Spectroscopy NIR and MIR toward predicting simultaneous phenolic contents and antioxidant in red propolis by multivariate analysis

Data fusion of near-infrared and mid-infrared spectroscopy for rapid origin identification and quality evaluation of Lonicerae japonicae flos

A data fusion strategy based on near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques were developed for rapid origin identification and quality evaluation of Lonicerae japonicae flos (LJF). A high-level data fusion for origin identification was formed using the soft voting method. This data fusion model achieved accuracy, log-loss value and Kappa value of 95.5%, 0.347 and 0.910 on the prediction set. The spectral data were converted to liquid chromatography data using a data fusion model constructed by the weighted average algorithm. The Euclidean distance and adjusted cosine similarity were used to evaluate the similarity between the converted and the real chromatographic data, with results of 247.990 and 0.996, respectively. The data fusion models all performed better than the models constructed using single data. This indicates that multispectral data fusion techniques have a wide range of application prospects and practical value in the quality control of natural products such as LJF.

Analysis of Chemical Changes during Maturation of Amomum tsao-ko Based on GC-MS, FT-NIR, and FT-MIR

Amomum tsao-ko Crevost et Lemaire (A. tsao-ko) is widely grown for its high nutritional and economic value. However, the lack of a scientific harvesting and quality control system has resulted in an uneven product quality. The present study was based on A. tsao-ko from four maturity stages from the same growing area, and its chemical trends and quality were evaluated using a combination of agronomic trait analysis, spectroscopy, chromatography, chemometrics, and network pharmacology. The results showed that A. tsao-ko was phenotypically dominant in October. Spectroscopy showed that the absorbance intensity at different maturity stages showed a trend of October > September > August > July. Further chemical differences between A. tsao-ko at different stages of maturity were found by chromatography to originate mainly from alcohol, aromatic, acids, esters, hydrocarbons, ketone, heterocyclic, and aldehydes. The network pharmacology results showed that the active ingredient for the treatment of obesity was present in A. tsao-ko and had high levels in A. tsao-ko in September and October. The results of this study provide a new idea for the comprehensive evaluation of A. tsao-ko and a theoretical basis for the harvesting and resource utilization of A. tsao-ko.

Effect of Adding Red Propolis to Edible Biodegradable Protein Films for Coating Grapes: Shelf Life and Sensory Analysis

Red propolis is an active ingredient of great nutritional interest which offers numerous benefits as an antioxidant and antimicrobial agent. Thus, the objective of this research was to evaluate the application of an edible and antimicrobial gelatine coating containing red propolis to increase the shelf life of grapes. Gelatine films with an addition of 5, 10, 15, 20 and 25% of red propolis extract were produced to evaluate their antimicrobial activity using the disk diffusion test in solid media. The films with 25% red propolis extract showed antimicrobial activity against the bacteria Staphylococcus aureus and Pseudomonas aeruginosa. The grapes were coated with pure gelatine, without a plasticizer and with gelatine with 25% red propolis and then stored for 1, 4, 10, 19 and 25 days at temperatures of 25 °C and 5 °C. The results showed that the gelatine coating with propolis reduced the mass loss of grapes stored at 25 °C for 19 days by 7.82% and by 21.20% for those kept at 5 °C for 25 days. The pH, total titratable acidity, soluble solids and color of the grapes increased due to the ripening process. Furthermore, the sensory acceptability indexes of the refrigerated grapes with coatings were superior (>78%) to those of the control samples (38%), proving the effectiveness of the coatings in maintaining the quality of grapes during storage.

Potential Antidiabetic Activity of Apis mellifera Propolis Extraction Obtained with Ultrasound

Recent studies have linked phenolic compounds to the inhibition of digestive enzymes. Propolis extract is consumed or applied as a traditional treatment for some diseases. More than 500 chemical compounds have been identified in propolis composition worldwide. This research aimed to determine Mexican propolis extracts' total phenolic content, total flavonoid content, antioxidant activity, and digestive enzyme inhibitory activity (ɑ-amylase and ɑ-glucosidase). In vitro assays measured the possible effect on bioactive compounds after digestion. Four samples of propolis from different regions of the state of Oaxaca (Mexico) were tested (Eloxochitlán (PE), Teotitlán (PT), San Pedro (PSP), and San Jerónimo (PSJ)). Ethanol extractions were performed using ultrasound. The extract with the highest phenolic content was PE with 15,362.4 ± 225 mg GAE/100 g. Regarding the flavonoid content, the highest amount was found in PT with 8084.6 ± 19 mg QE/100 g. ABTS•+ and DPPH• radicals were evaluated. The extract with the best inhibition concentration was PE with 33,307.1 ± 567 mg ET/100 g. After simulated digestion, phenolics, flavonoids, and antioxidant activity decreased by 96%. In contrast, antidiabetic activity, quantified as inhibition of ɑ-amylase and ɑ-glucosidase, showed a mean decrease in enzyme activity of approximately 50% after the intestinal phase. Therefore, it is concluded that propolis extracts could be a natural alternative for treating diabetes, and it would be necessary to develop a protective mechanism to incorporate them into foods.

A rapid extraction process monitoring of Swertia mussotii Franch. With near infrared spectroscopy

Swertia mussotii Franch. (SMF), a traditional Tibetan medicine, which has miraculous effect on treating hepatitis diseases. However, there is no research on its entire production process, and invisible production process has seriously hindered the SMF modern development. In this study, principal component analysis (PCA), subtractive spectroscopy, and two-dimensional correlation spectroscopy (2D-COS) were used to explain changes of characteristic groups in the extraction process. Four main characteristic peaks at 1884 nm, 1944 nm, 2246 nm and 2308 nm were identified to describe the changes of molecular structure information of total active components in SMF extraction process. In addition, multi critical quality attributes (CQAs) models were established by near-infrared spectroscopy (NIRS) combined with the total quantum statistical moment (TQSM). The coefficients of determination (R²_eval and R²_ival) were both greater than 0.99. The ratios of the standard deviation of validation to the standard error of the prediction (RPD_e and RPD_i) were greater than five. The quantitative model of AUC_T could save time on primary data measurement by not requiring determination of indicator components compared with others. In conclusion, these results demonstrated that it was feasible to understand the SMF extraction process through AUC_T and characteristic groups. These could realize the visual digital characterization and quality stability of the SMF extraction process.

Multivariate analysis of seed chemical diversity among wild fenugreek (Trigonella monantha C. A. Mey.) ecotypes

BACKGROUND

Wild fenugreek (Trigonella monantha), a multi-purpose annual plant, has traditionally been used as a food, forage, and medicinal plant. However, the knowledge of the diversity of its chemical characteristics is limited. In this study, 40 wild fenugreek ecotypes collected from their natural habitats in Iran and grown together in field conditions, were analyzed for their seed chemical properties.

RESULTS

The ecotypes were cultivated in a randomized complete block design (RCBD) with three replications. The results of ANOVA revealed a significant difference among the ecotypes for all measured characters (P < 0.01). The results showed a high level of diversity among the ecotypes based on the measured characters, including antioxidant activity (48.19 to 86.85%), phenol (0.82 to 1.51 mg gallic acid per g dry weight), flavonoid (1.07 to 3.11 mg quercetin per g dry weight), trigonelline (0.02 to 0.08 mmol/l), 4-hydroxyisoleucine (0.197 to 0.906 mg/g), sucrose (0.13 to 3.77 mM), glucose (1.07 to 12.1 mM), and fructose (13.3 to 45.5 mM). The cluster analysis divided the ecotypes into four groups and the PCA analysis showed that the three first components explained 73% of the total variance among the ecotypes. Also, heat map correlation revealed that many positive and negative correlations were observed among the measured characters. The results did not show a relationship between the amounts of compounds and the place of sample collection.

CONCLUSIONS

The present study suggests considerable diversity in the seed chemical compositions of the wild fenugreek ecotypes. Therefore, many ecotypes could be useful for medicinal purposes, as well as for human nutrition.

Untargeted GC-MS and FT-NIR study of the effect of 14 processing methods on the volatile components of Polygonatum kingianum

Introduction

Polygonatum kingianum is a traditional medicinal plant, and processing has significantly impacts its quality.

Methods

Therefore, untargeted gas chromatography-mass spectrometry (GC-MS) and Fourier transform-near-infrared spectroscopy (FT-NIR) were used to analyze the 14 processing methods commonly used in the Chinese market.It is dedicated to analyzing the causes of major volatile metabolite changes and identifying signature volatile components for each processing method.

Results

The untargeted GC-MS technique identified a total of 333 metabolites. The relative content accounted for sugars (43%), acids (20%), amino acids (18%), nucleotides (6%), and esters (3%). The multiple steaming and roasting samples contained more sugars, nucleotides, esters and flavonoids but fewer amino acids. The sugars are predominantly monosaccharides or small molecular sugars, mainly due to polysaccharides depolymerization. The heat treatment reduces the amino acid content significantly, and the multiple steaming and roasting methods are not conducive to accumulating amino acids. The multiple steaming and roasting samples showed significant differences, as seen from principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on GC-MS and FT-NIR. The partial least squares discriminant analysis (PLS-DA) based on FT-NIR can achieve 96.43% identification rate for the processed samples.

Discussion

This study can provide some references and options for consumers, producers, and researchers.

Rapid evaluation of Radix Paeoniae Alba and its processed products by near-infrared spectroscopy combined with multivariate algorithms

It is well known that the processing method of herbal medicine has a complex impact on the active components and clinical efficacy, which is difficult to measure. As a representative herb medicine with diverse processing methods, Radix Paeoniae Alba (RPA) and its processed products differ greatly in clinical efficacy. However, in some cases, different processed products are confused for use in clinical practice. Therefore, it is necessary to strictly control the quality of RPA and its processed products. Giving that the time-consuming and laborious operation of traditional quality control methods, a comprehensive strategy of near-infrared (NIR) spectroscopy combined with multivariate algorithms was proposed. This strategy has the advantages of being rapid and non-destructive, not only qualitatively distinguishing RPA and various processed products but also enabling quantitative prediction of five bioactive components. Qualitatively, the subspace clustering algorithm successfully differentiated RPA and three processed products, with an accuracy rate of 97.1%; quantitatively, interval combination optimization (ICO), competitive adaptive reweighted sampling (CARS), and competitive adaptive reweighted sampling combined with successive projections algorithm (CARS-SPA) were used to optimize the PLS model, and satisfactory results were obtained in terms of wavelength selection. In conclusion, it is feasible to use NIR spectroscopy to rapidly evaluate the effect of processing methods on the quality of RPA, which provides a meaningful reference for quality control of other herbal medicines with numerous processing methods.

Electrochemical Methodologies for Investigating the Antioxidant Potential of Plant and Fruit Extracts: A Review

In recent years, the growing research interests in the applications of plant and fruit extracts (synthetic/stabilization materials for the nanomaterials, medicinal applications, functional foods, and nutraceuticals) have led to the development of new analytical techniques to be utilized for identifying numerous properties of these extracts. One of the main properties essential for the applicability of these plant extracts is the antioxidant capacity (AOC) that is conventionally determined by spectrophotometric techniques. Nowadays, electrochemical methodologies are emerging as alternative tools for quantifying this particular property of the extract. These methodologies address numerous drawbacks of the conventional spectroscopic approach, such as the utilization of expensive and hazardous solvents, extensive sample pre-treatment requirements, long reaction times, low sensitivity, etc. The electrochemical methodologies discussed in this review include cyclic voltammetry (CV), square wave voltammetry (SWV), differential pulse voltammetry (DPV), and chronoamperometry (CAP). This review presents a critical comparison between both the conventional and electrochemical approaches for the quantification of the parameter of AOC and discusses the numerous applications of the obtained bioextracts based on the AOC parameter.

Edible oils as a co-extractant for the supercritical carbon dioxide extraction of flavonoids from propolis

Propolis is a good source for flavonoids, however, their recovery is challenging, as it is a waxy material. This study investigated edible oils virgin coconut oil (VCO), corn oil (CO), and ghee (G) as co-extractants for the supercritical carbon dioxide (scCO₂) extraction of flavonoids from the propolis. The extraction of flavonoids using 20% VCO as co-extractant with scCO₂ (25 g/min) for 210 min at 150 bar and 50°C was found to be the most appropriate, yielding a total flavonoid content (TFC) of 11.7 mg/g and 25% TFC recovery. At a higher temperature (60°C) and pressure (250 bar and 350 bar), the propolis became softer and compressed causing the extractions to retrograde. The extraction curves correlated to the diffusion model with 1.6% (AARD). The matrix diffusivities increased from 4.7 × 10⁻¹¹ m²/s (scCO₂) to 6.9 × 10⁻¹¹–21.4 × 10⁻¹¹ m²/s upon the addition of edible oils. Thus, edible oils could be used with scCO₂ to improve the flavonoid extraction from propolis.