Determination of antioxidant capacity and phenolic content of chocolate by attenuated total reflectance-Fourier transformed-infrared spectroscopy

Rapid classification of Camellia seed varieties and non-destructive high-throughput quantitative analysis of fatty acids based on non-targeted fingerprint spectroscopy combined with chemometrics

Camellia oil is a high-quality vegetable oil rich in unsaturated fatty acids (FAs), with quality standardization challenged by the diversity of Camellia seed varieties. This study compared spectroscopy techniques (Near-Infrared [NIR] vs Mid-Infrared [MIR] spectroscopy) and analytical models (Discriminant Analysis [DA], Partial Least Squares [PLS], and Artificial Neural Networks [ANN]), seeking to classify Camellia seed varieties and estimate oil and principal FAs composition. The PCA analysis effectively discriminated among various Camellia seed varieties, likely due to variations in their oil and principal FAs compositions. Significantly, the NIR-based DA model significantly outperformed MIR, achieving 100 % accuracy in distinguishing Camellia seed varieties. In terms of predicting the oil and principal FAs compositions in Camellia seeds, NIR-based predictions models outperformed those derived from MIR, with PLS models surpassing ANN models. This study validated the potential of NIR technology combined with chemometrics for rapid, high-throughput, non-destructive identification of Camellia seeds.

Salinity as an Inducer of Antioxidant Activity Exerted by Mangrove Species from Campeche, Mexico

The mangrove ecosystem is reported to have a large diversity of species that develop in environments with high salinity levels. Plant species from mangroves are used in traditional medicine and are potential sources of chemicals entities with therapeutic applications. The present work aims to assess and document the influence of salinity on the antioxidant activity exerted by extracts of mangrove species through spectroscopic and chemical analysis. The highest salinity is recorded in Río Verde (RV) in Petén Neyac (PN), an LPBR site. The leaves of Laguncularia racemosa (from RV and PN) recorded the highest extraction yield (35.29 ± 0.45%). Phytochemical analysis indicated the presence of several families of secondary metabolites in the leaves of Rhizophora mangle, Avicennia germinans, and L. racemosa collected in PN and RV, and the chromatographic profile confirms the complexity of the extracts, especially in L. racemosa-RV. The highest content of chlorophylls, carotenoids, and simple phenols was recorded in R. mangle (in RV and PN); flavonoids were high in A. germinans (RV), and the highest antioxidant activity was recorded in L. racemosa (RV) using the DPPH model (EC50: 39.74 ± 0.91 μg/mL; Emax: 67.82 ± 1.00%). According to HPLC, gallic acid (GA), and quercetin (Q) are important metabolites in L. racemosa. FTIR spectra can identify several chemical groups and fingerprint regions in complex mixtures, such as methanolic extracts of the species under study. In this context, this is the first report on chemical changes resulting from species collected at sites with different degrees of salinity. GA is the main metabolite affected by salinity and participates in the antioxidant activity exerted by the original extract, which could explain the physiological adaptations of L. racemosa and its traditional uses. L. racemosa (RV) is ideal for a bioguided phytochemical study that would yield valuable knowledge about its medicinal properties, support ecological conservation, and drive innovation across multiple industries. Further analytical studies are needed to corroborate the impact of salinity on the biosynthesis of secondary metabolites.

Rapid determination of total phenolic content and antioxidant capacity of maple syrup using Raman spectroscopy and deep learning

Total phenolic content (TPC) and antioxidant capacity of maple syrup were determined using Raman spectroscopy and deep learning. TPC was determined by Folin-Ciocalteu assay, while the antioxidant capacity was measured by 2,2-diphenyl-1picrylhydrazyl (DPPH) assay, oxygen radical absorbance capacity (ORAC) assay, and ferric reducing antioxidant power (FRAP) assay. A total of 360 spectra were collected from 36 maple syrup samples of different colours (dark, amber, light) by both benchtop and portable Raman spectrometers. These spectra were used to establish predictive models for assessing the antioxidant profiles of maple syrup. Deep learning models developed along with portable Raman spectroscopy exhibited comparable predictive performance to those developed along with benchtop Raman spectroscopy. Base on the spectral dataset collected using portable Raman spectroscopy, the developed deep learning models exhibited low RMSEs (root mean square errors, 7.2-17.9 % of mean reference values), low MAEs (mean absolute errors, 5.2-13.1 % of mean reference values) and high R2 values (>0.88). The results showed a great goodness of fit and accuracy for predicting the antioxidant profiles of maple syrup, indicating the potential of using portable Raman spectrometer for on-site analysis of antioxidant profiles of maple syrup.

Determination of antioxidant capacity and phenolic content of haskap berries (Lonicera caerulea L.) by attenuated total reflectance-Fourier transformed-infrared spectroscopy

The total phenolic content (TPC) and antioxidant capacity (TAC) of haskap berries cultivated in various locations across Alberta were analyzed using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The Folin-Ciocalteu assay was used to determine TPC, while TAC was quantified by 2,2-diphenyl-1-picrylhydrazl radicals (DPPH) assay and oxygen radical absorbance capacity (ORAC) assay. Three tenfold cross-validated partial least-squares regression (PLSR) models and three fivefold cross-validated deep learning models were developed separately based on FT-IR spectra collected from 22 haskap berry samples and their corresponding reference values determined through Folin-Ciocalteu, DPPH, and ORAC assays. The deep learning models (R2 = 0.95, 0.93, and 0.90 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively) demonstrated better prediction capability compared to the PLSR models (R2 = 0.74, 0.72, and 0.66 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively). In addition, PLS loading plots indicated that phenolic contents and polysaccharides in haskap berries could contribute to their antioxidant capacity. Using ATR-FTIR to estimate the TPC and TAC of fruits offers a rapid alternative to the conventional chemical assays.

Concentrating Cocoa Polyphenols-Clarification of an Aqueous Cocoa Extract by Protein Precipitation and Filtration

The seeds of Theobroma cacao L. are rich in antioxidant flavonoids such as flavan-3-ols, which are valued for their health benefits. In this context, it is of interest to improve flavanol content in cocoa extracts. The present study aimed at improving the clarification process of an aqueous cocoa extract using protein precipitation and filtration. Five pH modifications and two bentonite amounts were tested for their effects on protein precipitation and flavanol content. Micro- and ultrafiltration as a subsequent step was done by testing three different ceramic membranes (30, 80, and 200 nm). Lower pH in pre-treatment reduced protein content and kept flavanols constant, while at higher pH, flavanols were reduced up to 40%. Larger membrane pores enhanced polyphenol permeation, while smaller pores limited protein permeation. Adjusting pH to the isoelectric point increased protein adsorption, improving filtration quality despite decreased permeate flux. However, membrane fouling results in higher permeate quality due to increased selectivity. Furthermore, the addition of bentonite during filtration reduced both protein and flavanol content in the permeate, similar to the effects seen in the pre-treatment of the supernatant. Optimizing pH and membrane pore size enhances the recovery and quality of polyphenols during filtration, balancing protein removal and flavanol retention.

In Situ Synthesis of Cu2O Nanoparticles Using Eucalyptus globulus Extract to Remove a Dye via Advanced Oxidation

Water pollution, particularly from organic contaminants like dyes, is a pressing issue, prompting exploration into advanced oxidation processes (AOPs) as potential solutions. This study focuses on synthesizing Cu2O on cellulose-based fabric using Eucalyptus globulus leaf extracts. The resulting catalysts effectively degraded methylene blue through photocatalysis under LED visible light and heterogeneous Fenton-like reactions with H2O2, demonstrating reusability. Mechanistic insights were gained through analyses of the extracts before and after Cu2O synthesis, revealing the role of phenolic compounds and reducing sugars in nanoparticle formation. Cu2O nanoparticles on cellulose-based fabric were characterized in terms of their morphology, structure, and bandgap via SEM-EDS, XRD, Raman, FTIR, UV-Vis DRS, and TGA. The degradation of methylene blue was pH-dependent; photocatalysis was more efficient at neutral pH due to hydroxyl and superoxide radical production, while Fenton-like reactions showed greater efficiency at acidic pH, primarily generating hydroxyl radicals. Cu2O used in Fenton-like reactions exhibited lower reusability compared to photocatalysis, suggesting deterioration. This research not only advances understanding of catalytic processes but also holds promise for sustainable water treatment solutions, contributing to environmental protection and resource conservation.

An approach to manufacturing well-being milk chocolate in partial replacement of lecithin by the functional plant-based combination

Lecithin is constituted of a glycerophospholipid mixture and is abundantly used as an emulsifying agent in various food applications including chocolate production. However, overconsumption of lecithin may create an adverse effect on human health. Thus, this study aims to replace the lecithin with plant-based gums. Different ratios of guar and arabic gum (25%-75%) and their blend (25%-75%) were employed as partial replacement of lecithin. Milk chocolate prepared using 40% guar gum (60GGL [guar gum, lecithin]), 25% arabic gum (75AGL [arabic gum, lecithin]), and a blend of 15 arabic gum and 10 guar gum (65AGGL [arabic gum, guar gum, lecithin]) showed similar rheological behavior as compared to control chocolate (100% lecithin). The fat content of 65AGGL (37.85%) was significantly lower than that of the control sample (43.37%). Rheological behavior exhibited shear-thinning behavior and samples (60GGL-75GGL-80GGL, 65AGL-75AGL, and 65AGGL-75AGGL) showed similar rheological properties as compared to control. The chocolate samples (60GGL and 65AGGL) showed significantly (p < .05) higher hardness values (86.01 and 83.55 N) than the control (79.95 N). As well, gum-added chocolates exhibited higher thermal stability up to 660°C as compared to the control sample. The Fourier transform infrared spectroscopy (FTIR) analysis revealed predominant β-(1 → 4) and β-(1 → 6) glycosidic linkages of the gums and lecithin. Sensory evaluation revealed a comparable score of gum-added milk chocolate in comparison to control samples in terms of taste, texture, color, and overall acceptance. Thus, plant exudate gums could be an excellent alternative to lecithin in milk chocolate, which can enhance the textural properties and shelf life.

Controlled-release hydrogel loaded with magnesium-based nanoflowers synergize immunomodulation and cartilage regeneration in tendon-bone healing

Tendon-bone interface injuries pose a significant challenge in tissue regeneration, necessitating innovative approaches. Hydrogels with integrated supportive features and controlled release of therapeutic agents have emerged as promising candidates for the treatment of such injuries. In this study, we aimed to develop a temperature-sensitive composite hydrogel capable of providing sustained release of magnesium ions (Mg2+). We synthesized magnesium-Procyanidin coordinated metal polyphenol nanoparticles (Mg-PC) through a self-assembly process and integrated them into a two-component hydrogel. The hydrogel was composed of dopamine-modified hyaluronic acid (Dop-HA) and F127. To ensure controlled release and mitigate the "burst release" effect of Mg2+, we covalently crosslinked the Mg-PC nanoparticles through coordination bonds with the catechol moiety within the hydrogel. This crosslinking strategy extended the release window of Mg2+ concentrations for up to 56 days. The resulting hydrogel (Mg-PC@Dop-HA/F127) exhibited favorable properties, including injectability, thermosensitivity and shape adaptability, making it suitable for injection and adaptation to irregularly shaped supraspinatus implantation sites. Furthermore, the hydrogel sustained the release of Mg2+ and Procyanidins, which attracted mesenchymal stem and progenitor cells, alleviated inflammation, and promoted macrophage polarization towards the M2 phenotype. Additionally, it enhanced collagen synthesis and mineralization, facilitating the repair of the tendon-bone interface. By incorporating multilevel metal phenolic networks (MPN) to control ion release, these hybridized hydrogels can be customized for various biomedical applications.

In vitro antibiofilm, antibacterial, antioxidant, and antitumor activities of the brown alga Padina pavonica biomass extract

The antibiofilm, antibacterial, antioxidant, and anticancer activities of the methanolic extract of Padina pavonica L. were determined. Results deduced that the algal extract had a high biofilm formation inhibitory action done via crystal violet (CV) assay, to 88-99%. The results showed a strong antibacterial against the identified bacteria species. Staphylococcus aureus, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumonia, Bacillus subtilis, and the extract had moderate antibacterial activity against Escherichia coli, Pseudomonas fluorescens and Streptococcus agalactiae. The algal extract has a concentration-dependent DPPH radical scavenging activity (84.59%, with IC50 = 170.31 µg/ml). The inhibitory percent of P. pavonica methanolic extract in vitro antiproliferative activity was 1.79-98.25% with IC50 = 15.14 µg/ml against lung carcinoma. Phenols, terpenes, amino acids, alkaloids, flavones, alcohols, and fatty acids were among the metabolites whose biological actions were evaluated. In conclusion, for the first time, P. pavonica methanolic extract exhibited effective antibiofilm, antibacterial, antioxidant, and anticancer activities.      .

Mycosynthesis of selenium nanoparticles using Penicillium tardochrysogenum as a therapeutic agent and their combination with infrared irradiation against Ehrlich carcinoma

Over the past years, the assessment of myco-fabricated selenium nanoparticles (SeNPs) properties, is still in its infancy. Herein, we have highly stable myco-synthesized SeNPs using molecularly identified soil-isolated fungus; Penicillium tardochrysogenum OR059437; (PeSeNPs) were clarified via TEM, EDX, UV-Vis spectrophotometer, FTIR and zeta potential. The therapeutic efficacy profile will be determined, these crystalline PeSeNPs were examined for antioxidant, antimicrobial, MIC, and anticancer potentials, indicating that, PeSeNPs have antioxidant activity of (IC50, 109.11 μg/mL) using DPPH free radical scavenging assay. Also, PeSeNPs possess antimicrobial potential against Penicillium italicum RCMB 001,018 (1) IMI 193,019, Methicillin-Resistant Staphylococcus aureus (MRSA) ATCC 4330 and Porphyromonas gingivalis RCMB 022,001 (1) EMCC 1699; with I.Z. diameters and MIC; 16 ± 0.5 mm and MIC 500 µg/ml, 11.9 ± 0.6 mm, 500 µg/ml and 15.9±0.6 mm, 1000 µg/ml, respectively. Additionally, TEM micrographs were taken for P. italicum treated with PeSeNPs, demonstrating the destruction of hyphal membrane and internal organelles integrity, pores formation, and cell death. PeSeNP alone in vivo and combined with a near-infrared physiotherapy lamp with an energy intensity of 140 mW/cm2 showed a strong therapeutic effect against cancer cells. Thus, PeSeNPs represent anticancer agents and a suitable photothermal option for treating different kinds of cancer cells with lower toxicity and higher efficiency than normal cells. The combination therapy showed a very large and significant reduction in tumor volume, the tumor cells showed large necrosis, shrank, and disappeared. There was also improvement in liver ultrastructure, liver enzymes, and histology, as well as renal function, urea, and creatinine.

The Use of Infrared Spectroscopy for the Quantification of Bioactive Compounds in Food: A Review

Infrared spectroscopy (wavelengths ranging from 750-25,000 nm) offers a rapid means of assessing the chemical composition of a wide range of sample types, both for qualitative and quantitative analyses. Its use in the food industry has increased significantly over the past five decades and it is now an accepted analytical technique for the routine analysis of certain analytes. Furthermore, it is commonly used for routine screening and quality control purposes in numerous industry settings, albeit not typically for the analysis of bioactive compounds. Using the Scopus database, a systematic search of literature of the five years between 2016 and 2020 identified 45 studies using near-infrared and 17 studies using mid-infrared spectroscopy for the quantification of bioactive compounds in food products. The most common bioactive compounds assessed were polyphenols, anthocyanins, carotenoids and ascorbic acid. Numerous factors affect the accuracy of the developed model, including the analyte class and concentration, matrix type, instrument geometry, wavelength selection and spectral processing/pre-processing methods. Additionally, only a few studies were validated on independently sourced samples. Nevertheless, the results demonstrate some promise of infrared spectroscopy for the rapid estimation of a wide range of bioactive compounds in food matrices.

Polyphenols in Jabuticaba (Plinia spp.) Peel Flours: Extraction and Comparative Evaluation of FTIR and HPLC for Quantification of Individual Compounds

Jabuticabas are wild fruits native to Brazil, and their peels, the main residue from jabuticaba processing, contain significant amounts of bioactive compounds, which are mostly phenolics. Conventional methods based on the estimation of total extractable phenolics (TEP—Folin–Ciocalteau) or total monomeric anthocyanins (TMA) have limitations and may not reflect the actual antioxidant potential of these peels. Analytical methods, such as high-performance liquid chromatography (HPLC), are more appropriate for the quantification of specific phenolics, and can be used as a reference for the construction of mathematical models in order to predict the amount of compounds using simple spectroscopic analysis, such as Fourier Transform Infrared Spectroscopy (FTIR). Therefore, the objectives of this study were (i) to evaluate the composition of specific polyphenols in flours prepared from jabuticaba peels and verify their correlation with TEP and TMA results from a previous study, and (ii) to employ FTIR coupled with chemometrics to predict the concentrations of these polyphenols in jabuticaba peel flours (JPFs) using HPLC as a reference method. Cyanidin-3-glucoside (C3G), ellagic acid (EA) and delphinidin-3-glucoside (D3G) were the main polyphenols found in the samples. The C3G contents ranged from 352.33 mg/100 g (S10) to 1008.73 mg/100 g (S22), with a strong correlation to TMA (r = 0.97; p = 0.00) and a moderate correlation to TEP (r = 0.45; p = 0.02). EA contents ranged from 163.65 mg/100 g (S23) to 334.69 mg/100 g (S11), with a moderate to strong correlation to TEP (r = 0.69; p = 0.00). The D3G values ranged from 94.99 mg/100 g (S10) to 203.36 mg/100 g (S5), with strong correlations to TMA (r = 0.91; p = 0.00) and C3G levels (r = 0.92; p = 0.00). The developed partial least squares-PLS models based on FTIR data provided satisfactory predictions of C3G and EA levels, reasonably matching those of HPLC.

Box-Behnken design based optimization of phenolic extractions from Polygonum equisetiforme roots linked to its antioxidant and antibacterial efficiencies

Purpose

The Polygonum equisetifome is a prospective plant source of high protein, unsaturated fatty acids, and useful safe bioactive molecules. Therefore, the aim of this study was to optimize the ultrasonic aqueous extraction of phenols from P. equisetifome roots using Box-Behnken design based statistical modeling, and to evaluate the antioxidant and antibacterial efficiencies of P. equisetifome root extracts against pathogenic bacteria.

Methods

In this study, the box-behnken design was used to optimize the extraction of phenols. The extraction temperature (30–70°C), ultrasound assisted extraction (UAE) time (1–9 min), and liquid-solid ratio (35–45 mL/g) were investigated as the factors that influence the phenolic yield (Y1) and their DPPH (1,1-diphenyl-2-picrylhydrazyl) scavenging activity (Y2).

Results

The optimal conditions for both responses were 50°C, 5 min, and 40 mL/g. At these conditions, Y1 reached its maximum to be 45.321 mg GAE/g dry weight and Y2 to be 120.354 μmol Trolox/g dry weight. The P. equisetifome roots contained water soluble phenol, high anthocyanin, and condensed tannins. Interestingly, the P. equisetifome extracts showed a relation to its antioxidant and antibacterial activities, FRAP (Ferric-reducing/antioxidant power), and ABTS scavenging activity were determined. The morphological and physico-chemical features of the extract were analyzed using SEM-EDX, FT-IR, and minimum inhibitory concentration (MIC) was analyzed against several pathogenic bacteria. The antibacterial activity of the extract showed that the extract is more efficient against Staphylococcus aureus, while the P. equisetifome extracts showed efficient MIC against S. aureus, followed by Bacillus cereus.

Suggestions

The relation of P. equisetifome extracts to its antioxidant, and antibacterial efficiencies open a new avenue of their potential uses in the food and pharmaceutical industries.

Analysis of White Mulberry Leaves and Dietary Supplements, ATR-FTIR Combined with Chemometrics for the Rapid Determination of 1-Deoxynojirimycin

Diabetes mellitus is a metabolic disease affecting more people every year. The treatment of diabetes and its complications involve substantial healthcare expenditures. Thus, there is a need to identify natural products that can be used as nutraceuticals to prevent and treat early-stage diabetes. White mulberry (Morus alba L.) is a plant that has been used in traditional Chinese medicine for thousands of years due to its many beneficial biological properties. White mulberry leaves are a source of 1-deoxynojirimycin (DNJ), which, due to its ability to inhibit α-glucosidase, can be used to regulate postprandial glucose concentration. In addition to consuming dried white mulberry leaves as herbal tea, many functional foods also contain this raw material. The development of the dietary supplements market brings many scientific and regulatory challenges to the safety, quality and effectiveness of such products containing concentrated amounts of nutraceuticals. In the present study, the quality of 19 products was assessed by determining the content of DNJ, selected (poly)phenols and antioxidant activity (DPPH^• assay). Nine of these products were herbal teas, and the other samples were dietary supplements. These results indicate the low quality of tested dietary supplements, the use of which (due to the low content of nutraceuticals) cannot bring the expected beneficial effects on health. Moreover, a method for determining the content of DNJ (the essential component for antidiabetic activity) based on ATR-FTIR spectroscopy combined with PLS regression has been proposed. This might be an alternative method to the commonly used chromatographic process requiring extraction and derivatization of the sample. It allows for a quick screening assessment of the quality of products containing white mulberry leaves.

Effects of Fermentation Periods and Drying Methods on Postharvest Quality of Cocoa (Theobroma Cacao) Beans in Ghana

Cocoa (Theobroma cacao) contributes significantly to Ghana’s GDP and has made Ghana a recognized leader in the cocoa industry. However, there are myriad problems associated with Ghana’s cocoa bean quality. One such problems stems from farmers paying less attention to the required postharvest activities (fermentation and drying) which contributes significantly to bean quality losses. This study investigated the effect of the duration of the traditional heap fermentation period and different drying methods: solar biomass hybrid dryer (SBHD) and traditional sun drying method (TSDM) on the bean quality of two cocoa varieties (hybrid cocoa and Amazonia). Quality attributes of cocoa beans such as pH, moisture content, fat content, crude protein, free fatty acids, phenolic contents, colour, and bean size were examined. The statgraphics statistical tool was used to analyse data and the least significant difference (LSD) was used to compare treatment means. Purple beans incidence was observed to be lower in hybrid with a value of 21.90% in the solar biomass hybrid dryer after 5 days of fermentation. Hybrid recorded the highest flavonoid value of 6069.74 mg QE/g DW in the traditional sun drying after 7 days of fermentation. Hybrid as well recorded the highest total phenolic value of 711.44 mg GAE/g DW in the solar biomass hybrid dryer under 5 days of fermentation. Results also indicated that using the solar biomass hybrid dryer resulted in the best moisture content removal and was very efficient compared with the traditional sun drying method in ensuring high-quality beans per international market standards. Cocoa beans dried under SBHD had the overall highest purity and were of better quality compared to those dried directly in the sun. There were no significant differences ( $p\le 0.24$ ) in percentage purity among the cocoa samples studied.

Uses of FT-MIR Spectroscopy and Multivariate Analysis in Quality Control of Coffee, Cocoa, and Commercially Important Spices

Nowadays, coffee, cocoa, and spices have broad applications in the food and pharmaceutical industries due to their organoleptic and nutraceutical properties, which have turned them into products of great commercial demand. Consequently, these products are susceptible to fraud and adulteration, especially those sold at high prices, such as saffron, vanilla, and turmeric. This situation represents a major problem for industries and consumers’ health. Implementing analytical techniques, i.e., Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with multivariate analysis, can ensure the authenticity and quality of these products since these provide unique information on food matrices. The present review addresses FT-MIR spectroscopy and multivariate analysis application on coffee, cocoa, and spices authentication and quality control, revealing their potential use and elucidating areas of opportunity for future research.

Bioavailability and radical scavenging power of phenolic compounds of cocoa and coffee mixtures

Cocoa and coffee are natural sources of phenolic compounds, which are degraded during beans processing of both. For this reason, there is an interest in obtaining extracts of these bio compounds. The aim of this study was uncovering the radical scavenging activity (AC) of mixtures of cocoa and coffee extracts, and the bioavailability of their phenolic compounds, resorting to in vitro models: DPPH and ORAC antioxidant methods, and the characterization of the trans-epithelial transport of cocoa and coffee phenolics through Caco-2 cells monolayer model of the intestinal barrier. The cocoa displayed a higher AC than the coffee regarding both DPPH and ORAC assays, while the mixtures increased in parallel with the percentage of cocoa in the blends. The combination index was calculated to set up the type of interaction in the cocoa-coffee mixtures, obtaining that the mixture 25:75 was moderately antagonistic, 50:50 nearly additive, and 75:25 slightly synergistic. The absorption efficiency of the cocoa phenolic compounds was between 87.9%-97.4%, in the coffee compounds was 100%. The mixtures varied according to the proportion of cocoa and coffee. The results obtained allowed concluding that the phenolic compounds present in cocoa and coffee, respectively, are featured by high bioavailability and a valuable antioxidant capacity, while no pattern was found in the mixtures concerning the real benefit of using them combined.

Molecular interaction between pectin and catechin/procyanidin in simulative juice model: Insights from spectroscopic, morphology, and antioxidant activity

The interactions between polysaccharides and phenolics in foods affect their physicochemical properties and bioactivity. Pectin and catechin/procyanidin present in plants ubiquitously and attracting more attentions for the potential health benefits. This work investigates the interactions between high methoxyl pectin and catechin/procyanidin in a simulative juice model using multiple microscopic and spectroscopic approaches and their influences on the antioxidant activity of phenolics were evaluated in the Caco-2 cells model. The results showed that pectin with either of phenolic compunds exhibited lower transmittance, zeta potential, viscosity, and larger particle size than it alone. The morphology of pectin complexes with either of phenolics under experimental conditions (pH = 3.5) was observed. The ΔH° (-6.821 kJ mol^-1 ) and ΔS° (6.357×10^-2  kJ mol^-1 ) indicated that pectin interacts with procyanidin via electrostatic interaction, whereas hydrophobic interaction was the dominant drive force between pectin and catechin (ΔH° = 1.422 kJ mol^-1 ; ΔS° = 13.048 × 10^-2  kJ mol^-1 ). The antioxidant activities of catechin/procyanidin decreased while binding with pectin based on indexes of glutathione peroxidase, total superoxide dismutase, total antioxidant capacity, and malondialdehyde. PRACTICAL APPLICATION: The findings of this work indicated that the physicochemical property of pectin and the antioxidant activity of catechin/procyanidin were influenced by the interactions between pectin and catechin/procyanidin in a simulative food system. This study provides insights into the molecular interactions between pectin and phenolics in a simulative food system.

FTIR and PLS-regression in the evaluation of bioactive amines, total phenolic compounds and antioxidant potential of dark chocolates

Cloning techniques are used to improve agronomical traits and answer to the demand for fine chocolate. The objective of this study was to predict the concentrations of bioactive amines, phenolic compounds, and the antioxidant potential of dark monoclonal chocolate from nine fine cocoa varieties by FTIR analysis and conventional techniques. Total phenolic compounds, bioactive amines and antioxidant activity varied significantly among chocolates. The antioxidant activity was also affected by the analytical method (DPPH vs. Rancimat). Chemometric models based on FTIR data provided satisfactory predictions of the concentrations of the amines: spermidine (R2 = 0.92; RMSEP = 0.39; RMSEC = 0.21), tryptamine (R2 = 0.92; RMSEP = 0.41; RMSEC = 0.20), cadaverine (R2 = 0.82; RMSEP = 1.58; RMSEC = 0.75) and tyramine (R2 = 0.87; RMSEP = 1.87; RMSEC = 0.68); as well as phenolic compounds and antioxidant activity by Rancimat® (R2 = 0.98; RMSEP = 0.32; RMSEC = 0.21) and DPPH (R2 = 0.97; RMSEP = 4.05; RMSEC = 1.66). The wavenumbers of amines vibrations are among those that most affected antioxidant prediction models, confirming the contribution of amines to the antioxidant activity of chocolates.

Robust prediction performance of inner quality attributes in intact cocoa beans using near infrared spectroscopy and multivariate analysis

Fast and simultaneous determination of inner quality parameters, such as fat and moisture contents, need to be predicted in cocoa products processing. This study aimed to employ the near-infrared reflectance spectroscopy (NIRS) in predicting the quality mentioned above parameters in intact cocoa beans. Near-infrared spectral data, in a wavelength ranging from 1000 to 2500 nm, were acquired for a total of 110 bulk cocoa bean samples. Actual fat and moisture contents were measured with standard laboratory procedures using the Soxhlet and Gravimetry methods, respectively. Two regression approaches, namely principal component regression (PCR) and partial least square regression (PLSR), were used to develop the prediction models. Furthermore, four different spectra correction methods, namely multiple scatter correction (MSC), de-trending (DT), standard normal variate (SNV), and orthogonal signal correction (OSC), were employed to enhance prediction accuracy and robustness. The results showed that PLSR was better than PCR for both quality parameters prediction. Spectra corrections improved prediction accuracy and robustness, while OSC was the best correction method for fat and moisture content prediction. The maximum correlation of determination (R²) and residual predictive deviation (RPD) index for fat content were 0.86 and 3.16, while for moisture content prediction, the R² coefficient and RPD index were 0.92 and 3.43, respectively. Therefore, NIRS combined with proper spectra correction method can be used to rapidly and simultaneously predict inner quality parameters of intact cocoa beans.

Influence of high-intensity ultrasound on the IgE binding capacity of Act d 2 allergen, secondary structure, and In-vitro digestibility of kiwifruit proteins

Kiwifruit can trigger allergic reactions that can lead to death, causing public health concerns worldwide. In the present study, we treated kiwifruit samples with high-intensity ultrasound (20 kHz, 400 W, 50% duty cycle) for 0 to 16 min to evaluate its effect on the IgE binding capacity of kiwifruit allergen Act d 2, secondary structure and in-vitro digestibility of kiwifruit proteins. The changes in the protein solubility and microstructures of kiwifruit were also analyzed. The results showed that treatment with powerful ultrasound caused a significant disruption in the microstructure of kiwifruit tissues, leading to the changes in the secondary structures of proteins, including a loss of alpha-helixes and an increase in beta-sheet structures. These structural changes were due to the ultrasound treatment, especially 16 min of treatment, resulted in a 50% reduction in Act d 2 allergen content and significantly improved in-vitro digestibility up to 62% from the initial level of 35%. Furthermore, the solubility of the total proteins present in kiwifruit samples was significantly decreased by 20% after 16-min ultrasound processing. The results of this work showed that high-intensity ultrasound treatment has a potential application in reducing the allergenicity of kiwifruit or related products.

NIR and MIR spectroscopy for quick detection of the adulteration of cocoa content in chocolates

The Near (NIR) and Mid (MIR) Infrared Spectroscopy associated with chemometric techniques were used to determine the cocoa solids content in chocolates and detect possible adulterations. Five chocolate formulations (30% to 90%) were produced with different cocoa solids concentrations and 110 commercial samples from 10 different countries with varying concentrations of cocoa solids (30% to 88%) were acquired. All repetions of the produced and commercial chocolates were evaluated using NIR and MIR. Spectroscopic data were submitted to multivariate techniques of Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS). For both spectroscopy techniques, the PCA of the 5 formulations formed 5 distinct groups regarding the cocoa solids and the commercial samples showed a behavior pattern similar to the produced samples. For PLS, the regression equations showed high predictive capacity, with correlation coefficients above 90 and RMSECV values of 0.70 and 1.22, for NIR and MIR, respectively. These models highlighted, approximately, 14% of the commercial samples as possible adulterated products.

Optimization of ultrasound-assisted extraction of bioactive compounds from acerola waste

The industrial processing of acerola (Malpighia emarginata D.C.) produces huge quantities of waste material that are badly discarded or undervalued. In spite of this, acerola wastes have a high content of antioxidant compounds. The aim of this work was to study the extraction of antioxidant compounds from acerola residues using ultrasound assisted extraction. Using multiple regression techniques, the effects of ethanol concentration in the hydroethanolic solution (C), extraction time (t), temperature (T), and liquid-solid ratio (R) on the total phenolic content, total flavonoid content and antioxidant potential were investigated. The best extraction conditions were identified using the desirability function, which is a multi-response optimization technique. The optimal processing parameters were 67.5% of ethanol concentration, temperature of 80.9 °C, liquid/solid ratio of 59.8 mL/g, and extraction time of 13.6 min. HPLC-UV has been used to identify the main antioxidant compounds obtained under these optimal condition. Based on the results, acerola waste has high potential for better use, such as in food and pharmaceutical applications.

Prediction of Fatty Acids in Chocolates with an Emphasis on C18:1 trans Fatty Acid Positional Isomers Using ATR-FTIR Associated with Multivariate Calibration

This work aimed to predict C18:1 TFA isomers as well as other groups of fatty acids (saturated, monounsaturated, polyunsaturated, and total TFA) in chocolates by ATR-FTIR and partial least square regression. The quantification of fatty acids in representative samples (white, dark, and milk chocolates) was rapid (<30 s) and did not require derivatization. The optimized models showed satisfactory linear correlations compared to a reference gas chromatographic method. Coefficients of correlation for prediction considering C18:1 positional isomers were 0.973 (trans 6-8), 0.991 (trans 9), 0.991 (trans 10), 0.988 (trans 11), and 0.998 (trans 12). When considering fatty acids groups, these coefficients ranged from 0.965 to 0.999. The obtained results indicate that this straightforward procedure is suitable for chocolate analysis, for determining its general lipid composition and TFA isomeric profile, which would be of great interest for quality control programs in the face of the new TFA regulations.

Antioxidant Activities and Volatile Flavor Components of Selected Single-Origin and Blend Chocolates

The biological activity of chocolates gains more and more attention of consumers. Its antioxidant properties depend, among other factors, mainly on the origin of cocoa and the characteristics that this origin gives to the final product. Therefore, the aim of the study was to measure and compare the total content of polyphenols, antioxidant activity, and key odorants of commercial chocolates made from blend cocoa with single-origin ones. The highest content of polyphenols was found in 90% blend cocoa chocolate and single-origin samples, while the lowest content was exhibited by 100% chocolate from blend cocoa mass. The highest antioxidant activity measured by 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) and ferric reducing antioxidant power (FRAP) assays was observed in the sample of chocolate with 90% cocoa solids from blend mass, followed by single-origin chocolates. A high positive correlation between ABTS assay and the total polyphenol and phenolic acids' content, as well as among the total content of polyphenols, flavonoids, and phenolic acids was found. Mineral composition analysis showed that dark chocolate is a valuable source of some elements, especially Mg, Fe, and Zn. Potentially toxic elements were not detected or below permitted limits. Moreover, it was noticed that the main volatile compound in all tested samples was acetic acid, but pyrazines were considered the most important group of chocolate odorants.

Application of Mass Spectrometry Imaging for Visualizing Food Components

Consuming food is essential for survival, maintaining health, and triggering positive emotions like pleasure. One of the factors that drive us toward such behavior is the presence of various compounds in foods. There are many methods to analyze these molecules in foods; however, it is difficult to analyze the spatial distribution of these compounds using conventional techniques, such as mass spectrometry combined with high-performance liquid chromatography or gas chromatography. Mass spectrometry imaging (MSI) is a two-dimensional ionization technology that enables detection of compounds in tissue sections without extraction, purification, separation, or labeling. There are many methods for ionization of analytes, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization, and desorption electrospray ionization. Such MSI technologies can provide spatial information on the location of a specific analyte in food. The number of studies utilizing MSI technologies in food science has been increasing in the past decade. This review provides an overview of some of the recent applications of MSI in food science and related fields. In the future, MSI will become one of the most promising technologies for visualizing the distribution of food components and for identifying food-related factors by their molecular weights to improve quality, quality assurance, food safety, nutritional analysis, and to locate administered food factors.

Data analysis on near infrared spectroscopy as a part of technology adoption for cocoa farmer in Aceh Province, Indonesia

Presented manuscript described data analysis on near infrared spectroscopy used as adopted and portable technology for cocoa farmers in Aceh Province, Indonesia. The near infrared spectroscopy (NIRS) assisted farmers in post-harvest handling especially for cocoa quality evaluation. This technology was used to determine moisture content (MC) and fat content (FC) of intact cocoa bean samples rapidly and simultaneously. Near infrared spectra data were acquired as absorbance spectrum in wavelength range from 1000 to 2500 nm with co-added of 32 scans for a total of 72 intact bulk cocoa bean samples. Spectra data can be used to predict MC and FC of intact cocoa beans by establishing prediction models and validate with actual MC and FC measured by means of standard laboratory procedures. Prediction performances were evaluated using several statistical indicators: coefficient correlation (r), coefficient of determination (R²), root mean square error (RMSE) and residual predictive deviation (RPD) index. Near infrared spectra data can be enhanced using spectra pre-treatment methods to improve prediction performances. Moreover, prediction models can be developed using principal component regression (PCR), partial least squares regression (PLSR) and other regression approaches. Ideal prediction models should have r and R² above 0.75, RPD index above 2.0 and RMSE lower than its standard deviation (SD). Dataset were available as raw MS Excel format and The Unscrambler files as *.unsb extension.

Effects of adding solid and molten chocolate on the physicochemical, antioxidant, microbiological, and sensory properties of ewe's milk cheese

A novel dairy product, namely "chocolate cheese", was produced with two typical Sicilian food products: Pecorino cheese, processed from ewe's milk, and Modica chocolate. The cheese, manufactured with 0%, 5%, 10%, and 15% (w/w) solid or molten chocolate, was evaluated after 0, 2, 4, and 6 weeks of vacuum storage for its nutritional and health properties. The addition of chocolate reduced the pH, protein, fat, and ash; the addition of 5% or 10% molten chocolate reduced hardness (N/mm² ). The addition of either solid or molten chocolate resulted in a slight increase (P < 0.1038) in the total polyphenol content, a higher oleic acid content, and less oxidative stability. The microbiological profile showed that the total mesophilic count and the number of mesophilic coccus lactic acid bacteria (LAB) were approximately equal (about 10⁸ CFU/g) in all cheese. The survival of the microorganisms was affected by both the chocolate added and the storage time. Chocolate cheese stored for 6 weeks had less Enterobacteriaceae than control cheese, whereas yeasts were detected at higher cell densities in the former cheese. Filamentous fungi were undetectable in some cheese. Differences were also observed in the number of mesophilic rod LAB, which increased progressively over time in all cheese, and in Enterobacteriaceae, yeasts, and filamentous fungi, which decreased during storage. Descriptive and hedonic sensory tests and principal component analysis showed that fresh cheese and cheese stored for 2 weeks, including 5% molten chocolate, were the most preferred by evaluators. Based on these results, chocolate cheese has the potential to be appreciated in the market for its nutritional, health, and sensory properties. PRACTICAL APPLICATION: Chocolate cheese, made by combining two typical Sicilian foods, Pecorino cheese and Modica chocolate, is proposed as a novel dairy product. The highest sensory acceptance was obtained with the addition of 5% molten chocolate and storage for 2 weeks. Given its improved antioxidant properties, healthier fat, and sensory properties, chocolate cheese has the potential to be appreciated in the market, especially by young consumers.

The Kinetics of Total Phenolic Content and Monomeric Flavan-3-ols during the Roasting Process of Criollo Cocoa

Cocoa beans are the main raw material for the manufacture of chocolate and are currently gaining great importance due to their antioxidant potential attributed to the total phenolic content (TPC) and the monomeric flavan-3-ols (epicatechin and catechin). The objective of this study was to determine the degradation kinetics parameters of TPC, epicatechin, and catechin during the roasting process of Criollo cocoa for 10, 20, 30, 40, and 50 min at 90, 110, 130, 150, 170, 190, and 200 °C. The results showed a lower degradation of TPC (10.98 ± 6.04%) and epicatechin (8.05 ± 3.01%) at 130 °C and 10 min of roasting, while a total degradation of epicatechin and a 92.29 ± 0.06% degradation of TPC was obtained at 200 °C and 50 min. Reaction rate constant (k) and activation energy (Ea) were 0.02–0.10 min⁻¹ and 24.03 J/mol for TPC and 0.02–0.13 min⁻¹ and 22.51 J/mol for epicatechin, respectively. Degradation kinetics of TPC and epicatechin showed first-order reactions, while the catechin showed patterns of formation and degradation.

Artificial Intelligence Applied to Flavonoid Data in Food Matrices

Increasing interest in constituents and dietary supplements has created the need for more efficient use of this information in nutrition-related fields. The present work aims to obtain optimal models to predict the total antioxidant properties of food matrices, using available information on the amount and class of flavonoids present in vegetables. A new dataset using databases that collect the flavonoid content of selected foods has been created. Structural information was obtained using a structural-topological approach called TOPological Sub-Structural Molecular (TOPSMODE). Different artificial intelligence algorithms were applied, including Machine Learning (ML) methods. The study allowed us to demonstrate the effectiveness of the models using structural-topological characteristics of dietary flavonoids. The proposed models can be considered, without overfitting, effective in predicting new values of Oxygen Radical Absorption capacity (ORAC), except in the Multi-Layer Perceptron (MLP) algorithm. The best optimal model was obtained by the Random Forest (RF) algorithm. The in silico methodology we developed allows us to confirm the effectiveness of the obtained models, by introducing the new structural-topological attributes, as well as selecting those that most influence the class variable.

Detection of adulterants in dietary supplements with Ginkgo biloba extract by attenuated total reflectance Fourier transform infrared spectroscopy and multivariate methods PLS-DA and PCA

The infrared spectroscopy with attenuated total reflectance (ATR) sampling coupled with chemometric methods has been applied to non-destructive detection of adulterants in dietary supplements containing Ginkgo biloba extract. The sample set comprised the spectra of six drugs and sixteen dietary supplements with ginkgo leaf extract. Spectral data (900-1800 cm^-1) were analyzed using multivariate partial least squares regression combined with a discriminant analysis (PLS-DA). The second derivative of spectra followed by mean centering was used as pre-processing method. Three models were constructed and validated for detection of potential adulterants: kaempferol, quercetin, and rutin. The iPLS-DA classification models achieved about 87.5%, 93,7%, and 87,5% of correct classification for adulteration with kaempferol, quercetin and rutin, respectively. The results obtained from classification models were verified by chromatographic fingerprints of unhydrolyzed sample extracts. Two-trace two-dimensional asynchronous correlation maps were constructed from pairs of spectra (each dietary supplement spectrum vs. averaged spectrum of drugs) and then analyzed by multiway PCA which revealed good discrimination between samples.

Simultaneous Recognition of Species, Quality Grades, and Multivariate Calibration of Antioxidant Activities for 12 Famous Green Teas Using Mid- and Near-Infrared Spectroscopy Coupled with Chemometrics

In this paper, mid- and near-infrared spectroscopy fingerprints were combined to simultaneously discriminate 12 famous green teas and quantitatively characterize their antioxidant activities using chemometrics. A supervised pattern recognition method based on partial least square discriminant analysis (PLSDA) was adopted to classify the 12 famous green teas with different species and quality grades, and then optimized sample-weighted least-squares support vector machine (OSWLS-SVM) based on particle swarm optimization was employed to investigate the quantitative relationship between their antioxidant activities and the spectral fingerprints. As a result, 12 famous green teas can be discriminated with a recognition rate of 100% by MIR or NIR data. However, compared with individual instrumental data, data fusion was more adequate for modeling the antioxidant activities of samples with RMSEP of 0.0065. Finally, the performance of the proposed method was evaluated and validated by some statistical parameters and the elliptical joint confidence region (EJCR) test. The results indicate that fusion of mid- and near-infrared spectroscopy suggests a new avenue to discriminate the species and grades of green teas. Moreover, the proposed method also implies other promising applications with more accurate multivariate calibration of antioxidant activities.

Detection and quantification of offal content in ground beef meat using vibrational spectroscopic-based chemometric analysis

As less consumed animal by-product, beef and pork offal have chances to sneak into the authentic ground beef meat products, and thus a rapid and accurate detection and quantification technique is highly required. In this study, Fourier transformed-infrared (FT-IR) spectroscopy was investigated to develop an optimized protocol for analyzing ground beef meat potentially adulterated with six types of beef and pork offal. Various chemometric models for classification and quantification were constructed for the collected FT-IR spectra. Applying optimized chemometric models, FT-IR spectroscopy could differentiate authentic beef meat from adulterated samples with >99% accuracy, to identify the type of offal in the sample with >80% confidence, and to quantify five types of offal in an accurate manner (R² > 0.81). An optimized protocol was developed to authenticate ground beef meat as well as identify and quantify the offal adulterants using FT-IR spectroscopy coupled with chemometric models. This protocol offers a limit of detection <10% w/w of offal in ground beef meat and can be applied by governmental laboratories and food industry to rapidly monitor the integrity of ground beef meat products.