PCA score plot based on both HPLC and ATR–FTIRrevealed the same discriminatory pattern, and the samples were dividedinto four major classes depending on their total content of polyphenols.The results revealed that spectral data obtained from ATR–FTIRacquired in the region (4000–500 cm–1) werefurther subjected to a standard normal variable (SNV) method thatremoves scattering effects from spectra. However, PCA, HCA, and PLSshowed that the best PLS model was obtained with a regression coefficient(R2) of 0.9001, root-mean-square estimationerror (RMSEE) of 0.0304, and root-mean-squared error cross-validation(RMSEcv) of 0.036. Discrimination between the three species has alsobeen possible by combining the pre-processed ATR–FTIR spectrawith PCA and PLS. Additionally, the HPLC chromatograms after pre-treatment(SNV) were subjected to unsupervised analysis (PCA–HCA) andsupervised analysis (PLS). The PLS model confers good results by factors(R2 = 0.98, RMSEE = 8.22, and RMSEcv =27.86). Prospects for devising bee pollen quality assessment methodsinclude utilizing ATR–FTIR and HPLC in combination with multivariatemethods for rapid authentication of the geographic location or plantsources of bee pollen.

The efficiency of the treatment of hospital wastewater by actinobacteria was investigated using two chemometric data analysis methods. Six strains of multi-resistant bacteria isolated from Marrakesh hospital wastewater and four strains of antagonistic actinobacteria isolated from Moroccan marine environment were characterized by fatty acids released as methyl esters by thermochemolysis-GC/MS. The hierarchical cluster analysis (HCA) and the principal component analysis (PCA) were used to correlate fatty acids (FA) distributions within strains. HCA allowed to discriminate between bacteria and actinobacteria. A lower Euclidean distance is noted for bacteria. With PCA, linear and branched-chained FAs correlated with bacteria whereas mono unsaturated FAs correlated more specifically with Gram (-) bacteria. Terminally branched-chained FAs correlated most likely with actinobacteria. A co-culture of actinobacteria and bacteria monitored during 15 days demonstrated the efficiency of the biological treatment for 2 of the 4 studied actinobacteria. The effect is more important on Gram-negative bacteria. Antagonistic actinobacteria seem to be poorly efficient against Gram-positive bacteria.

A Novel Method for Early Diagnosis of Malignant Pleural Mesothelioma from Human Serum Samples: ATR-FTIR Spectroscopy

The main aim of this study was to investigate the use of Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR FTIR) and selected chemometric methods to classify eggs in terms of the laying hen farming method, as well as to identify changes in the individual egg compositions during storage. In total, 50 eggs were used for the study; 10 eggs per classes: 0, 1, 2, 3 and rural. Eggs were stored by 29 days period, which was divided on the 10 measuring days in which one egg from each class was tested by recording two FTIR spectra for the shell, albumen and egg yolk. The chemometric analysis, including Hierarchical Cluster Analysis (HCA) and the Principal Component Analysis (PCA), was performed based on the recorded FTIR spectra. Changes in chemical composition during the experiment in individual egg elements were analyzed. Furthermore, by analyzing the graphs (HCA and PCA) obtained by the chemometric analysis, it was noted that the largest changes in the chemical composition of eggs occurred in the shell and yolk, while in the albumen it was less insignificant. The chemometric analysis of the recorded spectra also showed that combination of chemometric methods and FTIR spectroscopy can potentially be used to develop a non-destructive method for classifying eggs in terms of the hen culture method and to monitor of their freshness.

Rhizoma Paridis (RP) is economically significant but identifies complex traditional medicine materials, which can be accidentally contaminated, deliberately substituted, or admixed with other species of similar morphological characteristics. This issue can affect quality and safety issues. In this study, the screening technique to detect adulteration in RP was developed using multiple fingerprints and chemometrics. Fourier transform infrared (FT-IR) spectroscopy and high-performance liquid chromatography (HPLC) combined with chemometrics, including similarity analysis (SA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and hierarchical clustering analysis (HCA), were applied for the identification of RP and its adulterants. HPLC analysis was more sensitive than FT-IR for differentiating RP from its contaminants. Except for the slight overlapping between Paris polyphylla var. chinensis (Franch.) Hand.-Mazz. and Paris mairei H.Lév., the remaining species could be successfully differentiated by the chemometrics method. This study indicates that the fingerprint of FT-IR and HPLC combined with chemometrics may be a valuable tool for discriminating RP and its adulterants. FT-IR and HPLC combined with chemometrics analysis were developed to discriminate between RP and adulterants. The chemometrics analysis using SA and OPLS-DA indicates significant differentiation in the chemical composition of these species. This research provides important chemotaxonomic references in species identification.

1. Background Stroke, i.e. loss of brain function(s) due to disturbance in the blood supply to the brain, is the main cause of adult disability (e.g. paralysis) in the world, leaving more than half of the patients dependent on daily assistance. In Qatar, stroke is a major health problem with an estimated incidence of 238/100,000 per year for the population over 45 years old [1]. Stroke patients are often hospitalized and/or subjected to intensive rehabilitation programs for long periods of time, and their quality of life is severely affected socially and economically. Around 10% of the hospital beds in Qatar are occupied by stroke patients [1]. Thus, without major advances to improve prevention, treatment and rehabilitation of stroke, the social and economic costs of this disease will increase dramatically. There are pathological and physiological changes on the cellular and molecular levels associated with stroke. The objective of this work is to determine the molecular and structural changes occurring in the tissue of rat's brain. Vibrational spectroscopy, i.e. Fourier transform infrared (FTIR) imaging spectroscopy, was used as rapid and objective diagnostic platform to investigate the pathological and pathological changes in the rat's brain sections three weeks after stroke. FTIR spectroscopy was also used to differentiate between the biochemical makeup of the white and grey matters of a healthy control brain samples. Also, in the current study, scanning electron (SEM), energy dispersive X-ray spectroscopy (EDX), and atomic force microscopic (AFM) techniques were assessed to study the structural changes in the rat's brain tissues after experiencing an induced stroke. 2. Experimental 2.1. Sample preparation Rats were anesthetized using 2–3% isoflurane. Experimental stroke was induced in rats by 90-min occlusion of the right middle cerebral artery with an intraluminal filament. Rats were euthanized with a lethal dose of sodium pentobarbital and transcardially perfused with 4% paraformaldehyde. Rat's brains were extracted, embedded in paraffin and then serially sliced, using semi-automated rotary microtome, into 5 μm thickness sections for the FTIR imaging and AFM analysis and 35 μm thickness for the SEM and EDX analysis. The brain sections were mounted on MirrIR CFR, Low-e microscope slides for the FTIR imaging analysis, and on aluminum metal for the SEM analysis and EDX analysis. The paraffin was removed from the samples by using xylene and isopropanol. 2.2. Instrumentation 2.2.1. FTIR Imaging Measurements The FTIR images were obtained using FTIR spectrometer (Agilent Technology) at a reflection mode within the range of 4000–700 cm –1 . Spectral images were analyzed using Metlab software (The Mathworks Inc.). Origin 2015 software was used for graph drawing. Principal component analysis (PCA) was performed to study the spectral data variations between the FTIR spectra and images. 2.2.2. Scanning Electron Microscopy (SEM) Rat's brain sections of 35 μm thickness were mounted on aluminum slides for SEM analysis. All the samples were viewed with a FEI Quanta 200, USA scanning electron microscope at 10 kV. SEM micrographs of the brain stroke and healthy rat's sections were compared. Elemental distribution in both healthy and induced stroke brain sections were investigated by using energy dispersive X-ray spectroscopy (EDX) equipped with SEM. The spectra provided a semi-quantitative view of the elemental composition of both weight and atomic percent. 2.2.3. Atomic Force Microscopy (AFM) Bruker atomic force microscopy (AFM) was used for imaging and quantitatively determining the local elastic properties of healthy and induced stroke rat's brain sections. A controllable and constant force was applied at each data point and using the resulting force-distant curve for the formation the AFM images. Brain sections were scanned at 10 μm by 10 μm. About 100 force-distance curve were collected for each healthy and induced stroke brain sections and two random scan lines of force-distance curves was recorded. 3. Results and Discussions The FTIR spectroscopy results indicated that the white matter is richer in lipid content than the grey matter as shown in Figs. 1 and 2. The infrared spectrum images showed a decrease in the lipid content of the white matter associated with the induced stroke brain sections. FTIR bands assigned to the bio-chemical makeup such as proteins, lipids and ester varied in positions, line-shape, and intensity between control and induced stroke brain samples. The spectral images showed that there is a configuration changes is associated with the lipid bands in the rat's brain white matter that experienced stroke. The FTIR spectral images of the white matter in the induced stroke brain sections indicated that amide I and ester bands experienced a bio-chemical changes as shown in Fig. 3 and 4. Figure 5 shows the second derivative of the collected FTIR spectra from induced stroke brain sections. In Fig. 5, there are spectral differences that assigned to ester and protein regions. Figure 6a represents the loading spectra of the first three principal component analysis (PC1, PC2 and PC3). The variations principally were located in the regions of amide I band at (∼1695-1637 cm –1 ) and small variation in the amide II band at (1543 cm –1 ). Figure 6b represents the loading spectra of the PC4, PC5 and PC6. The variations principally were located in the protein region, mainly amide I band at (∼1695-1637 cm –1 ) and ester band at about 1730 cm –1 . The use of FTIR imaging and chemometric analyses such as principal component analysis (PCA) of spectral data allows to investigate and differentiate spectral images pattern collected from control and stroke rat's brain samples. The scanning electron microscope results showed that lesion region in the induced stroke brain sections are enriched by the selected elements such as Fe and Ca as shown in Fig. 7 (a & b). Scanning electron microscope (SEM) micrographs indicated that there is structure change in the induced stroke brain section. The structure of stroked brain sample in the nanometer scale appeared to be significantly rough compared to the control brain sample (Fig. 8 a & b). Atomic force microscope (AFM) images showed that the stroke brain section is swollen compared to healthy brain sections. The AFM images of the induced stroke brain sections appeared more stretched when compared to the control brain section image as shown in Fig. 9 (a & b). AFM results also showed that the force-distance curves in Fig. 10, recorded using control (healthy) brain sections (blue) and induced stroke brain sections (red). The force-distance showed that the AFM cantilelver deflection of the healthy brain samples is higher than the induced stroke brain section. This indicate that the healthy brain section are softer and elastic than the induced stroke brain sections. 4. Conclusion FTIR imaging spectroscopy, scanning electron and atomic force microscopy techniques were able to analyze and differentiate between the healthy and induced stroke rat's brain sections on the molecular, structural and global levels making them valuable tools to investigate, diagnose and study the structural plasticity of the stroke induced brain. FTIR imaging spectroscopy in combination with multivariate analysis such as principal component analysis (PCA) is a non-destructive technique that proves to be rapid, accurate and straightforward to be performed. It constitutes a powerful approach to be used as a medical diagnosis tool to investigate the pathological changes associated with stroke in the brain tissues. Keywords Fourier Transform Infrared (FTIR) imaging spectroscopy, Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), Brain tissue, Stroke, Chemometric Analysis Acknowledgments This article was made possible by a NPRP award [5 - 381 - 3 - 10] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors. We would like to acknowledge the Center for Advanced Materials at Qatar University for performing the AFM analysis, and Central Laboratories Unit at Qatar University for performing the SEM and EDX analysis. Reference [1] Hamad, A., Sokrab, T.E., Momeni, S., Mesraoua, B., and Lingren, A., Stroke in Qatar: a one-year, hospital-based study. J Stroke Cerebrovasc Dis, 2001. 10(5): p. 236–41.

Rapid subtyping of pathogenic and nonpathogenic Vibrio parahaemolyticus by fourier transform infrared spectroscopy with chemometric analysis

Fuzi is a well-known traditional Chinese medicine developed from the lateral roots of Aconitum carmichaelii Debx. It is rich in alkaloids that display a wide variety of bioactivities, and it has a strong cardiotoxicity and neurotoxicity. In order to discriminate the geographical origin and evaluate the quality of this medicine, a method based on high-performance liquid chromatography (HPLC) was developed for multicomponent quantification and chemical fingerprint analysis. The measured results of 32 batches of Fuzi from three different regions were evaluated by chemometric analysis, including similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), and linear discriminant analysis (LDA). The content of six representative alkaloids of Fuzi (benzoylmesaconine, benzoylhypaconine, benzoylaconine, mesaconitine, hypaconitine, and aconitine) were varied by geographical origin, and the content ratios of the benzoylmesaconine/mesaconitine and diester-type/monoester-type diterpenoid alkaloids may be potential traits for classifying the geographical origin of the medicine. In the HPLC fingerprint similarity analysis, the Fuzi from Jiangyou, Sichuan, was distinguished from the Fuzi from Butuo, Sichuan, and the Fuzi from Yunnan. Based on the HCA and PCA analyses of the content of the six representative alkaloids, all of the batches were classified into two categories, which were closely related to the plants’ geographical origins. The Fuzi samples from Jiangyou were placed into one category, while the Fuzi samples from Butuo and Yunnan were put into another category. The LDA analysis provided an efficient and satisfactory prediction model for differentiating the Fuzi samples from the above-mentioned three geographical origins. Thus, the content of the six representative alkaloids and the fingerprint similarity values were useful markers for differentiating the geographical origin of the Fuzi samples.

Rhizosphere bacterial communities play a crucial role in improving nutrient availability, disease and stress resistance, and overall development in plants. Biofertilizers can enhance plant growth, but little is known about their mode of interaction. Here, we studied the impact of seedling coating with two nitrogen-fixing cyanobacterial strains, Nostoc sp. NoHu, or Anabaenopsis circularis AnHu, on chamomile (Chamomilla recutita L.) growth, essential oil yield and quality, apigenin-7-O-glucoside, and the composition of rhizosphere bacterial communities, under field conditions in Egypt. The rhizosphere bacterial community, analyzed by 16S rRNA amplicon libraries, composed of 31 phyla and 164 different genera. Compared to untreated plants, the application of both strains showed contrasting effects. Nostoc sp. application significantly enhanced almost all tested plant growth parameters, including fresh and dry weights of shoots, roots, and flowers, as well as the yield and content of vital essential oil constituents and the apigenin-7-O-glucoside. Furthermore, Nostoc sp. application increased both the abundance and diversity of the rhizosphere bacterial community compared to untreated plants, suggesting an indirect effect mediated through altering the rhizosphere bacterial community structure. In contrast, A. circularis application negatively affected essential oil yield and quality, exhibited the lowest bacterial abundance and diversity. These findings highlight potential of Nostoc sp. NoHu to boost chamomile productivity and essential oil quality. The contradictory responses between the two cyanobacterial strains emphasize strain-specific effects with Nostoc sp. NoHu as a promising biofertilizer candidate for chamomile.

A comprehensive and innovative chemometric approach: Archaeometric analysis of the sherds from the Neolithic Period to the Chalcolithic and early Bronze Age with the full deployment of FTIR's molecular spectroscopic capabilities