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Raman spectroscopy is an emerging technique for the rapid detection of oil qualities. But the spectral analysis is time-consuming and low-throughput, which has limited the broad adoption. To address this issue, nine supervised machine learning (ML) algorithms were integrated into a Raman spectroscopy protocol for achieving the rapid analysis. Raman spectra were obtained for ten commercial edible oils from a variety of brands and the resulting spectral dataset was analyzed with supervised ML algorithms and compared against a principal component analysis (PCA) model. A ML-derived model obtained an accuracy of 96.7% in detecting oil type and an adulteration prediction of 0.984 (R2). Several ML algorithms also were superior than PCA in classifying edible oils based on fatty acid compositions by gas chromatography, with a faster readout and 100% accuracy. This study provided an exemplar for combining conventional Raman spectroscopy or gas chromatography with ML for the rapid food analysis.

This study presents the employment of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflection and principal component analysis (PCA) to analyze the stability of a Pickering emulsion stabilized by carboxylated-cellulose nanocrystal (cCNC) comprising sesame oil phases with or without sesamolin. FTIR measurements identified an intermolecular hydrogen bond between the ester group of the triglyceride and the carboxyl group of the cCNC to create the emulsion droplet. The spectral bands from the hydroxyl group vibration (3700–3050 cm−1), carbonyl (1744 cm−1), C O groups of the ester triglyceride and cCNC (1160–998 cm−1) markedly discriminated between stabilized and destabilized emulsions. The PCA of FTIR spectra detected the change of molecular interaction during storage according to creaming, aggregation, and coalescence and changes in physicochemical parameters such as droplet size, refractive index, and zeta potential. Hence, PCA enabled the observation of the destabilization of emulsion in real-time. [Display omitted] • Cellulose-based Pickering emulsions were loaded with sesamolin-enriched sesame oil. • The ATR-FTIR spectroscopy probed the stability of the o/w Pickering emulsion. • Droplet size, zeta potential, & refractive index were changed in unstable emulsions. • ATR-FTIR spectral analysis depicted molecular interactions of emulsion components. • ATR-FTIR coupled with PCA differentiated stable from unstable emulsions in real-time. [ABSTRACT FROM AUTHOR]

Fermentation is the key process to determine the quality of black tea. Traditional physical and chemical analyses are time consuming, it cannot meet the needs of online monitoring. The existing rapid testing techniques cannot determine the specific volatile organic compounds (VOCs) produced at different stages of fermentation, resulting in poor model transferability; therefore, the current degree of black tea fermentation mainly relies on the sensory judgment of tea makers. This study used proton transfer reaction mass spectrometry (PTR-MS) and fourier transform infrared spectroscopy (FTIR) combined with different injection methods to collect VOCs of the samples, the rule of change of specific VOCs was clarified, and the extreme learning machine (ELM) model was established after principal component analysis (PCA), the prediction accuracy reached 95% and 100%, respectively. Finally, different application scenarios of the two technologies in the actual production of black tea are discussed based on their respective advantages. • First detection of black tea fermentation volatiles by PTR-MS and FTIR techniques. • The study clarified for the first time the changing pattern of specific volatiles. • The effect of different injection methods on signal intensity was analyzed. • Both technologies can be applied to the actual production of black tea fermentation. [ABSTRACT FROM AUTHOR]

This study aimed to authenticate re-esterified triacylglycerol (rTG)-type omega-3 oils prone to adulteration with fatty acid ethyl ester (FAEE)-type oils via hierarchical cluster analysis (HCA) and principal component analysis (PCA) of their lipid profiles. A total of 104 rTG-type omega-3 oil samples, consisting of seven authentic (two commercial and five laboratory-made), 60 adulterated, and 37 unauthenticated commercial samples, were analyzed for their acylglycerol, FAEE, and total EPA/DHA contents. Type 1 authentic samples contained higher triacylglycerols (TG) (63.0-86.3 wt%), lower diacylglycerols (DG) (8.1-31.5 wt%), and no FAEE compared to type 2 authentic samples (36.9-62.1 wt% TG, 9.4-36.9 wt% DG, and 14.9-27.3 wt% FAEE). HCA and PCA differentiated authentic samples from adulterated samples, although type 2 samples were closer to adulterated samples. Both analyses showed that 30/37 commercial samples exhibited higher similarity in lipid profiles to authentic samples than to adulterated samples, indicating their potential for authentication., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Byung Hee Kim reports financial support was provided by Ministry of Food and Drug Safety. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

For texture control in plant-meat alternatives, the interrelationship between apparent characteristics and chemical bonds in high-fiber formulations remains unclear. The influence of mulberry leaf powder on apparent characteristics and chemical bonds of raw materials, block and strip products at addition amounts of 0.5-25% was analyzed. The results showed that 8% addition significantly increased the chewiness of the block by 98.12%. The strips' texture shows a downward trend, and the processing produced more redness and color difference. Additives promoted the formation of voids, lamellar and filamentous structures, and the strip produced more striped structures. Disulfide bonds significantly increased in the block, and the β-turn in the secondary structure enhanced by 12.20%. The β-turn transformed into a β-sheet in strips. Principal component analysis revealed that the texture improvement was associated with producing disulfide bonds and β-turn, providing a basis for high-fiber components to improve products' apparent characteristics by chemical bonds., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in the paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This paper develops a new hybrid, automated, and non-invasive approach by combining hyper-spectral imaging, Savitzky-Golay (SG) Filter, Principal Components Analysis (PCA), Machine Learning (ML) classifiers/regressors, and stacking generalization methods to detect sugar in honey. First, the 32 different sugar concentration levels in honey were predicted using various ML regressors. Second, the six ranges of sugar were classified using various classifiers. Third, the 11 types of honey and 100% sugar were classified using classifiers. The stacking model (STM) obtained R2: 0.999, RMSE: 0.493 ml (v/v), RPD: 40.2, a 10-fold average R2: 0.996 and RMSE: 1.27 ml (v/v) for predicting 32 sugar concentrations. The STM achieved a Matthews Correlation Coefficient (MCC) of 99.7% and a Kappa score of 99.7%, a 10-fold average MCC of 98.9% and a Kappa score of 98.9% for classifying the six sugar ranges and 12 categories of honey types and a sugar., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

In this study, Black chokeberry (Aronia melanocarpa) was used as an example to provide reference for improving the safety, efficacy and quality consistency of homologous foods. In this study, two quality markers (Q-markers) of 27 batches of Black chokeberry were determined using high performance liquid chromatography (HPLC), and there were some differences among the 27 samples. Origin B samples had the highest levels of Q-markers for S15, and origin C had lower than average levels overall. Samples were analyzed qualitatively and quantitatively by Systematic Quantitative Fingerprinting (SQFM). Subsequently, a three-wavelength fusion analysis (TWFP) was established on the chromatographic data to compensate for the lack of a single wavelength. Fourteen batches of TWFP samples were rated at Level 5 or above in the SQFM assessment, indicating that there is some variation in the content of samples from different origins. Principal component analysis (PCA) was used to observe the differences in chemical composition and content of TWFP samples. Subsequently, electrochemical fingerprinting (ECFP) was established and nine characteristic parameters were recorded, showing that the samples were suppressed for all electrochemical Belousov-Zhabotinsky oscillation systems (B-Z oscillation systems). Finally, antioxidant tests were performed using DPPH. The antioxidant capacity was predicted using Partial Least Squares (PLS) analysis with R 2 Y = 0.84, Q 2  = 0.77, a good model fit and accurate prediction. The fingerprint-potency relationship between IC 50 -peak area showed that 17 of the 19 shared peaks were negatively correlated, indicating that 17 peaks contributed significantly to the antioxidant. The methods established in this study for the determination of TWFP and ECFP, as well as the spectral relationships with peak area and IC 50 , can be used for the quality inspection and antioxidant capacity test of Black chokeberry, which provides a new research direction for improving the quality standard of medicinal and foodstuffs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rice varieties of different subspecies types (indica rice and japonica rice) across various geographical origins (Hunan, Jiangsu, and Northeast China) were monitored using microsatellite markers (simple sequence repeats, SSR). 110 representative rice cultivars were collected from the main crop areas. Multiple methods including clustering analysis (neighbor-joining (NJ) method, unweighted pair-group method with arithmetic mean (UPGMA) method), principal component analysis (PCA) and model-based grouping were applied. The study revealed that 25 pairs of SSR markers exhibited a broad range of polymorphism information content (PIC) values, ranging from 0.240 to 0.830. Furthermore, our study successfully achieved a higher overall mean correct rate of 99.09% in determining the geographical origin of rice. Simultaneously, it accurately classified indica rice and japonica rice. These findings are significant as they provide an SSR fingerprint of 110 high-quality rice cultivars, serving as a valuable scientific resource for the detection of rice adulteration and traceability of its origin., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Eleven compounds including caffeic acid (CA), 4 kinds of caffeoylquinic acid (CQA) and 6 kinds of dicaffeoylquinic acid (DCQA), were selected to evaluate the anti-inflammatory effectiveness using mouse primary peritoneal macrophages in the absence or presence of lipopolysaccharide (LPS). The optimal non-cytotoxic doses of each individual compound were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Pro-inflammatory (TNF-α, IL-1β, IL-6) and anti-inflammatory (IL-10) cytokines secreted by treated macrophages were analyzed using the enzyme-linked immunosorbent assay. Cytokine secretion profiles of each individual test sample at optimal non-cytotoxic doses were further analyzed using Principal Component Analysis (PCA). The results showed that CA and all selected CQAs exhibited lower cytotoxicity (IC 50 : >50 μmol/l). Both CA and 5-CQA were found to have the most significant contributions for inhibiting pro-inflammatory cytokines, but increasing anti-inflammatory cytokine secretions, evidencing that CA at 10 μmol/l and 5-CQA at 25 μmol/l can be qualified as potent anti-inflammatory agents for treating inflammation-related diseases. [Display omitted] • Eleven caffeic acid (CA) derivatives were analyzed their anti-inflammatory effects. • Cytotoxicities of CA, caffeoylquinic acids (CQAs) and diCQAs (DCQAs) were compared. • Cytokines secreted by treated macrophages were comprehensively assessed using PCA. • CA and CQAs had the lower cytotoxicity than DCQAs. • CA and 5-CQA had the most significant contributions for anti-inflammatory effects. [ABSTRACT FROM AUTHOR]

The pharmaceutical and nutraceutical potentials of whole fruit, pulp and seeds of Rosa pimpinellifolia L. were evaluated. Forty-two phenolic compounds and two triterpenoids were identified in extracts by LC-MS/MS and GC–MS, respectively. The most prominent compounds were ellagic acid, catechin, epicatechin, tannic acid, quercetin, oleanolic acid, and ursolic acid. The highest enzyme inhibitory activities of the extracts (94.83%) were obtained against angiotensin-converting enzyme and were almost equal to those of the commercial standard (lisinopril, 98.99%). Whole fruit and pulp extracts (IC 50 :2.47 and 1.52 μg DW/mL) exhibited higher antioxidant capacity than the standards (α -tocopherol, IC 50 :9.89 μg DW/mL). The highest antibacterial activity was obtained against Bacillus cereus (MIC: 256 μg/mL) for the whole fruit extract. Correlation analyses were conducted to find the correlation between individual phenolics and enzyme inhibitory activities. The results showed the remarkable future of not only the edible part but also the seeds of black rose hips in phytochemical and functional aspects. [Display omitted] • The parts of the fruit contain different phytochemical content and posses different bioactivities. • Whole fruit showed a better polyphenolic profile, both in terms of quantity and diversity. • Whole fruit, pulp and seed parts possessed excellent ACE inhibition activity. • BChE, urease, tyrosinase and elastase inhibition activity were detected in whole fruit and pulp parts. • Whole fruit extract showed a significant antioxidant and antibacterial properties. [ABSTRACT FROM AUTHOR]

The structure and function of dietary proteins, as well as their subcellular prediction, are critical for designing and developing new drug compositions and understanding the pathophysiology of certain diseases. As a remedy, we provide a subcellular localization method based on feature fusion and clustering for dietary proteins. Additionally, an enhanced PseAAC (Pseudo-amino acid composition) method is suggested, which builds upon the conventional PseAAC. The study initially builds a novel model of representing the food protein sequence by integrating autocorrelation, chi density, and improved PseAAC to better convey information about the food protein sequence. After that, the dimensionality of the fused feature vectors is reduced by using principal component analysis. With prediction accuracies of 99.24% in the Gram-positive dataset and 95.33% in the Gram-negative dataset, respectively, the experimental findings demonstrate the practicability and efficacy of the proposed approach. This paper is basically exploring pseudo-amino acid composition of not any clinical aspect but exploring a pharmaceutical aspect for drug repositioning. • Accurately predicting dietary protein subcellular composition using machine learning methods remains a challenging scientific inquiry. • This study provides a feature-fusion and clustering-based subcellular localization method for dietary proteins. • The construction of food protein feature expression models involves the use of autocorrelation and chi-density approaches. • An enhanced PseAAC (Pseudo-amino Acid Composition) method is suggested, which builds upon the conventional PseAAC. • Prediction accuracies of 99.24% on the Gram-positive dataset and 95.33% on the Gram-negative dataset, respectively, is observed. [ABSTRACT FROM AUTHOR]

This study explored the efficacy of multi-elements combined with chemometrics to discriminate the geographical origins of oysters (Crassostrea ariakensi). We determined 52 elements in 166 samples from four regions along the southeast coast of China. Significant regional variations of 51 elements were revealed (P < 0.05), while the principal component analysis (PCA) provided no clear regional delineations. The training models (n = 117) established on linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), and random forest (RF) uniformly achieved 100% predictive accuracy. The cross-validation accuracies of the final models (n = 166) derived from LDA, PLS-DA, and RF were 100%, 100%, and 99.4%, respectively. Even with the models simplified to 8 elements (Zn, Al, K, Cd, Cu, Rb, B, and Ag), high predictive and cross-validation accuracies were maintained, underscoring the robustness and algorithm flexibility of elemental profiling for accurately identifying the geographical origins of oysters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The freezing point (FP) is an important quality indicator of the superchilled meat. Currently, the potential of hyperspectral imaging (HSI) for predicting beef FP as affected by multiple freeze-thaw (F-T) cycles was explored. Correlation analysis revealed that the FP had a negative correlation with the proportion of bound water (P 21 ) and a positive correlation with the proportion of immobilized water (P 22 ). Moreover, the optimal wavelengths were selected by principal component analysis (PCA). Principal component regression (PCR) and partial least squares regression (PLSR) models were successfully developed based on the optimal wavelengths for predicting FP with determination coefficient in prediction (R P 2 ) of 0.76, 0.76 and root mean square errors in prediction (RMSEP) of 0.12, 0.12, respectively. Additionally, PLSR based on full wavelengths was established for predicting P 21 with R P 2 of 0.80 and RMSEP of 0.67, and PLSR based on the optimal wavelengths was established for predicting P 22 with R P 2 of 0.87 and RMSEP of 0.66. The results show the potential of hyperspectral technology to predict the FP and moisture distribution of meat as a nondestructive method., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Hongyuan (HY) yaks live in a pollution-free environment, making HY yak milk a green food, but their short milk production period and low milk yield make yak milk precious and expensive. The phenomenon of counterfeiting HY yak milk with ordinary milk from other origins has already occurred, so the authenticity assessment of HY yak milk is necessary. This study developed a rapid soft ionisation by chemical reaction in transfer quadrupole time-of-flight mass spectrometry (SICRIT-QTOF MS) for HY yak milk differences assessment. Principal component analysis and orthogonal least squares discriminant analysis showed differences between HY milk and the other three origins. Twenty-eight differential compounds were screened out by variable importance in projection, fold change, P-value, and database matching. Furthermore, six characteristic compounds (proline, 2-hydroxy-3-methylbutyric acid, and l-isoleucine, etc.) of HY samples were putatively identified. The study demonstrated that SICRIT-QTOF MS has great potential for rapidly distinguishing the milk origin., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

[Display omitted] • FTIR fingerprints revealed different secondary structures of protein extracts. • Performing chemometric analysis with FTIR data can differentiate protein types. • α-helices were employed to separate sarcoplasmic protein from myofibrillar protein. • Alkali-extracted protein was classified from muscle protein by β-sheet structure. • Hydrolysates from various proteins exhibited different antioxidant activities. This research aimed to characterize protein types including sarcoplasmic protein (SP), myofibrillar protein (MP), and alkali-aided protein extract (AP) prepared from tilapia byproducts using water, 0.6 M NaCl, and alkaline solution (pH 11), respectively compared to freeze-dried minced tilapia muscle (CONTROL). Principal component analysis was performed from second derivative FTIR spectra to differentiate protein type. The AP mostly contained β-sheet structure and had low total sulfhydryl content and surface hydrophobicity. SP can be distinguished from MP by the loading plots of the FTIR bands representing the α-helical structure. While the bands for lipids and β-sheet of protein were noted for differentiating AP from CONTROL. After being hydrolyzed by Protease G6, the AP hydrolysate disclosed the highest ABTS radical scavenging activity, while the SP hydrolysate revealed the strongest metal chelating ability. Thus, an understanding of how fish processing waste can be utilized in the production of antioxidant protein hydrolysates has been achieved. [ABSTRACT FROM AUTHOR]

[Display omitted] • ML approaches were extended to food identification and adulteration detection. • FTIR in combination with ML offered a non-destructive path for classifying selected oils and margarines. • PCA efficiently separated oil and margarine samples. • FTIR-ML method could detect 1% adulteration in oil samples. • KNN had the highest accuracy and R2 in both pure and adulterated samples. This study assessed the combined utility of ATR-FTIR spectroscopy and machine learning (ML) techniques for identifying and classifying pure njangsa seed oil (NSO), palm kernel oil (PKO), coconut oil (CCO), njangsa seed oil-palm kernel oil (NSOPKO) and njangsa seed oil-coconut oil (NSOCCO) margarine. Additionally, it quantified the degree of adulteration in each oil and margarine using ML regression models and sunflower oil and canola-flaxseed oil margarine as adulterants. Fingerprints of the oils and the margarines derived in the spectra region 4000–600 cm−1 were combined with ML models. The first two principal components explained 99.4% and 98% of the variance of pure oils and margarines and 90.1, 88.3, 88, 97.3 and 98.3% of adulterated PKO, NSO, CCO, NSOCCO and NSOPKO, respectively while enabling visualization. Pure margarines were classified accurately (100%) in all models. KNN was most effective in classifying pure oil at 97% followed by LR (93%), SVM (83%), LightGBM (53%) and DT (50%). The R2 obtained from all the models for adulterated PKO, NSO, CCO, NSOPKO and NSOCCO ranged from 59–99%, 55–99%, 45–94%, 69–98% and 59–94%, respectively. SVM and DT underperformed, while KNN was the best model. [ABSTRACT FROM AUTHOR]

Chickpeas are a nutrient-rich source with optimal and high essential amino acid score. To evaluate its potential as a functional food ingredient, 36 chickpea protein hydrolysates were produced at the lab-scale using food-grade enzymes. Parameters including yields, protein content, hydrolysis degree, and antioxidant activities were employed to identify the most favourable conditions for scaling up production to a pilot plant level using a principal component analysis. The selected hydrolysate demonstrated commendable traits: a substantial content of essential amino acids and proteins at 67.71%, notable protein (73.12%) and weight (72.00%) yields, coupled with exceptional solubility exceeding 80%, and a noteworthy digestibility of 89.50%. Upon transition to pilot plant proportions, the hydrolysate retained its attenuated protein profile while exhibiting heightened antioxidant activities. Derived chickpea protein hydrolysates offer promise for innovative foods applications, impacting health and chronic disease prevention., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The survival of Amazon stingrays is threatened due to excessive fishing and habitat degradation. To address this issue, this study developed a groundbreaking method to authenticate and differentiate Amazon stingray meats using a portable spectrophotometer and chemometrics. Samples were collected from various species, including an endangered one with a commercialization ban and no population reduction records. Principal Component Analysis (PCA), identified natural groupings based on the meat's commercial origin, while Partial Least Squares-Discriminant Analysis (PLS-DA), accurately discriminated the commercial and geographic origins with 100 % accuracy. Moreover, Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA), effectively distinguished Amazon stingray meat from other marketable species. This approach offers a rapid, precise, and non-destructive means for monitoring and controlling the illegal trade of these species, thereby supporting decision-making in the field and promoting the conservation and sustainability of freshwater stingrays in the Amazon region., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The accurate identification of tea grade is crucial to the quality control of tea. However, existing methods lack sufficient generalization ability in identifying tea grades due to the effect of temporal and spatial factors. In this study, we analyzed the effect of cultivar and altitude on EnshiYulu (ESYL) tea grades and established a robust model to evaluate their quality. Principal component analysis (PCA) revealed that differences in variety and elevation can mask grade differences. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) was used for grade identification of samples from different altitudes. For ESYL tea samples above and below 800 m altitude, 75 and 35 grade differentiated metabolites were discovered, with 14 common differentiated metabolites. Based on reconstructed OPLS-DA models, the grades of multi-altitude sources ESYL were discriminated with a rate > 85%. These results demonstrate the potential of a grade discrimination model based on common differential metabolites, which exhibits generalization ability., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Sea buckthorn is an important ecological and economic plant which has multiple bioactivities. The fruits and seeds of sea buckthorn are rich in oil. However, there are few studies on the differences of lipid profiles of sea buckthorn varieties. Herein, the lipidomic fingerprints of sea buckthorn was established. First, a mixture solvent of methanol and chloroform (2:1, v/v) was selected to extract the lipid of the flesh and seed of sea buckthorn. Then, global lipidomic analysis of different varieties of sea buckthorn was conducted. A total of 16 lipid classes and 112 lipid molecular species were determined. Several molecular species, such as PE (phosphatidylethanolamine) 18:1/18:3, PE18:0/18:1, PE18:0/18:2, etc. were selected as the potential biomarkers to classify the samples. Our study provides a scientific basis for quality control of sea buckthorn and promotes the development of sea buckthorn oil., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

• Algorithm-assisted Raman and SERS for rapid peroxide and fatty acid analysis of oil. • Advanced chemometric approaches can identify reheating-induced chemical changes. • The developed Raman method can measure trans fats less than 2% with 94% accuracy. • The developed SERS method can measure trans fats less than 2% with 97% accuracy. Deep-fat frying of food develops lipid oxidation products that deteriorate oil and pose a health risk. This necessitates the development of a rapid and accurate oil quality and safety detection technique. Herein, surface-enhanced Raman spectroscopy (SERS) and sophisticated chemometric techniques were used for rapid and label-free determination of peroxide value (PV) and fatty acid composition of oil in-situ. In the study, plasmon-tuned and biocompatible Ag@Au core–shell nanoparticle-based SERS substrates were used to obtain optimum enhancement despite matrix interference to efficiently detect the oil components. The potent combination of SERS and the Artificial Neural Network (ANN) method could determine the fatty acid profile and PV with upto 99% accuracy. Moreover, the SERS-ANN method could quantify the low level of trans fats, i.e., < 2%, with 97% accuracy. Therefore, the developed algorithm-assisted SERS system enabled the sleek and rapid monitoring and on-site detection of oil oxidation. [ABSTRACT FROM AUTHOR]

Several factors affect the quality of beef. In the field of chemometrics, multi-block data analysis methods are useful for examining multiple sources of information from a sample. This study focuses on the application of ComDim, a multi-block data analysis method, to evaluate beef from different parts of hyperspectral spectrum and image texture information, 1 H NMR fingerprints, quality parameters and electronic nose. Compared to principal component analysis (PCA) methods based on low-level data fusion, ComDim is more efficient and powerful, because it reveals the relationships between the methods and techniques studied, as well as the variability of beef quality across multiple metrics. The quality and metabolite composition of beef tenderloin and hindquarters were differentiated, with low L* value and high shear tenderloin distinguished from hindquarters with opposite characteristics. The proposed strategy demonstrates that ComDim approach can be used to characterize samples when different techniques describe the same set of samples., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The aim of this study is to evaluate a previousely developed photoacoustic spectroscopy system with light sources of visible to short-wave near infrared (Vis-SWNIR, 395-940 nm) for detection of adulterations in cow's milk including formalin, urea, hydrogen peroxide, starch, sodium hypochlorite, and detergent powder. The results of principal component analysis (PCA) showed a very good visual differentiation of different adulterations. The artificial neural networks (ANN) showed the highest classification accuracy (97.6 %) in detection of adulteration type and adulteration level (nearly 100 %). It can be generally concluded that the Vis-SWNIR photoacoustic spectroscopy system is a reliable and potent instrument for detecting various types of milk adulterations. Further studies are suggested with including cow's milk of different sources with probable variations in composition to generalize the findings of the present study. With the extension of the light sources to the range of long-wave NIR, the system can be applied as a diagnostic tool for quality evaluation of other liquid foods., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Highlights • Phenolic composition in pericarps from 20 purple maize genotypes was characterized. • PMW had impact on inflammation, adipogenesis and diabetes in vitro. • Composition-activity relationship was elucidated by principal component analysis. • C3G, P3G and derivatives contributed to the biological properties of PMW. Abstract This study aimed to investigate the associations between phenolic composition of selected purple maize genotypes and their anti-inflammatory, anti-adipogenic and anti-diabetic properties in vitro. Anthocyanin-rich water extracts (PMWs) from 20 purple maize genotypes were evaluated in RAW 264.7 macrophages and 3T3-L1 adipocytes under different conditions. Cyanidin-3- O -glucoside (C3G), pelargonidin-3- O -glucoside (Pr3G), peonidin-3- O -glucoside (P3G) and corresponding acylated forms were major anthocyanins in PMW, accompanied by ten tentatively identified non-anthocyanin phenolics. Correlation studies showed that C3G, P3G, and derivatives, but not Pr3G and its acylated form contributed to the biological properties of PMW. Besides anthocyanins, quercetin, luteolin, and rutin were the dominant anti-inflammatory and anti-diabetic components, in terms of down-regulating pro-inflammatory mediator production in inflamed macrophages and adipocytes, modulating diabetes-related key enzymes and improving insulin sensitivity in insulin-resistant adipocytes. Quercetin and phenolic acids, especially vanillic acid and protocatechuic acid, were closely associated with anti-adipogenic properties of PMW via inhibition of the preadipocyte-adipocyte transition. [ABSTRACT FROM AUTHOR]

Highlights • Lactic acid bacteria fermentation altered metabolite profile of retorted broccoli. • Increase in glucoraphanin, glucoiberin and progotrin after fermentation. • Increase in 10 major polyphenols after fermentation. • The increases in metabolites were strain specific. • LC–MS and FTIR fingerprint based PCA enabled LAB species based separation. Abstract This study investigated the effect of lactic acid bacteria (LAB) fermentation on the chemical profile of autoclaved broccoli puree, using 7 broccoli-derived LAB isolates (named F1-F5, BF1 and BF2). The total concentrations of glucosinolates (glucoiberin, progoitrin and glucoraphanin) and 10 major phenolics significantly increased from trace level and 289 μg total phenolics/g dry weight (DW) respectively in autoclaved broccoli to 55 to ∼359 μg/g DW and 903 to ∼3105 μg/g DW respectively in LAB fermented broccoli puree. Differential impacts of LAB isolates on the chemical composition of autoclaved broccoli were observed, with the major differences being the significant increase in phloretic acid after fermentation by F1-F5 and an elevated glucoraphanin level in ferments by F1 and BF2. LAB fermentation is a promising way to increase the content of glucosinolates and polyphenolic compounds in broccoli, making the ferments attractive for use as functional ingredients or as a whole functional food. [ABSTRACT FROM AUTHOR]

Highlight • Forty-two primary and secondary metabolites were assigned. • Changes occurred during the germination and sprouting processes. • Sugar and amino acid metabolism pathways were activated under energy deficit. • Transcription of related genes confirmed the metabolic hypothesis. Abstract Germination and sprouting are regulated by the energy status. In the present study, mung bean seeds were treated with adenosine triphosphate and 2,4-dinitrophenol (DNP). The metabolomic changes during development of mung beans under different energy statuses were investigated. In total, 42 metabolites were identified. Principal component analysis revealed that the featured compounds produced in seeds were oleic, linoleic, and succinic acids. Sugars, including maltose, sucrose, and glucose were related to sprouting. Mung bean seeds utilised diverse energy resources and produced higher succinic acid content. Sugars and secondary metabolites accumulated in sprouts. Nitrogen, sugar, and amino acid metabolism pathways contributed to this physiological process. DNP caused an energy deficit, which resulted in the consumption and translation of glucose. Higher contents of other saccharides and amino acids were observed. The transcriptional results further confirmed our metabolic hypothesis. In conclusion, sufficient energy supply is crucial for sprout development and nutritive metabolite synthesis. [ABSTRACT FROM AUTHOR]

Highlights • Classification of wine based on the content of carboxylic acids. • Capillary electrophoresis and biosensor analysis of carboxylic acids linked to chemometrics. • Principal component analysis on lactate and inhibition of sarcosine oxidase, vs. wine tasting. • Self-organized maps as a novel method linked to biosensor analysis. Abstract Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods – principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classification. [ABSTRACT FROM AUTHOR]

Highlights • Orange juice models were flavoured with seven characteristic volatile compounds (VCs). • Nine retronasal attributes were affected by sugar content. • Orthonasal "overripe orange" and six VCs increased with increasing sugar content. • Total VC release was highly correlated with perceived intensity of "overripe orange". Abstract To examine the effect of sugar reduction on the sensory perception of sweetened beverages, an orange juice soft drink model flavoured with seven characteristic compounds (hexanal, decanal, linalool, ethyl butanoate, α-pinene, β-myrcene and (Z)-3-hexen-1-ol) was developed. Five samples were prepared with relevant sugar contents (5.2, 8.2, 9.7, 11.2 and 14.2 °Brix). Using retronasal quantitative descriptive analysis (QDA), nine attributes were found to differ significantly (p < 0.05) with sugar content. When the samples were evaluated orthonasally, only the attribute "overripe orange" significantly decreased (p < 0.05) with reduction of sugar content. Headspace solid-phase microextraction with gas chromatography–mass spectrometry showed that as sugar concentration decreased, the headspace concentration of six of the volatile compounds decreased, whilst ethyl butanoate remained constant. Principal component analysis revealed that the total release of the flavour compounds was highly correlated with the perceived intensity of the orthonasal attribute "overripe orange". [ABSTRACT FROM AUTHOR]

Highlights • Fuzzy controller algorithm via E-nose was used for S. oryzae infestation detection. • Out of 18 metal oxides sensors in E-nose, 6 were selected by fuzzy triplet score. • Defuzzified data obtained was subjected to PCA and MLR techniques. • MLR was cross validated with reference analysis methods of protein and uric acid. • PCA (84.75%) and MLR (97.2, 99.7%) values confirmed reliability of algorithm. • Hybrid fuzzy E-nose is authentic tool for detection of insects in food grains. Abstract Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. oryzae infested rice with PCA and MLR techniques. Reliability of data was cross validated with reference methods of protein and uric acid content. Out of 18 MOS, 6 sensors namely P30/2, P30/1, T30/1, P40/2, T70/2 and PA/2 showed maximum resistivity change. Defuzzified score of 62.17 for P30/2 and 59.33 for P30/1 MOS further confirmed validity studies of E-nose sensor response with reference methods. The PCA plots were able to classify up to 84.75% of rice with variable degree of S. oryzae infestation. The MLR values of predicted versus reference values of protein and uric acid content were found to be fitting with R2 of 0.972, 0.997 and RMSE values of 2.08, 1.05. [ABSTRACT FROM AUTHOR]

Highlights • Particle size and chemical composition of cornmeal influence the RS content. • Hydrothermal treatment promoted availability of free phenolic acids. • The ferulic acid was the major in the bound phenolic's fraction. • Cornmeal with smaller particle size had higher RS content. • Hydroxybenzoic and ferulic acids influence the RS formation. Abstract The influence of particle size and chemical composition of three different cornmeals on the resistant starch (RS) content formed during the hydrothermal treatment was studied. The changes in reducing sugars and phenolic acids in different fractions caused by the hydrothermal treatment were correlated with RS content. The cornmeal with smaller particle size had higher RS content (202 mg/g). The hydrothermal treatment promoted a reduction in the total reducing sugars (46.7–84.5%), availability of free phenolic acids (256.7%) and reduction of the bound phenolic acids (71.1%). The correlation between RS contents and phenolic acids was determined by multivariate statistics and principal component analysis (PCA) showed that hydroxybenzoic and ferulic acids influence the formation of RS similar to type 5, amylose-phenol complex. The texture profile parameters (TPA) of cornmeal were negatively correlated with RS and differential scanning calorimetry (DSC) analysis showed consistency with this behavior. [ABSTRACT FROM AUTHOR]

Highlights • HRMAS-NMR identifies the primary metabolome of Aglianicone grape berries pulp. • Diagnostic compounds were found to correlate with both terroir and vintage effect. • EMI-detected spatial soil-variability correlates with the grapes pulp metabolome. • The reported results are relevant because derive from plants grown in real field. • The HRMAS-EMI method may also serve to assess the quality of other agrofood products. Abstract Aglianicone is an autochthonous variety of black berried wine grape cultivated exclusively in southern Italy, but with limited information on the molecular composition of its grapes. HRMAS NMR spectroscopy was used to identify the primary metabolome of Aglianicone grape pulp from two different vineyards and the observed metabolomic changes reflected the local terroir conditions or harvesting years. Moreover, the berries pulp metabolome was related to Apparent Electrical Conductivity (ECa) maps deriving from on-site near-surface geophysical measurements of vineyard soils obtained by an electromagnetic induction (EMI) technique. Most of primary metabolites of Aglianicone grape varied systematically as a function of the spatial variability of soil properties as well as vineyards terroir and harvesting years. Therefore, the proposed approach that couples HRMAS NMR spectroscopy with ECa maps of vineyard soils represents an innovative support for wine producers who can select the best vine/soil combination to ensure the maximum wine quality. [ABSTRACT FROM AUTHOR]

Highlights • The use of FT-NIR or FT-MIR spectroscopy was evaluated for OTA analysis in wheat. • PLS-DA and PC-LDA chemometric models were compared for samples classification. • FT-MIR classification models showed the best predictive performances. Abstract The use of infrared spectroscopy for the screening of 229 unprocessed durum wheat samples naturally contaminated with OTA has been investigated. Samples were analysed by both Fourier Transform near- and mid-infrared spectroscopy (FT-NIR, FT-MIR). Partial-Least Squares-Discriminant Analysis (PLS-DA) and Principal Component-Linear Discriminant Analysis (PC-LDA) classification models were used to differentiate highly contaminated durum wheat samples from low contaminated ones and the performances of the resulting models were compared. The overall discrimination rates were higher than 94% for both FT-NIR and FT-MIR range by using a cut-off limit set at 2 µg/kg OTA, independently from the classification model used thus confirming the reliability of the two statistical approaches used. False compliant rates of 6% were obtained for both spectral ranges and both classification models. These findings indicate that FT-NIR, as well as FT-MIR analysis, might be a promising, inexpensive and easy-to-use screening tool to rapidly discriminate unprocessed wheat samples for OTA content. [ABSTRACT FROM AUTHOR]

Highlights • Cereal lipids were analysed using GC/Q-TOF MS. • Differences in sterol, tocopherol and alkylresorcinol patterns could be observed. • Novel tocomonoenols and methyl-alkylresorcinols were detected. • The cereals could be discriminated by PCA based on non-targeted lipid profiles. • Non-targeted lipid profiling could be a new tool for cereal authenticity. Abstract Minor lipids in cereals (such as phytosterols and alkylresorcinols) can be important for human nutrition and/or be used as biomarkers for cereal intake. However, the analysis of cereal lipids is very challenging due to the complex lipidome comprising several hundred individual compounds present over a wide range of concentrations. Here we present a method for the profiling of cereal lipids using high temperature gas chromatography coupled to high resolution mass spectrometry (GC/Q-TOF MS). The method was used to investigate the lipid profiles of 77 samples of bread wheat, spelt, einkorn, emmer, barley, rye and oats. Distinct differences in the patterns of alkylresorcinols, free and conjugated sterols and tocopherols between the cereals could be observed. Furthermore, traces of tocomonoenols and diunsaturated and methyl-alkylresorcinols (not previously reported in cereals) could be detected. Finally, the lipid patterns in the cereals could be used to separate the cereals by Principal Component Analysis. [ABSTRACT FROM AUTHOR]

Highlights • The hardness of lotus rhizomes is significantly changed by cooking. • The changes of pectin are accompanied by changes of hardness. • Hardness change of lotus rhizomes is highly related to chelate-soluble pectin. Abstract The differences in cell wall polysaccharides are considered as a major influencing factor on the texture of plant-based food after cooking. Here, 18 varieties of lotus rhizomes were collected from different regions of China and subjected to analysis, with the aim to identify the key factors that affect the texture of lotus rhizomes after cooking. The texture (hardness) of fresh samples and the samples after thermal treatment for different time periods was examined. The cell wall polysaccharides present in alcohol insoluble residue (AIR) were further subdivided into different fractions, and the composition of monosaccharides in each fraction was analyzed by gas chromatography. We then calculated the sugar ratios to examine the discrepancies in molecular structure among the fractions. Principal component analysis and regression analysis showed that the ratio of chelate-soluble fraction (CSF) to AIR is the major factor affecting the texture of lotus rhizomes after cooking. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The pure MP gelation had a loose and dispersed network with interconnected water channels. • The MP gelation was significantly improved by IDF addition. • IDF addition eliminate interconnected water channels in the gelation network. • The IDF addition promoted to the protein aggregation during thermal process. Abstract The effects of insoluble dietary fiber (IDF) on heat-induced gelation properties, such as microstructural changes and the molecular conformation of myofibrillar proteins (MP), were analyzed by image analyses and Raman spectroscopy. Scanning electron microscopy revealed that pure MP gelation contained a loose and dispersed network with interconnected water channels. With IDF addition, the lacunarity and the particle size of water pores both significantly decreased (P < 0.05) and fractal dimension significantly increased (P < 0.05), which indicated the formation of a homogenous and compact three-dimensional network. Through Raman spectra, IDF addition resulted in modification of amide I and III regions, by a significant decrease in α-helix content, accompanied by an increase of β-sheets, β-turns, and random coil content (P < 0.05); the intensity of CU+005CH stretching vibrations bending vibrations bands were significantly decreased (P < 0.05). Principal component analyses showed significant correlations between textual property, microstructure and molecular conformations. Cluster analyses indicated IDF improved the functionality of MP gel by 1): IDF stable the moisture phase 2) "concentrated" MP promoted structural integrity and compact gelation. [ABSTRACT FROM AUTHOR]

Highlights • Phenolic profile and contents largely influenced by extracting conditions. • Phenolic compounds and antioxidant capacity higher with increased SC-CO 2 pressures. • Isohydroxymatairesinol is the main phenolic compound obtained by SC-CO 2. • 3-Vinylphenol is the predominant compound in oils after conventional extraction. • Phenolic compounds extracted by SC-CO 2 more strongly associated with TEAC values. Abstract In this study, the effect of different supercritical CO 2 (SC-CO 2) pressures (10–40 MPa) on phenolic compounds extraction in oils obtained from " horchata " by-products was evaluated, and the results were compared to those obtained after conventional oil extraction (CE). Moreover, the relationship between the individual phenolic compounds and the total antioxidant capacity as well as oil oxidative quality parameters was compared. The phenolic profile and contents were largely influenced by extracting conditions. The main phenolic compound obtained by SC-CO 2 was the isohydroxymatairesinol, particularly at 30 and 40 MPa, while 3-vinylphenol was the predominant compound in oils extracted by CE procedure. Increasing SC-CO 2 extraction pressures enhanced the extraction of phenolic compounds, along with improving the antioxidant capacity and oxidative quality of extracted oil. The principal component analysis indicated that the main phenolic compounds associated with TEAC values were those extracted by SC-CO 2 , which were inversely correlated to oxidative indexes. [ABSTRACT FROM AUTHOR]

Highlights • Brazilian soft drinks could be differenced by chemometric tools. • PCA and ANN were compared in the pattern recognition capacity. • PCA and ANN were able to extract relevant information from soft drink samples. Abstract This study approaches the determination of nine elements from Brazilian carbonated soft drinks of several flavors and manufactures using inductively coupled plasma optical emission spectrometry (ICP OES). The concentrations of the elements varied as follows: (in µg L−1: Cu: 4.00–78.0; Fe: 74.0–506; Mn: 20.0–66.0; Zn: 104–584) and (in mg L−1: Ca: 4.81–16.2; K: 6.73–260; Na: 26.0–175; S: 1.43–5.41; P: 0.186–219). Principal component analysis has shown some tendencies to form two groups according to the drink flavor (orange and cola), but only cola presented a clear and complete separation. Using Kohonen maps, it was observed a tendency to form three flavor groups: (i) cola, (ii) orange and lemon, and (iii) guarana. However, this last tool proved to be more accurate in the groups' formation. [ABSTRACT FROM AUTHOR]

Highlights • Bivalve molluscs species were analyzed by ICP OES and ICP-MS. • Most Lucina pectinata samples had higher concentrations of Cu, Cr and Pb. • Concentrations of As obtained in most samples were above the legal limit recommended by ANVISA. • PCA and HCA showed separation between Lucina pectinata and Trachycardium muricatum species. Abstract Four species of bivalve molluscs (Anomalocardia brasiliana , Iphigenia brasiliana , Lucina pectinata and Trachycardium muricatum) were collected in the Todos os Santos Bay (TSB), Bahia, Brazil, in order to evaluate As, Cd, Co, Cu, Cr, Fe, Mn, Ni, Pb, Se, V and Zn levels and, consequently, the risk of bivalve mollusc consumption in humans. The samples were analyzed by inductively coupled plasma optical emission spectrometry (ICP OES) and inductively coupled plasma mass spectrometry (ICP-MS) after closed-vessel microwave digestion. The accuracy was confirmed using the certified reference materials of oyster tissue (NIST 1566b) and mussel tissue (NIST 2977), and the results were statistically equivalent to the certified values. Application of principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed a tendency to form two groups between samples of Lucina pectinata and Trachycardium muricatum. All species showed As and Cr concentrations higher than the maximum tolerable limit specified in Brazilian legislation. [ABSTRACT FROM AUTHOR]

Highlights • Determination of 13 bioactive phenolic compounds. • Analises of Mango samples (Mangifera indica L.) development, validation and application of a fast and efficient analytical method by HPLC-DAD. • Application of PCA and ANN, for correlation between the origin, type and fraction and the sample discrimination. Abstract A method using reversed-phase high-performance liquid chromatography with diode array detection (HPLC-DAD) was applied after extraction with acidified methanol, to determine 12 bioactive phenolic compounds in the peel and pulp of the mango fruit (Mangifera indica L.) cultivated in the Bahia, state of Brazil. The proposed methodology was previously fully validated and proven successful in the analysis of methanolic extracts of lyophilized samples. The limits of quantification ranged between 0.78 and 3.14 mg L−1 and the individual recovery values obtained for the spiked samples ranged from 80% to 120%. The results were evaluated using PCA and ANN. The results indicate that the fruits are rich in polyphenols, mainly: ellagic acid, gallic acid, rutin and catechin, which contribute to their greater use as functional foods, natural antioxidants and in the pharmaceutical industry, as well as other applications. [ABSTRACT FROM AUTHOR]

Highlights • Crude yields are correlated with coumarin absorbances in summer, winter and spring. • Organic and polar fraction yields correlate with coumarin UV–vis absorbance. • Significant seasonal and solvent effects for crude and fractional yields. • Best solvent extractor varies depending on harvest season. Abstract Statistical mixture design extraction and fractionation of Mikania plant samples were carried out to quantitatively study seasonal and solvent composition effects as well as their interactions on secondary metabolites. The mixture design consisted of ethanol, acetone, dichloromethane and chloroform solvents and their binary, ternary and quaternary mixtures. Yields were measured for the crude extract and its neutral, organic, basic, polar and fiber fractions obtained with each solvent composition from samples harvested during 2010. Two-way ANOVA found statistically significant seasonal and solvent effects for the crude extract and all the fractions except for the polar fraction solvent. The best solvent extractor depends the harvest season. High crude, organic and polar fraction yields in the summer are correlated with the coumarin UV–vis absorbance at 274 nm. Crude yields of mixtures containing ethanol are correlated with the coumarin absorbances in summer, winter and spring whereas mixtures without ethanol show no significant correlation. [ABSTRACT FROM AUTHOR]

Highlights • Ripening stages showed significant effect on the volatile profiles of jujube fruits. • (E)-2-hexenal was the most abundant component and showed rising trend during ripening. • Jujube at half-red maturity showed better performance in overall flavor quality. • GC–MS coupled with E-nose is an accurate method to identify 4 maturities of jujube. Abstract Volatile profiles of jujube fruits at different ripening stages were characterized by GC–MS and E-nose. Changes in the possible precursors of volatile components were also investigated. Four ripening stages were established: GM, green maturity; YM, yellow maturity; HRM, half-red maturity; RM, red maturity. Fruit maturity showed significant effect on the volatile components and their precursors. (E)-2-hexenal was the most abundant component which showed rising trend from 169.2 μg/kg (GM) to 733.4 μg/kg (RM). Glucose and fructose showed a decreasing tendency during ripening. As the important precursors of jujube flavor, seven fatty acids were identified, the predominant ones were C 16:0 , C 16:1n7 , C 18:1n9c and C 18:2n6c ; twenty-six free amino acids were quantified, in which l -AspNH 2 and l -Pro were the abundant components. Owing to the highest content of total aldehydes (59.33%) and the strongest responses of E-nose, jujubes at HRM stage showed superior overall flavor quality among all the samples. [ABSTRACT FROM AUTHOR]

The aim of this work is the evaluation of quality indicators for the estimation of the shelf life of opened cans using the migration of specific metals as variables. For this reason the determination of targeted analytes such as: Cd, Pb, As, Cu, Cr, Ni, Fe, Mn and Sn in different canned samples (cardoon, tuna, green and red beans, corn, and fungi) by Electrothermal Atomic Absorption Spectrometry (Perkin Elmer, SIMAA 6000) was developed and validated. Statistical analysis was performed using SPSS version 22. Principal component analysis (PCA) and cluster analysis were performed in order to examine the correlation between the content of metals and metalloids and the storage time of opened cans. The results showed that there is a strong correlation between metal concentration and storage time, especially for Fe and Sn. The storage time ranged from hours to days and the vast number of collected data sets, led to reliable conclusions about the evaluation of a new shelf life indicator. Principal component analysis indicated the appropriate storage time for opened cans, where no significant migration was observed. [ABSTRACT FROM AUTHOR]

Food by-products containing bioactive substances have attracted attention due to the possibility of adding values to residues of the food industry. In this work, the extraction of phenolic compounds from pinhão seed coats ( Araucaria angustifolia (Bertol.) Kuntze) using a central composite rotatable design was applied to obtain prediction models for the extract volume yield, total phenolic content, total phenolic acids and total flavonoids. Principal component analysis and hierarchical cluster analysis were implemented showing an evident poor effect of the temperature on phenolic compounds extraction, which is in accordance with the prediction model obtained by the experimental design for total phenolic acids. Volume yield presented a high positive correlation with extraction temperature, followed by solvent composition. Scanning electron microscopy showed that higher temperatures and lower ethanol percentages resulted in highly defibrillated pinhão coats that retained more extract after the extraction process, leading to lower volume yield percentages. [ABSTRACT FROM AUTHOR]

The effects of the concentration of watermelon juice at different temperatures (45, 55, or 65 °C) on the physicochemical and sensory characteristics, antioxidant capacity, and volatile organic compounds (VOCs) of whey-based popsicles were investigated. Total phenolic content, lycopene, citrulline, VOCs, melting rate, instrumental colour, antioxidant capacity, and the sensory characteristics (hedonic test and free listing) were determined. The temperature led to a significant decrease in bioactive compounds (total phenolics, lycopene, and citrulline). The popsicle manufactured with reconstituted watermelon juice concentrated to 60 °Brix at 65 °C presented higher antioxidant capacity and was characterized by the presence of alcohols, aldehydes and ketones and presented a similar acceptance to the untreated popsicle (except for flavour). It is possible to combine whey and concentrated watermelon juice for the manufacture of bioactive-rich popsicles, using the concentration temperature of 65 °C as a suitable processing condition for potential industrial applications. [ABSTRACT FROM AUTHOR]

In this study, we aim to establish a comprehensive spectral database for analysis of edible oils using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). More than 900 edible oil samples, including 30 types of edible oils, were analyzed and compared, and the characteristic peaks and spectral features of each edible oil were obtained. Edible oils were divided into eight groups based on their characteristic spectral patterns and principal component analysis results. An overall correct rate of 97.2% (98.1% for testing set) was obtained for classification of 435 edible oil products using partial least square-discriminant analysis, with nearly 100% correct rate for commonly used edible oils. Differentiation of counterfeit edible oils, repeatedly cooked edible oils and gutter oils from normal edible oils could also be achieved based on the MALDI-MS spectra. The establishment of this spectral database provides reference spectra for spectral comparison and allows rapid classification of edible oils by MALDI-MS. [ABSTRACT FROM AUTHOR]

Anthocyanin composition in forty-five Lycium ruthenicum Murray (LRM) samples grown in China was identified by high-performance liquid chromatography-electrospray ionisation-mass spectrometry (HPLC-ESI-MS) and quantified by HPLC with a diode array detector (HPLC-DAD). The results showed that the overall pattern of anthocyanin composition of LRM from different provinces was the same, while the individual and total anthocyanin concentrations, were significantly different, indicating an important impact of geographical origin on anthocyanin composition, which can be considered as credible indices for LRM classification. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to develop discrimination models for the anthocyanin concentrations. PCA clearly separated the LRM based on its geographical origins. LDA satisfactorily categorized the samples by providing a 100% success rate based on geographical origins. The results obtained could be used to trace the geographical origin of LRM. [ABSTRACT FROM AUTHOR]

Soluble-free, soluble-conjugated, insoluble-bound phenolics and antioxidant activity, flavonoid (TFC), proanthocyanidins (TPAC), anthocyanins and minerals of fifteen whole rice grains with different colors were investigated. Soluble-free protocatechuic and vanillic acids were only quantified in black rice, which had the most quantities. Non-pigmented rice had no detectable conjugated protocatechuic and 2,5 -dihydroxybenzoic acids both of which were found in black and red rice, respectively. The main bound phenolic acids were ferulic and p -coumaric, as well as 2,5 -dihydroxybenzoic in red rice and protocatechuic and vanillic acids in black rice. Soluble-conjugated phenolics, TFC, and anthocyanins were negatively correlated with L ∗ , b ∗ , C and H ° values. TPAC was positively correlated with a ∗ ( P < 0.01). Protocatechuic, vanillic, syringic and ferulic acids were associated with TPC and antioxidant activity in the soluble-conjugated fraction while protocatechuic and ferulic acid were correlated with those in the insoluble-bound fraction. Principal component analysis divided samples into non-pigmented, red and black rice groups. [ABSTRACT FROM AUTHOR]

The degradation of catechins and other phenolics in green tea infusions were monitored using fast HPLC/MS separation. The final separation was performed within 2.5 min using Ascentis Express C18 column (50 mm × 2.1 mm i.d.) packed with 2 μm porous shell particles. Degradation was studied in relation to the temperature of water (70, 80, 90 °C) and the standing time of the infusion (up to 6 h). Along with chromatographic separation, the antioxidant properties of the infusions were monitored using two spectrophotometric methods. During staying of green tea infusion, the degradation of some catechins probably to gallic acid was observed. Finally, the influence of tea bag storage on antioxidant properties of green tea was evaluated. Rapid degradation of antioxidants after 3 weeks was observed. The principal component analysis, factor analysis and discriminant analysis were used for the statistical evaluation of obtained experimental data. [ABSTRACT FROM AUTHOR]

Arsenic speciation and heavy metal distributions have been investigated in locally grown rice grains from Guangdong Province, Southern China. A total of 41 polished rice grain samples were collected throughout Guangdong Province. Arsenite (As(III)), as the predominant form found in the rice, was positively correlated ( p < 0.01) with total As (tAs) concentration. However, the percentage of As(III) reduced while tAs concentration increased (r = −0.361, p < 0.05), due to restricted accumulation and translocation of As(III) in rice grains at high level of tAs. Statistical and geostatistical analyses were applied to investigate potential origins of heavy metals in rice. Only Cd, Cu and Ni were identified as influenced by anthropogenic sources such as industrial and commercial activities. As and Pb were primarily controlled by natural occurrence. The results of health risk assessment implied that continuous intake of rice grown in Guangdong Province could cause considerably non-carcinogenic and carcinogenic risk to local inhabitants. [ABSTRACT FROM AUTHOR]

Determination of metabolic alterations in apples induced by such processes as different crop protection strategies or storage, are of interest to assess correlations with fruit quality or fruit disorders. Preliminary results proposed the metabolic discrimination of apples from organic (BIO), integrated (IP) and low-input (LI) production. To determine contributions of temporal metabolic developments and to define the type of metabolic changes during storage, 1 H high resolution-magic angle spinning (HR-MAS) NMR spectroscopy of apple pulp was performed before and after two time points of controlled atmosphere storage. Statistical analysis revealed similar metabolic changes over time for IP-, LI- and BIO-samples, mainly decreasing lipid and sucrose, and increasing fructose, glucose and acetaldehyde levels, which are potential contributors to fruit aroma. Across the production systems, BIO apples had consistently higher levels of fructose and monomeric phenolic compounds but lower levels of condensed polyphenols than LI and IP apples, while the remaining metabolites assimilated. [ABSTRACT FROM AUTHOR]