Development of an Unified Food Composition Database for the European Project "Stance4Health".

The European Commission funded project Stance4Health (S4H) aims to develop a complete personalised nutrition service. In order to succeed, sources of information on nutritional composition and other characteristics of foods need to be as comprehensive as possible. Food composition tables or databases (FCT/FCDB) are the most commonly used tools for this purpose. The aim of this study is to describe the harmonisation efforts carried out to obtain the Stance4Health FCDB. A total of 10 FCT/FCDB were selected from different countries and organizations. Data were classified using FoodEx2 and INFOODS tagnames to harmonise the information. Hazard analysis and critical control points analysis was applied as the quality control method. Data were processed by spreadsheets and MySQL. S4H's FCDB is composed of 880 elements, including nutrients and bioactive compounds. A total of 2648 unified foods were used to complete the missing values of the national FCDB used. Recipes and dishes were estimated following EuroFIR standards via linked tables. S4H's FCDB will be part of the smartphone app developed in the framework of the Stance4Health European project, which will be used in different personalized nutrition intervention studies. S4H FCDB has great perspectives, being one of the most complete in terms of number of harmonized foods, nutrients and bioactive compounds included.

GC-FID-MS Based Metabolomics to Access Plum Brandy Quality.

Plum brandy (Slivovitz (en); Sljivovica(sr)) is an alcoholic beverage that is increasingly consumed all over the world. Its quality assessment has become of great importance. In our study, the main volatiles and aroma compounds of 108 non-aged plum brandies originating from three plum cultivars, and fermented using different conditions, were investigated. The chemical profiles obtained after two-step GC-FID-MS analysis were subjected to multivariate data analysis to reveal the peculiarity in different cultivars and fermentation process. Correlation of plum brandy chemical composition with its sensory characteristics obtained by expert commission was also performed. The utilization of PCA and OPLS-DA multivariate analysis methods on GC-FID-MS, enabled discrimination of brandy samples based on differences in plum varieties, pH of plum mash, and addition of selected yeast or enzymes during fermentation. The correlation of brandy GC-FID-MS profiles with their sensory properties was achieved by OPLS multivariate analysis. Proposed workflow confirmed the potential of GC-FID-MS in combination with multivariate data analysis that can be applied to assess the plum brandy quality.

Intra-Laboratory Validation of Alpha-Galactosidase Activity Measurement in Dietary Supplements.

INTRODUCTION: Alpha-galactosidase (α-Gal) is an enzyme responsible for the hydrolyzation of glycolipids and glycoprotein commonly found in dietary sources. More than 20% of the general population suffers from abdominal pain or discomfort caused by intestinal gas and by indigested or partially digested food residuals. Therefore, α-Gal is used in dietary supplements to reduce intestinal gases and help complex food digestion. Marketed enzyme-containing dietary supplements must be produced in accordance with the Food and Drug Administration (FDA) regulations for Current Good Manufacturing Practice (cGMPs). AIM: in this work we illustrated the process used to develop and validate a spectrophotometric enzymatic assay for α-Gal activity quantification in dietary supplements. METHODS: The validation workflow included an initial statistical-phase optimization of materials, reagents, and conditions, and subsequently a comparative study with another fluorimetric assay. A final validation of method performance in terms of specificity, linearity, accuracy, intermediate-precision repeatability, and system precision was then executed. RESULTS AND CONCLUSIONS: The proven method achieved good performance in the quantitative determination of α-Gal activity in commercial food supplements in accordance with the International Council for Harmonisation of Technical Requirements for Pharmaceuticals (ICH) guidelines and is suitable as a rapid in-house quality control test.

Quantitative analysis of blended oils by matrix-assisted laser desorption/ionization mass spectrometry and partial least squares regression.

Quantitative labeling of oil compositions has become a trend to ensure the quality and safety of blended oils in the market. However, methods for rapid and reliable quantitation of blended oils are still not available. In this study, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) was used to profile triacylglycerols in blended oils, and partial least squares regression (PLS-R) was applied to establish quantitative models based on the acquired MALDI-MS spectra. We demonstrated that this new method allowed simultaneous quantitation of multiple compositions, and provided good quantitative results of binary, ternary and quaternary blended oils, enabling good limits of detection (e.g., detectability of 1.5% olive oil in sunflower seed oil). Compared with the conventional GC-FID method, this new method could allow direct analysis of blended oils, analysis of one blended oil sample within minutes, and accurate quantitation of low-abundance oil compositions and blended oils with similar fatty acid contents.

The difference of origin and extraction method significantly affects the intrinsic quality of licorice: A new method for quality evaluation of homologous materials of medicine and food.

As a homologous material of both medicine and food, licorice is a famous traditional Chinese medicine. In the application process, different origins and different extraction methods have an impact on the intrinsic quality of licorice. In order to ensure the intrinsic quality of commercially available licorice products, and to explore the influence of origin and extraction methods on the quality of licorice, we put forward a simple and effective discriminatory method for "chemometrics analysis-based fingerprint establishment". First, fingerprints of licorice ethanol extraction (LEE) and licorice water extraction (LWE) were established. Then, similarity analysis (SA), hierarchical clustering analysis (HCA), principal component analysis (PCA) and other chemometrics methods were used to select qualitative and quantitative markers. Besides, the quantitative determination of 7 compounds of licorice with statistical significance was carried out, which provided accurate and informative data for quality evaluation. Finally, discriminant analysis was used to trace the origin of licorice.

Rapid Identification of Different Grades of Huangshan Maofeng Tea Using Ultraviolet Spectrum and Color Difference.

Tea is an important beverage in humans' daily lives. For a long time, tea grade identification relied on sensory evaluation, which requires professional knowledge, so is difficult and troublesome for laypersons. Tea chemical component detection usually involves a series of procedures and multiple steps to obtain the final results. As such, a simple, rapid, and reliable method to judge the quality of tea is needed. Here, we propose a quick method that combines ultraviolet (UV) spectra and color difference to classify tea. The operations are simple and do not involve complex pretreatment. Each method requires only a few seconds for sample detection. In this study, famous Chinese green tea, Huangshan Maofeng, was selected. The traditional detection results of tea chemical components could not be used to directly determine tea grade. Then, digital instrument methods, UV spectrometry and colorimetry, were applied. The principal component analysis (PCA) plots of the single and combined signals of these two instruments showed that samples could be arranged according to grade. The combined signal PCA plot performed better with the sample grade descending in clockwise order. For grade prediction, the random forest (RF) model produced a better effect than the support vector machine (SVM) and the SVM + RF model. In the RF model, the training and testing accuracies of the combined signal were all 1. The grades of all samples were correctly predicted. From the above, the UV spectrum combined with color difference can be used to quickly and accurately classify the grade of Huangshan Maofeng tea. This method considerably increases the convenience of tea grade identification.

Polyphenol composition and biological activity of Thymus citriodorus and Thymus vulgaris: Comparison with endemic Iberian Thymus species.

The polyphenol compositions of Thymus × citriodorus and Thymus vulgaris extracts as obtained by exhaustive hydroethanolic (HE) extraction and aqueous decoction (AD) were compared. In addition, their compositions and bioactivities were compared to those of Thymus pulegioides and Thymus mastichina, grown under the same edaphoclimatic conditions, and Thymus carnosus. Rosmarinic acid was the most abundant polyphenol followed by luteolin-hexuronide, salvianolic acids I and K. Cluster analysis suggests a similarity of the polyphenol composition of T. citriodorus and T. vulgaris. A significant antioxidant activity was observed and correlated with their polyphenol levels. The same being observed for the higher anti-proliferative activity/cytotoxicity of HE extracts on Caco-2 and HepG2 cells as compared to AD extracts. Significant association between the total phenolic compounds with the anti-proliferative activity, for both cell lines, was observed. These results support the importance of salvianolic acids levels in Thymus extracts and their in vitro anti-proliferative/cytotoxic activities.

Using near-infrared hyperspectral imaging with multiple decision tree methods to delineate black tea quality.

The evaluation of tea quality tended to be subjective and empirical by human panel tests currently. A convenient analytical approach without human involvement was developed for the quality assessment of tea with great significance. In this study, near-infrared hyperspectral imaging (HSI) combined with multiple decision tree methods was utilized as an objective analysis tool for delineating black tea quality and rank. Data fusion that integrated texture features based on gray-level co-occurrence matrix (GLCM) and short-wave near-infrared spectral features were as the target characteristic information for modeling. Three different types of supervised decision tree algorithms (fine tree, medium tree, and coarse tree) were proposed for the comparison of the modeling effect. The results indicated that the performance of models was enhanced by the multiple perception feature fusion. The fine tree model based on data fusion obtained the best predictive performance, and the correct classification rate (CCR) of evaluating black tea quality was 93.13% in the prediction process. This work demonstrated that HSI coupled with intelligence algorithms as a rapid and effective strategy could be successfully applied to accurately identify the rank quality of black tea.

A rapid analysis method of safflower (Carthamus tinctorius L.) using combination of computer vision and near-infrared.

The quality of safflower (Carthamus tinctorius L.) in the market is uneven due to the problems of dyeing and adulteration of safflower, and there is no perfect standard for the classification of quality grade of safflower at present. In this study, computer vision (CV) and near-infrared (NIR) were combined to realize the rapid and nondestructive analysis of safflower. First, the partial least squares discrimination analysis (PLS-DA) model was used to qualitatively identify the dyed safflower from 150 samples. Then the partial least squares (PLS) model was used for quantitative analysis of the hydroxy safflower yellow pigment A (HSYA) and water extract of undyed safflower. Herein, the discrimination rate of PLS-DA model reached 100%, and the residual predictive deviation (RPD) values of the PLS models for HSYA and water extract were 2.5046 and 5.6195, respectively. It indicated that the rapid analysis method combining CV and NIR was reliable, and its results can provide important reference for the formulation of safflower quality classification standards in the market.

Determination of tea polyphenols in green tea by homemade color sensitive sensor combined with multivariate analysis.

Tea polyphenols content in green tea has an indirect relationship with the aroma quality of tea. This study innovatively proposed a method for quantitative determination of tea polyphenols in green tea based on the self-developed color sensitive sensor. Firstly, the color sensitive sensor was prepared to acquire the aroma information of green tea. Secondly, color components were extracted and then optimized using ant colony optimization (ACO) algorithm. Finally, extreme learning machine (ELM) model was built using the optimized color feature components for quantitative determination of tea polyphenols content in green tea. Results showed that the correlation coefficient (RP) of the best ELM model is 0.8035, and the root mean square error prediction (RMSEP) is 1.6003% in the validation set. The overall results sufficiently demonstrate that it is feasible to quantitative detect tea polyphenols content in green tea by the homemade color sensitive sensor combined with appropriate chemometrics methods.

Extraction induced by emulsion breaking for As, Se and Hg determination in crude palm oil by vapor generation-AFS.

In this work is presented the development of a method for As and Se determination in crude palm oil samples by hydride generation atomic fluorescence spectrometry and Hg by cold vapor atomic fluorescence spectrometry after ultrasound-assisted emulsification and extraction induced by emulsion breaking (EIEB). The optimization of the method was carried out by multivariate designs. The developed method has presented limits of quantification (LOQ) of 0.72, 0.12, and 1.5 µg L-1 for As, Hg, and Se, respectively. The precisions of the proposed method expressed as repeatability were 0.92, 2.2, and 3.7% RSD for 2 µg L-1 (n = 10) of As, Hg and Se, respectively. The developed methodology was applied in palm oil samples collected in the Bahia State. Concentrations (µg L-1) found in the samples were between

Nutritional adequacy and content of food bank parcels in Oxfordshire, UK: a comparative analysis of independent and organisational provision.

BACKGROUND: Food bank use has increased significantly in the UK. With the rise in demand, it is imperative that users are receiving food parcels that meet their requirements. The present study aimed to explore whether typical food parcels, supplied by The Trussell Trust and independent food banks, were meeting the daily nutrient and energy requirements of an adult user. METHODS: The Trussell Trust (n = 2) and independent food banks (n = 9) were surveyed in Oxfordshire, UK. Data were collected on food bank use, resources, donations and parcel content. The energy and nutrient contents of a representative parcel were compared with the average dietary reference values (DRVs) for an adult. Additional comparisons were made between The Trussell Trust and independent provision. RESULTS: Parcels provided energy, carbohydrate, sugar, protein and fibre contents that significantly exceeded the DRVs. In total, 62.2% of energy was provided as carbohydrate and 569% of the DRV was provided by sugars. The vitamin D and retinol content of the parcels was significantly lower than the DRVs, meeting 25% and 27% of users' needs respectively; provision of all other micronutrients exceeded the DRVs. The Trussell Trust's parcels provided significantly less vitamin D and copper than independent parcels. CONCLUSIONS: Food bank parcels distributed in Oxfordshire, UK, exceeded energy requirements and provided disproportionately high sugar and carbohydrate and inadequate vitamin A and vitamin D compared to the UK guidelines. Improved links with distributors and access to cold food storage facilities would help to address these issues, via increased fresh food provision.

Improved detection of key odourants in Arabica coffee using gas chromatography-olfactometry in combination with low energy electron ionisation gas chromatography-quadrupole time-of-flight mass spectrometry.

Four Arabica coffees (Brazil, Colombia, Ethiopia, and Guatemala) yield highly variant odours, attesting to the complexities of coffee aroma that command advanced analytical tools. In this study, their volatiles were extracted using solvent-assisted flavour evaporation (SAFE) and headspace solid-phase microextraction (HS-SPME). Due to matrix complexity, some trace odourants were detected in SAFE extracts by aroma extract dilution analysis (AEDA) but remained difficult to quantify by gas chromatography-mass spectrometry (GC-MS). This prompted the application of low energy electron ionisation (EI) coupled with GC-quadrupole time-of-flight (GC-QTOF). Optimal low EI GC-QTOF parameters (EI energy: 15 eV, acquisition rate: 3 Hz) were applied to achieve improved molecular ion signal intensity and reproducibility (relative standard deviation < 10%) across five compounds, which resulted in good linearity (R2 ≥ 0.999) and lowered detection levels (e.g. 0.025 ±â€¯0.005 ng/mL for 4-hydroxy-5-methyl-3(2H)-furanone). Therefore, this method potentially improves the measurement of trace odourants in complex matrices by increasing specificity and sensitivity.

Comparison between polyphenol profile and bioactive response in blackthorn (Prunus spinosa L.) genotypes from north Serbia-from raw data to PCA analysis.

The aim of this work was to investigate and compare the phenolic profile of 15 wild growing blackthorn (Prunus spinosa L.) genotypes from the slopes of Fruska Gora mountain in north Serbia. Their effect in inhibiting i) α-amylase and α-glucosidase activities and ii) colorectal cancer cell line (HT29) growth was also studied. Blackthorn fruit extracts exhibited high phenolic content being enrich in anthocyanins. Principal component analysis was used to correlate the bioactive response with phenolic composition. It was found that derivatives quercetin and anthocyanin peonidin are the major contributors of the inhibition of carbohydrates hydrolyzing enzymes as well as with the antiproliferative effect of blackthorn. Among all samples, the genotype from Beska locality showed the higher capacity in inhibiting alpha-amylase, alpha-glucosidase and HT29 cell growth. Because of high anthocyanin content and higher bioactive response, these genotypes could be recommended for the further cultivation and investigation.

Electrochemical impedance spectroscopy characterization of beverages.

This paper compares the results of standard chemical analytical processes and electrochemical impedance spectroscopy (EIS) in the characterization of different beverages, namely ground coffee, soluble coffee, coffee substitutes, barley, cow milk, vegetable drinks, tea, plant infusions and plant mixtures. For the two approaches, the similarities between the experimental data are assessed by means of the Euclidean and Canberra distances. The resulting information is processed by means of the multidimensional scaling (MDS) clustering and visualization algorithm. The results of the chemical analytical processes and EIS reveal identical clusters for the two adopted distances. Furthermore, the robustness of the experimental and computational scheme are assessed by means of the Procrustes technique. The results confirm the effectiveness of combining the EIS and MDS.

Differences in chemical composition predictive of in vitro biological activity among commercially important cultivars of genus Camellia.

Leaves of plants from the genus Camellia (CAM) are used to make tea; however, there are limited data that compares chemical composition and biological activity of CAM cultivars used to make six tea types. Fourteen CAM cultivars were analyzed by HPLC and UPLC-Q-TOF-MS/MS and biological activity was assessed in a cell growth assay. Tea bioactives and cell growth inhibition varied 2-4 fold. EGCG was the dominant catechin that predicted the magnitude of growth inhibition. However, pure EGCG did not fully account for inhibitory activity suggesting that it may serve as a chemical marker for bioefficacy. As an unbiased characterization of differences in chemical composition among CAM, individual metabolomes were determined and used to generate principle components (PC). PC's from the metabolome were complementary to those from targeted analyses of tea bioactives and were predictive of growth inhibition. This study provides a frame work for identifying CAM cultivars with beneficial traits.

Characterization of Brazilian coffee based on isotope ratio mass spectrometry (δ13C, δ18O, δ2H, and δ15N) and supervised chemometrics.

Authentication of ground coffee has become an important issue because of fraudulent activities in the sector. In the current work, sixty-seven Brazilian coffees produced in different geographical origins using organic (ORG, n = 25) and conventional (CONV, n = 42) systems were analyzed for their stable isotope ratios (δ13C, δ18O, δ2H, and δ15N). Data were analyzed by inferential analysis to compare the factors whereas linear discriminant analysis (LDA), k-nearest neighbors (k-NN), and support vector machines (SVM) were used to classify the coffees based on their origin. ORG and CONV cultivated coffees could not be differentiated according to C stable isotope ratio (δ13C; p = 0.204), but ORG coffees presented higher values of the N stable isotope ratio (δ15N; p = 0.0006). k-NN presented the best classification results for both ORG and CONV coffees (87% and 67%, respectively). SVM correctly classified coffees produced in São Paulo (75% accuracy), while LDA correctly classified 71% of coffees produced in Minas Gerais.

Rapid identification and quantification of cheaper vegetable oil adulteration in camellia oil by using excitation-emission matrix fluorescence spectroscopy combined with chemometrics.

Camellia oil is a high quality oil mainly produced in southern China. It is common that unscrupulous merchants attempt to make huge profits by adulterating camellia oil with other cheaper or lower-quality vegetable oils. Therefore, this paper proposed excitation-emission matrix fluorescence spectroscopy combined with chemometric methods for the rapid identification and quantification of camellia oil adulteration with other cheaper vegetable oils. A five-component parallel factor analysis (PARAFAC) model roughly completed spectral characterization of oil samples, and obtained chemically meaningful information. Four advanced chemometrics methods were used for the classification of camellia oil and other vegetable oils (model 1) and the classification of camellia oil and adulterated camellia oil (models 2 and 3), respectively. Two-directional two-dimensional linear discriminant analysis ((2D)2LDA) was used for chemical data for the first time and showed huge potential. Furthermore, the developed N-PLS regression model used for the prediction of adulteration level in camellia oil showed satisfactory accuracy.

Use of liquid chromatography quadrupole time-of-flight mass spectrometry and metabolomic approach to discriminate coffee brewed by different methods.

An untargeted metabolomic method based on UPLC-QTOF were used to investigate the differences in coffee brewed by boiled, pour-over and cold-brew methods here. Distinctive separation among the three groups could be seen from principal component analysis and hierarchical clustering analysis. Analysis of variance, fold change and orthogonal projection to latent structures discriminant mode were conducted to find the characteristic potential markers, subsequently, nine potential markers were putatively identified using general chemical databases, and five of them were further confirmed by acquisition of reference standards. This work provides an efficient way for discrimination of coffee brewed by different methods. Interestingly, the result of this work also suggested that the contents of two selected markers, norharman and harman, were higher in the pour-over and boiled methods, compared to the cold-brew method. This content difference were further verified by the quantitative analysis data of commercial coffee samples.

Cranberries versus lingonberries: A challenging authentication of similar Vaccinium fruit.

Due to unique phytochemicals contained, Vaccinum berries are known to have a number of positive health effects. In this context, lingonberries (Vaccinium vitis-idaea) are considered to be the most effective, thus finding many uses. Recently, fraud suspicion on lingonberries-based products has been reported, partial or even total replacement by less valued cranberries (Vaccinium macrocarpon) was found. In this study, metabolomic fingerprinting employing instrumental platform consisting of U-HPLC-HRMS/MS was investigated for discrimination between the two Vaccinum berries species. Methanolic extracts of 33 authentic samples from two harvest years were analyzed and chemometric evaluation was performed to identify significant marker compounds, their stability during drying process was assessed, too. The characteristic markers most contributing to berries classification were representatives of polyphenols and phospholipids. Peonidin 3-O-arabinoside and myricetin 3-O-glucoside, not occurring in lingonberries, enabled to discover the presence of cranberries in prepared admixtures down to 1% (w/w).