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Prosopis cineraria is a medicinal plant known for its rich flavonoid content, which plays a vital role in its pharmacological activities, including antioxidant, anti-inflammatory, and antimicrobial properties . This study aimed to analyze the flavonoid profile of P. cineraria leaves using High-Performance Thin-Layer Chromatography (HPTLC) combined with chemometric techniques. The methanolic leaf extracts were prepared and subjected to HPTLC for the separation and identification of flavonoid compounds. Chemometric analysis was employed to improve compound differentiation and quantification. The results provided valuable insights into the diverse flavonoid composition of P. cineraria, highlighting its potential for pharmaceutical and nutraceutical applications. This study contributes to the standardization and quality control of herbal formulations containing P. cineraria extracts.

The food products may attract unscrupulous vendors to dilute it with inexpensive alternative food sources to achieve more profit. The risk of high value food adulteration with cheaper substitutes has reached an alarming stage in recent years. Commonly available detection methods for food adulteration are costly, time consuming and requires high degree of technical expertise. However, a rapid and suitable detection method for possible adulterant is being evolved to tackle the aforesaid issues. In recent years, electronic nose (e-nose) system is being evolved for falsification detection of food products with reliable and rapid way. E-nose has the ability to artificially perceive aroma and distinguish them. The use of chemometric analysis together with gas sensor arrays have shown to be a significant procedure for quality monitoring in food. E-nose techniques with numerous provisions are reliable and favourable for food industry in food fraud detection. In the present review, the contributions of gas sensor based e-nose system are discussed extensively with a view to ascertain the adulteration of food products.

Knowledge about the metal content of wine is very important, for many reasons. Depending on the element, its quantity varies in wine from ng/L to mg/L. Despite the fact that metals are not directly connected to the taste and aroma of the wine, their content should be determined and controlled, because excess is undesirable, and in some cases prohibited, due to potential toxicity. Several analytical procedures for metal determination are applied. However, due to sensitivity, low limit of detection and speed of analysis, inductively coupled plasma-mass spectrometry (ICP-MS) is one of the most frequently used techniques. The aim of this study was to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines according to their metal content by application of chemometric analysis. For metals content determination, two techniques, ICP-MS and inductively coupled plasma-optical emission spectrometry (ICP-OES), were applied. Data obtained showed that none of the wine samples surpassed the toxic levels reported for metals in the literature, thus, these wines appeared to be safe as regards the risk associated with the potentially toxic metals intake. However, specific correlations between metals and specific aspects of the wines themselves have been found.

The continuous deterioration of drinking water quality supplies by several anthropogenic activities is a serious global challenge in recent times. In this current study, the drinking water quality of Ikem rural agricultural area (southeastern Nigeria) was assessed using chemometrics and multiple indexical methods. Twenty-five groundwater samples were collected from hand-dug wells and analyzed for physicochemical parameters such as pH, major ions, and heavy metals. The pH of the samples (which ranged between 5.2 and 6.7) indicated that waters were slightly acidic. Cations and anions (except for phosphate) were within their respective standard limits. Except for Mn, heavy metals were also found to be below their maximum allowable limits. Factor analysis identified both geogenic processes and anthropogenic inputs as possible origins of the analyzed physicochemical parameters. Modified heavy metal index, geoaccumulation index, and overall index of pollution revealed that all the hand-dug wells were in excellent condition, and hence safe for drinking purposes. However, pollution load index, water quality index (WQI), and entropy-weighted water quality index (EWQI) revealed that some wells (about 8–12%) were slightly contaminated, and hence are placed in good water category. A hierarchical cluster analysis (HCA) was performed based on the integration of the WQI and EWQI results. The HCA revealed two major quality categories of the samples. While the first cluster comprises of samples classified as excellent drinking water by both WQI and EWQI models, the second cluster comprises of about 12% samples which were identified as good water by either the WQI or EWQI.

Near-infrared spectroscopy (NIRS) has become a more popular approach for quantitative and qualitative analysis of feeds, foods and medicine in conjunction with an arsenal of chemometric tools. This was the foundation for the increased importance of NIRS in other fields, like genetics and transgenic monitoring. A considerable number of studies have utilized NIRS for the effective identification and discrimination of plants and foods, especially for the identification of genetically modified crops. Few previous reviews have elaborated on the applications of NIRS in agriculture and food, but there is no comprehensive review that compares the use of NIRS in the detection of genetically modified organisms (GMOs). This is particularly important because, in comparison to previous technologies such as PCR and ELISA, NIRS offers several advantages, such as speed (eliminating time-consuming procedures), non-destructive/non-invasive analysis, and is inexpensive in terms of cost and maintenance. More importantly, this technique has the potential to measure multiple quality components in GMOs with reliable accuracy. In this review, we brief about the fundamentals and versatile applications of NIRS for the effective identification of GMOs in the agricultural and food systems.

Elevated levels of trace metals (TMs) and heavy/non-essential metals (HnMs) in commonly consumed beverages concern the public and regulatory agencies. Thus, frequent monitoring of these metals is critically important. The present study intended to assess TMs and HnMs concentrations and associated health risks in beverages. Ten metals, such as Mn, Co, Cr, Cu, and Zn (TMs) and Ni, Cd, Pb, Al, and As (HnMs), were quantified in different beverage brands categorized into two groups such as non-carbonated and carbonated beverages. Chemometric analysis such as hierarchical cluster analysis (HCA), Pearson’s correlation coefficient (PCC), and principal component analysis (PCA) were also performed to demonstrate the possible natural and anthropogenic sources of metal contamination. Among the TMs, the mean concentration of Zn (233.3 ± 3.3–291.7 ± 3.2 µg/L) followed by Mn (119.0 ± 2.3–146.4 ± 2.2 µg/L) was found highest in both carbonated and non-carbonated beverage samples. In the case of HnMs, the lowest mean concentration of Cd (7.4 ± 0.9–18.6 ± 1.2 µg/L) followed by Pb (4.1 ± 0.4–4.5 ± 0.4 µg/L) was observed in both types of beverage samples. The tolerable dietary intake (TDI) value for Ni and provisional tolerable monthly intake (PTMI) value for Cd were higher than the value established by the WHO and EFSA. The computed values of the hazard index (HI < 1) and the cumulative cancer risk (CCR) indicated a low risk of exposure.

The objective of this study was to assess the antioxidant activity and phenolic compounds of bee bread samples obtained from various regions in Türkiye The goal was to characterize and classify 15 of bee bread samples based on their geographical origins. This investigation employed chemometric techniques, specifically principal component analysis (PCA) and a hierarchical clustering algorithm (HCA), for the inaugural comprehensive analysis of all data encompassing antioxidant activity and phenolic compounds in bee bread. The primary objective was to unveil potential clustering patterns among of bee bread samples based on their geographical origins. According to the results, the Total Phenolic Content (TPC) of bee bread samples ranged from 4.393 to 14.917 mg GAE/g dw, while the Total Flavonoid Content (TFC) exhibited variation within the range of 0.681 to 3.504 mg QE/g dw. p-OH benzoic and p-coumaric acids were detected in all samples. Other phenolic compounds were identified in different proportions among the bee bread samples. This study demonstrated the successful application of the PCA chemometric method to assess the antioxidant activity and phenolic compounds of bee bread samples from various regions of Türkiye. The results revealed effective clustering of the bee bread samples based on their geographical origins.

Seven amidrazones containing a characteristic NH[sub.2]–N=C(Ar[sup.1])–NHAr[sup.2] moiety, where Ar[sup.1], Ar[sup.2] are phenyl, 4-methylphenyl, 4-nitrophenyl, 2-pyridyl, and 4-pyridyl substituents, denoted as 2a–2g, were synthesized by the reactions between thioamides and hydrazine. Their molecular structures were confirmed by [sup.1]H, [sup.13]C, [sup.1]H-[sup.13]C HMQC, [sup.1]H-[sup.13]C HMBC, and [sup.1]H-[sup.15]N HMBC NMR spectroscopy, with complete assignment of the detected signals, as well as by high-resolution mass spectra. The biological activity of all compounds was studied, exhibiting antioxidant properties determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) methods, inhibitory potential against digestive tract enzymes (α-amylase, lipase, pepsin), cytotoxicity (hemolysis), and antimicrobial activities (against Gram-positive and Gram-negative bacteria, and a fungus). The antioxidant activity of the studied amidrazones varied from 83.34% to 93.27% and 1.01–5.79 mM FeSO[sub.4] for the DPPH and FRAP methods, respectively. Moreover, these derivatives revealed inhibition potential against α-amylase (28.6–86.8%), lipase (28.0–60.0%), and pepsin (34.1–76.6%), which increased when increasing their concentrations from 0.2 to 1 mg/mL. Among them, compound 2d (possessing 2-pyridyl and 4-nitrophenyl substituents) stood out in particular, as a potent antioxidant (DPPH = 90.43%, FRAP = 4.73 Mm FeSO[sub.4]) with the highest activity against Gram-positive bacteria: S. aureus (MIC = 64 μg/mL), G. rubripertincta (MIC = 64 μg/mL), and fungus: C. albicans (MIC = 32 μg/mL); high α-amylase (86.8%) inhibition at the highest concentration (1 mg/mL); and lipase (38.0%) and pepsin (43.8%) inhibition at the lowest concentration (0.2 mg/mL). The obtained results were analyzed by unsupervised multivariate techniques to confirm significant differences in the biological activity of amidrazones depending on the Ar[sup.1] and Ar[sup.2] substituents.

This study investigated the dose-dependent effects of γ-irradiation (0-20 kGy) on caraway seed oil. Samples were analysed using GC-MS and GC-FID, tested against six microorganisms using agar diffusion assays, and evaluated by molecular docking analysis. Chemical analyses revealed marked compositional changes. At 5 kGy, saturated fatty acids increased from 32.27% to 63.08%, accompanied by a decline in unsaturated fractions, while limonene exhibited a transient increase to 26.82%. At higher doses (10-20 kGy), the volatile profile shifted, with carvone dominating (75.71-76.85%) and increased relative levels of oxygenated monoterpenes such as dihydrocarvone and limonene oxides. Antimicrobial activity varied with irradiation dose. Gram-positive bacteria (Bacillus cereus and Staphylococcus aureus) were highly susceptible, showing inhibition zones up to 30.33 mm and 29.67 mm, respectively. Gram-negative bacteria exhibited reduced inhibition at 5 kGy but increased responses at higher doses, with Escherichia coli inhibition reaching 24.67 mm. Fungal strains showed limited inhibition with non-irradiated oil at lower concentrations, whereas irradiation at 10-20 kGy produced measurable inhibition zones ranging from 13 to 26 mm. Multivariate analysis associated the 5 kGy dose with altered fatty acid patterns and weaker antimicrobial responses, while treatments at 10-20 kGy correlated with oxygenated volatile constituents and stronger inhibitory effects. Molecular docking analysis was consistent with these trends, indicating more favorable interactions of carvone compared with limonene across selected microbial targets. Overall, γ-irradiation alters caraway seed oil chemistry in a dose-dependent manner, with higher doses associated with increased oxygenated volatiles and enhanced antimicrobial activity under the conditions of the assay.

Fourier transform infrared spectroscopy (FTIR) in connection with chemometric analysis were used as a fast and direct approach to classify spray dried honey powder compositions in terms of honey content, the type of diluent (water or skim milk), and carrier (maltodextrin or skim milk powder) used for the preparation of feed solutions before spray drying. Eleven variants of honey powders containing different amounts of honey, the type of carrier, and the diluent were investigated and compared to pure honey and carrier materials. Chemometric discrimination of samples was achieved by principal component analysis (PCA), hierarchical clustering analysis (HCA), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA) modelling procedures performed on the FTIR preprocessed spectral data for the fingerprint region (1800–750 cm−1) and the extended region (3600–750 cm−1). As a result, it was noticed that the type of carrier is a significant factor during the classification of different samples of powdered multifloral honey. PCA divided the samples based on the type of carrier, and additionally among maltodextrin-honey powders it was possible to distinguish the type of diluent. The result obtained by PCA-LDA and PLS-DA scores yielded a clear separation between four classes of samples and showed a very good discrimination between the different honey powder with a 100.0% correct overall classification rate of the samples.