Chemometric Techniques Research Articles

Chemometric Discrimination of Cichorium glandulosum Boiss. et Huet and Cichorium intybus L. via Their Metabolic Profiling, Antioxidative, and Hypoglycemic Activities

Cichorium glandulosum Boiss. et Huet (CG) and Cichorium intybus L. (CI) are widely used as the main raw material of functional food with hepatoprotective and hypoglycemic effects. Due to the lack of comparison on the chemical ingredients and efficacy, they were often used imprecisely and interchangeably. It is necessary to distinguish between them. With the plant metabolomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS) and multivariate chemometric techniques, the chemical ingredients were characterized and 59 compounds between CG and CI were classified. As for antioxidative and hypoglycemic activities in vitro, CI extraction exhibited better antioxidant activity than CG, while CG extraction showed stronger hypoglycemic activity. Furthermore, a bivariate correlation between the chemical composition and efficacy of the extract was also analyzed, and three differentially strong correlation components between CI and CG were prepared, and the antioxidative and hypoglycemic efficacies were compared in vivo and different active phenotypes were obtained. Finally, we revealed chemical and biological differences between CG and CI, providing a basis for achieving better quality control and developing more effective functional foods.

Profiles of Volatile Compounds from Seven New Hybrid Families Obtained by Crossings on Noir de Bourgogne Cultivar and Other Blackcurrant Varieties.

Berries of blackcurrant (Ribes nigrum L.) are popular for their strong and complex aroma and their benefits for health. In Burgundy (France), the most famous blackcurrant cultivar is the "Noir de Bourgogne". A blackcurrant breeding program was conducted to obtain new varieties, more resistant to infections and climate changes. The cultivar "Noir de Bourgogne" was crossed with seven other varieties in order to create a hybrid with good agronomic properties and organoleptic properties close to the ones of "Noir de Bourgogne". Several hybrids were created, and their aromatic profiles studied. Berries of eight cultivars, among which Noir de Bourgogne and hybrids resulting from crossings, were harvested during the summer of 2020. Volatile compounds of berries were analyzed by HS-SPME-GC-MS, and principal component analysis (PCA) was used as the most useful chemometric technique. The profiles in volatile compounds of hybrids were either different from those of the two parental varieties or close to that of varieties other than Bourgogne black. In all cases, the overall aroma strength of the hybrid did not equal that of the Noir de Bourgogne cultivar.

Quality Control and Authentication of Argan Oils: Application of Advanced Analytical Techniques

In addition to the nutritional and therapeutic benefits, Argan oil is praised for its unique bio-ecological and botanic interest. It has been used for centuries to treat cardiovascular issues, diabetes, and skin infections, as well as for its anti-inflammatory and antiproliferative properties. Argan oil is widely commercialized as a result of these characteristics. However, falsifiers deliberately blend Argan oil with cheaper vegetable oils to make economic profits. This reduces the quality and might result in health issues for consumers. Analytical techniques that are rapid, precise, and accurate are employed to monitor its quality, safety, and authenticity. This review provides a comprehensive overview of studies on the quality assessment of Moroccan Argan oil using both untargeted and targeted approaches. To extract relevant information on quality and adulteration, the analytical data are coupled with chemometric techniques.

Benefiting from information‐rich multi‐frequency AC voltammetry coupled with chemometrics on the example of on‐line monitoring of leveler component of electroplating bath

AbstractSimultaneous application of multiple sinusoidal waveforms perturbations superimposed onto DC staircase step significantly enriches current response. The measured current is characterized by a matrix of data rather than a conventional voltammetric output in a form of a vector. This increase of the dimensionality of the current response and therefore the wealth of analytical information is achieved without compromising the time of analysis. The natural approach for compression of such data and extraction of relevant information is by utilizing multi‐way chemometric decomposition techniques. An electroplating solution presents a very challenging analyte for electroanalysis as its constituents interact synergistically with each other during both the plating process and its simulation during electroanalysis. For some components the mechanism is not entirely understood. Therefore, the only way to benefit from the analytical data is by employing soft modeling. The electrode processes involving additives rely heavily on adsorption and, indirectly, on electron transfer kinetics for which AC voltammetry is an analytical technique capable of delivering informative signals. This paper presents a rigorous universal method for calculating and validating an exemplary multi‐way calibration of a leveler component in a copper electroplating bath used in the semiconductor industry. The method presented employs comparatively Parallel Factor Analysis coupled with Inverse Least Squares Regression and multi‐linear Partial Least Squares. The calibration training set consists of multi‐frequency AC voltammetric data subjected to pretreatments aiming to select informative independent variables and exclude outliers.

Surface-enhanced Raman spectroscopy of centrifuged blood serum samples of diabetic type II patients by using 50KDa filter devices

Blood serum contains essential biochemical information which are used for early disease diagnosis. Blood serum consisted of higher molecular weight fractions (HMWF) and lower molecular weight fractions (LMWF). The disease biomarkers are lower molecular weight fraction proteins, and their contribution to disease diagnosis is suppressed due to higher molecular weight fraction proteins. To diagnose diabetes in early stages are difficult because of the presence of huge amount of these HMWF. In the current study, surface-enhanced Raman spectroscopy (SERS) are employed to diagnose diabetes after centrifugation of serum samples using Amicon ultra filter devices of 50 kDa which produced two fractions of whole blood serum of filtrate, low molecular weight fraction, and residue, high molecular weight fraction. Furthermore SERS is employed to study the LMW fractions of healthy and diseased samples. Some prominent SERS bands are observed at 725 cm−1, 842 cm−1, 1025 cm−1, 959 cm−1, and 1447 cm−1 due to small molecular weight proteins, and these biomarkers helped to diagnose the disease early stage. Moreover, chemometric techniques such as principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are employed to check the potential of surface-enhanced Raman spectroscopy for the differentiation and classifications of the blood serum samples. SERS can be employed for the early diagnosis and screening of biochemical changes during type II diabetes.

Chemometric-Assisted Litmus Test: One Single Sensing Platform Adapted from 1-13 to Narrow pH Ranges.

A novel 3 × 4 colorimetric sensing platform, named the chemometric-assisted litmus test (CLT), has been developed by covalently anchoring commercial pH indicators to ethylene vinyl alcohol (EVOH). The proposed device can be exploited for pH determinations in a wide range from 1 to 13 and in specific narrow ranges, achieving sufficient accuracy and errors below 0.5 pH units. The experimental procedure is simple, quick and reliable; equilibration is reached in less than 2 h, CLT pictures are acquired by a camera, and data treatment is performed applying chemometric techniques such as principal component analysis (PCA) and partial least square regression (PLS) to RGB indices.

Techniques Used for Determining the Hydrotreated Vegetable Oil Presence in Diesel

Determining HVO content in diesel is essential for fuel quality control and other important aspects, so studying the techniques used for this purpose is necessary. In this article, the authors did a systematic review to determine the techniques used to define HVO in diesel and the efficiency of each technique. The results of the study showed that the use of techniques that are based on measuring the amount of C14 radiocarbon in the sample have good efficiency, but concerning the cost and time used to perform the exams, FTIR spectroscopy together with the use of Chemometric techniques is an excellent alternative for the study.

Development and validation of a new spectrophotometric method for simultaneous determination of spiramycin and metronidazole in tablet pharmaceutical dosage forms using chemometrics technique in comparison with HPLC

A new, easy, fast, and cost-effective simultaneous spectrophotometric method for determining the combined concentration of spiramycin and metronidazole in tablet pharmaceutical formulations was developed and proposed. The suggested method was validated using two chemometric techniques, namely partial least square regression (PLS) and principal component regression (PCR). The significance of the proposed method is that pretreatment or separation steps are not required. Various drug concentrations and instrumental spectra of 25 mixed solutions of spiramycin and metronidazole were used for model design and validation. The UV analysis of the prepared mixtures was recorded with respect to a selected solvent blank in the wavelength range of 200–375 nm. The digitized absorbance was sampled at 0.2 nm intervals. The R2 values of 1 and 0.9998 assigned for the PLS of spiramycin and metronidazole, and those of 0.9991 and 0.9998 for the PCR of spiramycin and metronidazole, respectively, exhibited greater prediction efficiencies. The results were statistically compared to those of the HPLC reference method. The statistical comparison between the recommended (PLS and PCR) and reference HPLC method did not find any appreciable variations in accuracy or precision. The suggested approach is simple, effective, and trustworthy enough to be employed as an alternative analytical method for quality control of drug analysis in the pharmaceutical industry.

Spectral imaging and chemometrics applied at phenotyping in seed science studies: a systematic review

AbstractThe evaluation of the genetic quality of a seed lot is crucial for the quality control process in its production and commercialization, as well as in the identification of superior genotypes and the verification of the correct crossing in plant breeding programmes. Current techniques, based on the identification of seed morphological characteristics, require skilled analysts, while biochemical methods are time-consuming and costly. The application of spectral imaging analysis, which combines digital imaging with spectroscopy, is gaining ground as a fast, accurate and non-destructive method. The success of this technique is closely linked to chemometric techniques, which use statistical and mathematical tools in data processing. The aim of the work was to evaluate the main procedures in terms of spectral image analysis and chemometric procedures applied in seed phenotyping and its practical application. A systematic review was conducted using the PRISMA methodology, in which a total of 1304 articles were identified and screened to the inclusion of 44 articles pertaining to the scope. It was concluded that spectral image analysis has a high ability to classify seeds of different genotypes (93.33%) in a range of situations: between cultivars; hybrids and progenitors; and hybrids and lines, as well as in the separation of coated seeds. Accurate classification can be obtained by different strategies, such as the choice of the equipment type, the spectrum range and extra features, guided by the characteristics of the species, as well as in the choice of algorithms and dimensionality reduction procedures for the optimization of models when there is a large amount of data. Despite the fact that the practical application of this technique in seed phenotyping still needs to be developed for use in laboratories with large volumes of analyses, lots, genotypes and harvests. Research has been accelerated to overcome the practical challenges of this method, as seen in works using model update algorithms, online classification systems, and real-time classification maps. Thus, there are strong indications that the application of multispectral image analysis will reach the routine of seed analysis laboratories.

Phenolic Constituents, Antioxidant and Antimicrobial Activity and Clustering Analysis of Propolis Samples Based on PCA from Different Regions of Anatolia.

This study aimed to evaluate the biochemical composition and biological activity of propolis samples from different regions of Türkiye to characterize and classify 24 Anatolian propolis samples according to their geographical origin. Chemometric techniques, namely, principal component analysis (PCA) and a hierarchical clustering algorithm (HCA), were applied for the first time to all data, including antioxidant capacity, individual phenolic constituents, and the antimicrobial activity of propolis to reveal the possible clustering of Anatolian propolis samples according to their geographical origin. As a result, the total phenolic content (TPC) of the propolis samples varied from 16.73 to 125.83 mg gallic acid equivalent per gram (GAE/g) sample, while the number of total flavonoids varied from 57.98 to 327.38 mg quercetin equivalent per gram (QE/g) sample. The identified constituents of propolis were phenolic/aromatic acids (chlorogenic acid, caffeic acid, p-coumaric acid, ferulic acid, and trans-cinnamic acid), phenolic aldehyde (vanillin), and flavonoids (pinocembrin, kaempferol, pinobanksin, and apigenin). This study has shown that the application of the PCA chemometric method to the biochemical composition and biological activity of propolis allows for the successful clustering of Anatolian propolis samples from different regions of Türkiye, except for samples from the Black Sea region.

Combination of Total-Reflection X-Ray Fluorescence Method and Chemometric Techniques for Provenance Study of Archaeological Ceramics.

The provenance study of archaeological materials is an important step in understanding the cultural and economic life of ancient human communities. One of the most popular approaches in provenance studies is to obtain the chemical composition of material and process it with chemometric methods. In this paper, we describe a combination of the total-reflection X-ray fluorescence (TXRF) method and chemometric techniques (PCA, k-means cluster analysis, and SVM) to study Neolithic ceramic samples from eastern Siberia (Baikal region). A database of ceramic samples was created and included 10 elements/indicators for classification by geographical origin and ornamentation type. This study shows that PCA cannot be used as the primary method for provenance purposes, but can show some patterns in the data. SVM and k-means cluster analysis classified most of the ceramic samples by archaeological site and type with high accuracy. The application of chemometric techniques also showed the similarity of some samples found at sites located close to each other. A database created and processed by SVM or k-means cluster analysis methods can be supplemented with new samples and automatically classified.

Characterizing Spray-Dried Powders through NIR Spectroscopy: Effect of Two Preparation Strategies for Calibration Samples and Comparison of Two Types of NIR Spectrometers.

Emerging portable near infrared (NIR) spectroscopic approaches coupled with data analysis and chemometric techniques provide opportunities for the rapid characterization of spray-dried products and process optimization. This study aimed to enhance the understanding of applying NIR spectroscopy in spray-dried samples by comparing two sample preparation strategies and two spectrometers. Two sets of whey protein-maltodextrin matrixes, one with a protein content gradient and one with a consistent protein content, were spray-dried, and the effect of the two preparation strategies on NIR calibration model development was studied. Secondly, a portable NIR spectrometer (PEAK) was compared with a benchtop NIR spectrometer (CARY) for the moisture analysis of prepared samples. When validating models with the samples with focused protein contents, the best PLS protein models established from the two sample sets had similar performances. When comparing two spectrometers, although CARY outperformed PEAK, PEAK still demonstrated reliable performance for moisture analysis, indicating that it is capable as an inline sensor.

Non-destructive detection of kiwifruit soluble solid content based on hyperspectral and fluorescence spectral imaging.

The soluble solid content (SSC) is one of the important parameters depicting the quality, maturity and taste of fruits. This study explored hyperspectral imaging (HSI) and fluorescence spectral imaging (FSI) techniques, as well as suitable chemometric techniques to predict the SSC in kiwifruit. 90 kiwifruit samples were divided into 70 calibration sets and 20 prediction sets. The hyperspectral images of samples in the spectral range of 387 nm~1034 nm and the fluorescence spectral images in the spectral range of 400 nm~1000 nm were collected, and their regions of interest were extracted. Six spectral pre-processing techniques were used to pre-process the two spectral data, and the best pre-processing method was selected after comparing it with the predicted results. Then, five primary and three secondary feature extraction algorithms were used to extract feature variables from the pre-processed spectral data. Subsequently, three regression prediction models, i.e., the extreme learning machines (ELM), the partial least squares regression (PLSR) and the particle swarm optimization - least square support vector machine (PSO-LSSVM), were established. The prediction results were analyzed and compared further. MASS-Boss-ELM, based on fluorescence spectral imaging technique, exhibited the best prediction performance for the kiwifruit SSC, with the , and RPD of 0.8894, 0.9429 and 2.88, respectively. MASS-Boss-PLSR based on the hyperspectral imaging technique showed a slightly lower prediction performance, with the , , and RPD of 0.8717, 0.8747, and 2.89, respectively. The outcome presents that the two spectral imaging techniques are suitable for the non-destructive prediction of fruit quality. Among them, the FSI technology illustrates better prediction, providing technical support for the non-destructive detection of intrinsic fruit quality.

Classification and authentication of spices and aromatic herbs by means of HPLC-UV and chemometrics

Recent increase in the adulteration of spices and aromatic herbs in food industry constitutes a problem that requires exhaustive quality control. As every spice has a different composition with characteristic biomarkers, chromatographic profiles are especially valuable to authenticate these products. Thus, in this work a new high performance liquid chromatography (HPLC) method with UV–vis detection was developed for the characterization, identification and authentication of cinnamon, oregano, thyme, sesame, bay leaf, clove, cumin, and vanilla. Chromatographic separation was optimized based on the separation of six characteristic biomarkers (sesamol, eugenol, thymol, carvacrol, salicylaldehyde and vainillin) and was performed using a C18 reversed-phase column under a 35 min gradient elution based on 0.1% (v/v) formic aqueous solution and methanol by means of UV–Vis detection at 280 nm. 87 samples, purchased in local supermarkets, were analyzed and the obtained profiles were processed by chemometric techniques. First, data treatment was evaluated by principal component analysis (PCA); next soft independent modelling by class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) were carried out in order to verify if classification according to their biomarkers was possible. The study concluded that PLS-DA (0.14–0.75% global error) classifies better the types of spice or aromatic herb than SIMCA (0.82–3.67% global error).

Chemometric Methods for Simultaneous Determination of Candesartan Cilexetil and Hydrochlorothiazide in Binary Combinations.

Simple, accurate, precise, and cost-effective chemometric techniques for the measurement of candesartan cilexetil and hydrochlorothiazide in synthetic mixtures were improved and validated. H-point standard addition, Q-absorption ratio, and correction absorbance spectrophotometric techniques were utilized for the simultaneous determination of both medicines in real pharmaceutical formulations. A new calibration approach was implemented based on chemical H-point standards. This approach was developed to resolve significantly overlapping spectra of two analytes and provide direct correction of both proportional and constant errors caused by the matrix of the sample. The first method of simultaneous determination of candesartan cilexetil and hydrochlorothiazide was carried out using the H-point standard addition method at wavelengths 239 and 283. For the ratio of the absorption at two selected wavelengths, one of which is the isoabsorptive point and the other being the maximum of one of the two components, the second method absorption ratio method was utilized. In distilled water, the isoabsorptive point of candesartan cilexetil and hydrochlorothiazide occurs at 258 nm. λ max of hydrochlorothiazide is 273 nm, which is the second wavelength used. Lastly, the absorbance correction method was implemented. This approach is based on absorbance correction equations and uses distilled water as the solvent for the examination of both medicines. In NaOH/EtOH solvent, the absorbance maxima of candesartan cilexetil and hydrochlorothiazide are 250 nm and 340 nm, respectively. For both wavelengths, candesartan cilexetil and hydrochlorothiazide exhibited linearity over a concentration range of 1-46 μg/ml and 1-44 μg/ml, respectively, for H-point standard addition. The Q-absorption ratio approach provides linearity over the concentration ranges of 1-46 μg/ml at 273 nm for candesartan cilexetil and 1-29 μg/ml for hydrochlorothiazide, 1-46 μg/ml at 258 nm for candesartan cilexetil, and 1-44 μg/ml for hydrochlorothiazide. For hydrochlorothiazide, the linearity for the correction absorbance method was obtained throughout a concentration range of 1-46 μg/ml at wavelengths 250 and 340 nm and 1-44 μg/ml at wavelength 250 nm. The results of the analysis have been statistically and empirically supported by recovery studies. All methods yielded recoveries in the range of 96 -102% for both medications. The LOD ranged from 0.46 -0.94 μg/mL for hydrochlorothiazide and from 1.26 -2.40 μg/mL for candesartan cilexetil. The approaches were then used to quantify candesartan cilexetil and hydrochlorothiazide in pharmaceutical tablets.

Spectroscopic, Chromatographic, and Chemometric Techniques Applied in Food Products Characterization

Spectroscopy is a technique indispensable for evaluating the quality of foods [...]

Identification and highly selective differentiation of organic gunshot residues utilizing their elemental and molecular signatures

Firearm related evidence is of great significance to forensic science. In recent years, many researchers have focused on exploring the probative value of organic gunshot residue (OGSR) evidence, which is often bolstered by many factors including recoverability. In addition, OGSR analysis has shown the potential to achieve differentiation between OGSRs generated from various ammunition brands and/or calibers. Raman spectroscopy is a vibrational spectroscopic technique which has been used in the past for gunshot residue analysis—including OGSR specifically. Raman spectroscopy is a nondestructive, highly-selective, simple, and rapid technique which provides molecular information about samples. LIBS or Laser-Induced Breakdown Spectroscopy is a simple, robust, and rapid analytical method which requires minimal to no sample preparation and a small amount of sample for analysis. LIBS provides information on the elemental compositions of samples.In this study, Raman spectroscopy and LIBS were used together in sequence in an attempt to achieve the specific identification and characterization of OGSR particles from ammunition types which were closely related. The main goal was to determine if this method had the potential to differentiate between various ammunition types of the same caliber and produced by the same manufacturer, and generated under identical firing conditions. High-resolution optical microscopy documented the OGSR particles’ morphologies and Raman spectroscopy was used to identify particles as OGSRs. Finally, LIBS analysis of the OGSR particles was carried out. Advanced chemometric techniques were shown to allow for very successful differentiation between the OGSR samples analyzed.

Development and validation of a new spectrophotometric method for simultaneous determination of sitagliptin and metformin hydrochloride in tablet pharmaceutical dosage forms using chemometrics technique in comparison with HPLC

A new, quick, easy, affordable and eco-friendly simultaneous spectrophotometric method for determining a combined sitagliptin and metformin hydrochloride in pharmaceutical formulations was developed and validated using two chemometrics technique. These two methods are the partial least square (PLS) and principal component regression (PCR). They do not need to do a sample preparation or separation before analysis. Various drug concentrations and instrumental spectra of 25 mixed solutions of a combination of sitagliptin and metformin hydrochloride were used for model construction in the range of 200�270 nm. The R2 values of 0.9994 and 0.9996 assigned for the PLS of the sitagliptin and metformin hydrochloride and that of 0.9987 and 0.9996 for the PCR of the sitagliptin and metformin hydrochloride, respectively. It is noteworthy that these two models were successfully and effectively used with the commercial pharmaceutical formulations. Finally, the statistical comparison revealed no significant differences with the results of the HPLC reference method. The proposed method is dependable to be adopted as an alternative analytical method in the pharmaceutical industry�s quality control.

Nanoplastika u vodenoj sredini - poreklo, separacija i karakterizacija - pregled

Scientists discovered plastic in the early 1900s, but didn't realize the detrimental effects its fragmentation could have on the environment 100 years later. In particular, nanoplastics (NPs) particles ranging in size from 1 to 100 nm can cause major problems in the living world due to their high specific surface area for the adsorption other polluting substances from water, and their further bioaccumulation through the food chain. There is no distinctive method to identify, characterize, and quantify nanoplastics in aquatic environments. Although many of the methods developed to study microplastics are not directly applicable to nanoplastics, conventional methods of characterizing nanoplastics are usually tedious because they study individual nanoparticles in isolation. Since nanoplastics resulting from the decomposition of microplastics have different properties than engineering plastic nanoparticles, new techniques need to be developed to help us better understand the seriousness of the nanoplastic problem. Nanoplastic can be isolated from the water environment by a combination of filters and ultracentrifugation. A recent publications states that combining microscopy and spectroscopy, supported by chemometric techniques, will alow a better understand he behavior of nanoplastic particles in the environment and organisms. High hopes are placed on microscopies combined with neural networks for the quantification and characterization of nanoplastics in complex systems. This article describes the degradation pathways of plastics and the formation of nanoplastics in aquatic environments, and possible methods for separation and characterization of nanoplastics in relation to recent publications.

Evaluation of Extraction Parameters for the Analysis of Lipid Classes in Plants

The aim of this study was to preliminary evaluate the lipid profile alterations on Pitcairnia flammea leaves based on variations in solvent proportion and ultrasonic ice bath extraction time, followed by a lipid class-enriched analysis employing chemometric techniques. Ultra-high performance liquid chromatography coupled to electrospray ionization mass spectrometry (UHPLC-ESI-MS) was used to acquire raw data and MS-DIAL and MetaboAnalyst platforms were used to perform data preprocessing and statistical analysis. The statistical analysis of UHPLC-ESI-MS data in both ionization modes enabled the visualization of a trend distribution based on extraction time. Furthermore, we were able to establish that the solvent proportion had a greater impact on group separation in data samples extracted for 30 min versus 10 and 20 min. Moreover, diacylglycerol or/and lysophosphatidylcholine are lipid subclasses that can be favored depending on the extraction time in the mass spectrometry analyses using positive electrospray ionization mode.