Evaluation of instrumental methods for the untargeted analysis of chemical stimuli of orange juice flavour

Application of Data Fusion in Traditional Chinese Medicine: A Review

Traditional Chinese medicine is characterized by numerous chemical constituents, complex components, and unpredictable interactions among constituents. Therefore, a single analytical technique is usually unable to obtain comprehensive chemical information. Data fusion is an information processing technology that can improve the accuracy of test results by fusing data from multiple devices, which has a broad application prospect by utilizing chemometrics methods, adopting low-level, mid-level, and high-level data fusion techniques, and establishing final classification or prediction models. This paper summarizes the current status of the application of data fusion strategies based on spectroscopy, mass spectrometry, chromatography, and sensor technologies in traditional Chinese medicine (TCM) in light of the latest research progress of data fusion technology at home and abroad. It also gives an outlook on the development of data fusion technology in TCM analysis to provide references for the research and development of TCM.

Identification of compounds that enhance bitterness of coffee brew

The bitterness perception of coffee is a key attribute that impacts consumer acceptance. Nontargeted liquid chromatography/mass spectrometry (LC/MS) flavoromics analysis was applied to identify compounds that enhance the bitter perception of roasted coffee brew. Orthogonal partial least squares (OPLS) analysis was used to model the comprehensive chemical profiles and sensory bitter intensity ratings of fourteen coffee brews with good fit and predictivity. Five compounds that were highly predictive and positively correlated to bitter intensity were selected from the OPLS model, further isolated, and purified using preparative LC fractionation. Sensory recombination testing demonstrated that five compounds significantly enhanced the bitter perception of coffee when presented as a mixture, but not when presented individually. In addition, a set of roasting experiments revealed the five compounds were generated during the coffee roasting process.

Corylus avellana L. Aroma Blueprint: Potent Odorants Signatures in the Volatilome of High Quality Hazelnuts

The volatilome of hazelnuts (Corylus avellana L.) encrypts information about phenotype expression as a function of cultivar/origin, post-harvest practices, and their impact on primary metabolome, storage conditions and shelf-life, spoilage, and quality deterioration. Moreover, within the bulk of detectable volatiles, just a few of them play a key role in defining distinctive aroma (i.e., aroma blueprint) and conferring characteristic hedonic profile. In particular, in raw hazelnuts, key-odorants as defined by sensomics are: 2,3-diethyl-5-methylpyrazine (musty and nutty); 2-acetyl-1,4,5,6-tetrahydropyridine (caramel); 2-acetyl-1-pyrroline (popcorn-like); 2-acetyl-3,4,5,6-tetrahydropyridine (roasted, caramel); 3-(methylthio)-propanal (cooked potato); 3-(methylthio)propionaldehyde (musty, earthy); 3,7-dimethylocta-1,6-dien-3-ol/linalool (citrus, floral); 3-methyl-4-heptanone (fruity, nutty); and 5-methyl-(E)-2-hepten-4-one (nutty, fruity). Dry-roasting on hazelnut kernels triggers the formation of additional potent odorants, likely contributing to the pleasant aroma of roasted nuts. Whiting the newly formed aromas, 2,3-pentanedione (buttery); 2-propionyl-1-pyrroline (popcorn-like); 3-methylbutanal; (malty); 4-hydroxy-2,5-dimethyl-3(2H)-furanone (caramel); dimethyl trisulfide (sulfurous, cabbage) are worthy to be mentioned. The review focuses on high-quality hazelnuts adopted as premium primary material by the confectionery industry. Information on primary and secondary/specialized metabolites distribution introduces more specialized sections focused on volatilome chemical dimensions and their correlation to cultivar/origin, post-harvest practices and storage, and spoilage phenomena. Sensory-driven studies, based on sensomic principles, provide insights on the aroma blueprint of raw and roasted hazelnuts while robust correlations between non-volatile precursors and key-aroma compounds pose solid foundations to the conceptualization of aroma potential.

Comparative Investigation of Combined Metabolomics-Flavoromics during the Ripening of Mango (Mangifera indica L.) cv. 'Nam Dok Mai Si Thong' and 'Nam Dok Mai No. 4'

A metabolomics-flavoromics approach was conducted to assess the micromolecules of 'Nam Dok Mai Si Thong' and 'Nam Dok Mai No. 4' mango cultivars from two seasons. During ripening, FAMEs, FFAs, fatty alcohols, sterols, and organic acids were dominant at 0-2 days, whereas amino acids, sugars, and volatile organic compounds, including esters, alcohols, ketones, aldehydes, and terpenes, were at higher levels at 4-8 days. Nine metabolites (palmitic/linoleic/linolenic/citric/malic acids, β-sitosterol, sucrose, glycine, and leucine) and two volatile organic compounds (ethyl octanoate/decanoate) were related to ripening-associated changes within eight days. During ripening, sucrose at 6-8 days, citric/malic acid at 0-2 days, glycine and leucine at 4 days, and ethyl octanoate and ethyl decanoate at 8 days could be used as quality biomarkers for Nam Dok Mai Si Thong; palmitic/linoleic/linolenic acids at 0 days and β-sitosterol at 0-4 days could be used as quality biomarkers for Nam Dok Mai No. 4.

Chromatographic Fingerprinting Strategy to Delineate Chemical Patterns Correlated to Coffee Odor and Taste Attributes

Coffee cupping includes both aroma and taste, and its evaluation considers several different attributes simultaneously to define flavor quality and therefore requires complementary data from aroma and taste. This study investigates the potential and limits of a data-driven approach to describe the sensory quality of coffee using complementary analytical techniques usually available in routine quality control laboratories. Coffee flavor chemical data from 155 samples were obtained by analyzing volatile (headspace-solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS)) and nonvolatile (liquid chromatography-ultraviolet/diode array detector (LC-UV/DAD)) fractions, as well as from sensory data. Chemometric tools were used to explore the data sets, select relevant features, predict sensory scores, and investigate the networks between features. A comparison of the Q model parameter and root-mean-squared error prediction (RMSEP) highlights the variable influence that the nonvolatile fraction has on prediction, showing that it has a higher impact on describing acid, bitter, and woody notes than on flowery and fruity. The data fusion emphasized the aroma contribution to driving sensory perceptions, although the correlative networks highlighted from the volatile and nonvolatile data deserve a thorough investigation to verify the potential of odor-taste integration.

Chemical fingerprinting strategies based on comprehensive two-dimensional gas chromatography combined with gas chromatography-olfactometry to capture the unique signature of Piemonte peppermint essential oil (Mentha x piperita var Italo-Mitcham)

Accurate, reliable, and informative mapping of untargeted and targeted components across many samples is here performed by combining off-line GC-Olfactometry (GC-O) and comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry with variable ionization energy (TOF MS featuring Tandem Ionization™). In particular, untargeted and targeted (UT) features patterns are processed by chromatographic fingerprinting, giving differential priority to potent odorants' retention-times regions. Distinguishing peppermint essential oil (EO) from Piedmont (Italy - Mentha × piperita L. var. Italo-Mitcham - Menta di Pancalieri EO), with its unique sensory fingerprint (i.e., freshness and long-lasting sweetness), from high-quality peppermint EOs produced in other areas poses a great challenge. Chromatographic UT fingerprinting provided a great chemical dimensionality by mapping more than 350 peak-regions at 70 eV and 135 at 12 eV. From them, 95 components were identified and responses compared to available literature. Then, potent odorants, detected by GC-O using the aroma extraction dilution analysis (AEDA), were tracked over the chromatographic space and tentatively identified. With the highest flavor dilution (FD), 1,8-cineole (eucalyptus, fresh, camphoraceous); menthone (minty, herbaceous); and menthofuran (minty, musty, petroleum-like) were highlighted. Responsible for creamy and coumarinic notes were the diasteroisomers of (3,6)-dimethyl-4,5,6,7-tetrahydrobenzo[b]-furan-2(3H)-one (i.e., menthofurolactones), detected in higher relative abundance in Pancalieri EOs. By prioritizing the investigation of volatiles on higher LogFD retention regions, including 131 untargeted/targeted features, Pancalieri EOs were separately clustered from United States samples. Besides pre-targeted analytes, additional untargeted features were post-processed for identification within marker chemicals. Myrtenyl methyl ether, ethyl 3-methyl butanoate, propyl-2-methylbutanoate, and (E)-2-hexenal were putatively identified. Of the "unknown - knowns" with diagnostic roles, all metadata were collected including low energy spectra at 12 eV, which were found to be highly complementary to 70 eV spectra.

Identification of key odorants in complex mixtures occurring in nature

Covering: up to 2019Soon after the birth of gas chromatography, mass spectrometry and olfactometry were used as detectors, which allowed impressive development to be achieved in the area of odorant determinations. Since the mid-80s, structured methods of gas chromatography-olfactometry have appeared, allowing the determination of which odor constituents play a key role in materials. Progressively, numerous strategies have been proposed for sample preparation from raw materials, the representativeness evaluation of extracts, the identification of odor constituents, their quantification, and subsequently, the recombination of the key odorants to mimic the initial odor. However, the multiplicity of options at each stage of the analysis leads to a confusing landscape in this field, and thus, the present review aims at critically presenting the available options. For each step, the most frequently used alternatives are described, together with their strengths and weaknesses based on theoretical and experimental justifications according to the literature. These techniques are exemplified by many applications in the literature on aromas, fragrances and essential oils, with the initial focus on wine odorants, followed by a short overview on the molecular diversity of key odorants, which illustrates most of the facets and complexities of odor studies, including the issues raised by odorant interactions such as synergies.

Effects of Scion/Rootstock Combination on Flavor Quality of Orange Juice from Huanglongbing (HLB)-Affected Trees: A Two-Year Study of the Targeted Metabolomics

The bacterial disease Huanglongbing (HLB) has been causing large economic losses in the citrus industry worldwide. Aimed at unraveling the mechanisms of scion/rootstock combination on improving HLB-affected orange juice quality, a specific scion/rootstock combination field trial was designed using three sibling rootstocks and two late-maturing sweet orange scion cultivars. Scion/rootstock combination significantly improved the overall consumer liking of orange juice from the HLB-affected trees. Rootstocks showed significant effects on the consumer liking and overall flavor, while scions had significant effects on the freshness and overall orange flavor intensity of the juice. A PLS-DA model combined with KEGG pathway enrichment analysis and some biomarker metabolites further indicated that scions mainly affected metabolism of alanine, aspartate, and glutamate in orange fruits. Meanwhile, rootstocks had an impact on the biosynthetic pathways of secondary metabolites. Sugars and organic acids were not closely correlated with the overall liking and sensory perception of orange juice. Rather, flavonoids, terpenoids, and volatile aromas played important roles in improving consumer overall liking. These results indicated that an optimum tolerant scion/rootstock combination can make a positive contribution toward improved fruit or juice quality from HLB-affected citrus trees.

Influence of Roasting Condition on Flavor Profile of Sunflower Seeds: A flavoromics approach

Sunflower see/ds (Helianthus annuus L.) were roasted in an electric forced air oven for 15, 30, 45, and 60 min at 125, 135 and 145 °C. The effect of temperature and time on the flavor profile of the samples were evaluated by headspace solid-phase microextraction coupled with gas chromatography-mass spectroscopy (HS-SPME-GC-MS). Unsupervised Principle Component Analysis (PCA) and Agglomerative Hierarchical Clustering (AHC) multivariate statistical methods were used to visualize, group and classify the samples. 114 volatiles were identified in the roasted sunflower seeds (RSF), with terpenes (α-pinene, β-pinene), heterocyclic compounds (2-ethyl-3-methylpyrazine, 2,5-dimethylpyrazine, 2-ethyl-3,5-dimethylpyrazine, pyridine), aldehydes (2-methylbutanal, furfural, hexanal, phenylacetaldehyde), hydrocarbons (octane, 2-isobutyl-1,4-dimethylcyclohexane, 6,6-dimethylundecane), alcohol (3-methyl-2-propyl-1-pentanol), and γ-butyrolactone being dominant compounds. The content of most volatile compounds increased with increase in roasting temperature and time, such as esters, terpenes, pyrazines, aldehydes, ketones, and alcohols. 2,3-dimethylpyrazine, 2,5-dimethylpyrazine, 2-ethyl-3-methylpyrazine, and 2-ethyl-3,5-dimethylpyrazine contributed to be the major role in roast and nutty flavor of the roasted sunflower seeds. Roasting at 125 °C for 45 min was found to be the better condition for roasted sunflower seeds, which gave the lowest off-flavor and burnt tastes.

Relationship between Sensory Attributes and Chemical Composition of Different Mango Cultivars

The present study investigated the relationship between the chemical composition and sensory quality of different mango ( Mangifera indica L.) cultivars by multivariate statistical analysis. The results showed that the high hedonic rating of mangoes was due in part to its flavor profile such as fruity, pineapple, and coconut with sweetness. High hedonic liking and positive flavors of mangoes could be responsible for the volatile compounds including fruity esters, 1-octanol, ( E, Z)-2,6-nonadienal, and γ-octalactone with high contents of sugars. On the other hand, turpentine-like and green flavors of mangoes are attributed to the relatively low hedonic liking of mangoes, which correlated with high contents of amino acids and terpenes. These findings demonstrated that interaction between individual chemical compounds within mangoes could be responsible for the specific sensory qualities of mango cultivars and provided insight into a paradigm for the selection and development of new and more desirable mango cultivars in the future.

Identification and Validation of Sensory-Active Compounds from Data-Driven Research: A Flavoromics Approach

In this study, highly predictive LC-MS features (retention time_ m/ z) derived from untargeted chemical fingerprinting-multivariate analysis (MVA) previously used to model flavor changes in citrus fruits related to aging (freshness) were further isolated and analyzed for sensory impact, followed by structural elucidation. The top 10 statistical features from two MVA approaches, partial least-squares data analysis (PLS-DA) and Random Forrest (RF), were purified to approximately 70% via multidimensional liquid chromatography-mass-directed fractionation to screen for sensory activity. When added to a 'fresh' orange flavor model system, 50-60% of the isolates were reported to cause a sensory change. From the subset of the actives identified, two compounds were selected, on the basis of statistical relevance, that were further purified to >97% for identification (MS, NMR) and for sensory descriptive analysis (DA). The compounds were identified as nomilin glucoside and a novel ionone glucoside. DA evaluation in the recombination orange model indicated both compounds statistically suppressed the perceived intensity of the "orange character" attribute, whereas the novel ionone glycoside also decreased the intensity of the floral character while increasing the green bean attribute intensity.

Current Developments in Analyzing Food Volatiles by Multidimensional Gas Chromatographic Techniques

This paper presents current developments and future perspectives on the spread of advanced analytical tasks in the field of food volatile analysis. The topics outlined comprise (a) recent advances on miniaturized sampling techniques; (b) the potential and challenges of multidimensional gas chromatography coupled with mass spectrometric detection for volatile identification and quantitation in samples with complex matrices;

Identification of Aging-Associated Food Quality Changes in Citrus Products Using Untargeted Chemical Profiling

Chemometric techniques have seen wide application in biological and medical sciences, but they are still developing in the food sciences. This study illustrated the use of untargeted LC/MS chemometric methods to identify features (retention time_m/z) associated with food quality changes as products age (freshness). Extracts of three citrus fruit varietals aged over four time points that corresponded to noted changes in sensory attributes were chemically profiled and modeled by two discriminatory multivariate statistical techniques, projection partial least-squares discrimant analysis (PLS-DA) and machine learning random forest (RF). Age-associated compounds across the citrus platform were identified. Varietal was treated as a nuisance variable to emphasize aging chemistry, and further variable selection using age-related piecewise model generation and meta filtering to emphasize features associated with general aging chemistry common to all the citrus extracts. The identified features were further replicated in a validation study to illustrate the validity and persistence of these markers for applications in citrus food platforms.

Data fusion methodologies for food and beverage authentication and quality assessment - a review

The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.