Rum classification using fingerprinting analysis of volatile fraction by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry

Nontargeted analysis and comparison strategies for volatile and semivolatile substances in toys made of different materials

A nontargeted broad-spectrum analysis method for unknown volatile and semivolatile substances in toys was established by gas chromatography-Orbitrap high-resolution mass spectrometry. Based on the NIST spectrum library, unknown substances could be accurately identified by comprehensive scoring, retention index, chemical ionization, and fine comparison of ion fragments. For substances not included in the library, the molecular formulas of unknown substances were retrieved through online compound databases. Possible structural formulas were verified by high-resolution spectra and fragmentation mechanisms. Taking teether toys as an example, the substances differences of products made of different materials were compared through the digitization of chemical composition. Specifically, 59 substances were identified in 50 teether toys. The toys made of two different materials each had their own substance distribution, and the types and quantities of substances in thermoplastic polyurethanes samples were more than those in silicone samples. Substances with high risk included phenol, N-methylaniline, cyclohexanone, and 4-tert-amylphenol. This work can serve as a reference for the identification of unknown substances in toys and other products, as well as for the comparison the chemical composition of products made of different materials. Thus, this work has positive significance in promoting the quality and safety of toys and reducing chemical harm to children.

The Spirit of Cachaça Production: An Umbrella Review of Processes, Flavour, Contaminants and Quality Improvement

This review provides a comprehensive analysis of the production, classification, and quality control of cachaça, a traditional Brazilian sugarcane spirit with significant cultural importance. It explores the fermentation and distillation of sugarcane juice, the ageing process in wooden containers, and the regulatory aspects of cachaça labelling. It emphasises the role of quality control in maintaining the spirit's integrity, focusing on monitoring copper levels in distillation stills. Ethyl carbamate (EC), a potential carcinogen found in cachaça, is investigated, with the study illuminating factors influencing its formation and prevalence and the importance of its vigilant monitoring for ensuring safety and quality. It also underscores the control of multiple parameters in producing high-quality cachaça, including raw material selection, yeast strains, acidity, and contaminants. Further, the impact of ageing, wood cask type, and yeast strains on cachaça quality is examined, along with potential uses of vinasse, a cachaça by-product, in yeast cell biomass production and fertigation. A deeper understanding of the (bio)chemical and microbiological reactions involved in cachaça production is essential to facilitate quality control and standardisation of sensory descriptors, promoting global acceptance of cachaça. Continued research will address safety concerns, improve quality, and support the long-term sustainability and success of the cachaça industry.

Non-targeted analysis of unknown volatile chemicals in medical masks

This paper reports the non-targeted analysis of unknown volatile chemicals in medical masks through headspace gas chromatography-Orbitrap high-resolution mass spectrometry. In view of the difficulties that may be encountered in the qualitative analysis of unknown substances, several typical cases and the corresponding reliable solutions are given from the perspective of comprehensive score and retention index, chemical ionization identification molecular formula, fragment ion detail comparison for distinguishing isomers, and identification of alkanes. With this method, 69 volatile substances were identified in 60 masks. The identified substances were divided into nine categories. Alkanes, esters, benzenes, and alcohols were the top four groups of substances identified in masks and accounted for 34.8%, 15.9%, 10.1%, and 7.2% of the total substances, respectively. In addition, ketones, ethers, phenolics, amides, and other substances were identified. Ethanol, 1,4-dichlorobenzene, toluene, m-xylene, dimethyl glutarate, and N,N-dimethylacetamide had high detection rates. The identified substances were further filtered and screened according to their detection rate, toxicity, and response intensity. Finally, 12 high-risk volatile chemicals in medical masks were listed. This study could serve as a reference for identifying unknown substances and a guide for monitoring volatile chemicals in masks and promoting chemical safety improvements in products.

Sensory and chemical characterization of Chinese bog bilberry wines using Check-all-that-apply method and GC-Quadrupole-MS and GC-Orbitrap-MS analyses

The sensory and chemical profiles of commercial bog bilberry (BB) wines were investigated using a multi-analytical approach. Sensory test included scaling and check-all-that-apply (CATA) method with questions on liking of BB wine. The sensory data was correlated with their volatile compound profiles determined using gas chromatography coupled with quadrupole and orbitrap mass spectrometry (GC-Quadrupole/Orbitrap-MS). In general, all BB wines were characterized with "fruity", "blueberry" and "floral" odors and "sour", "mouth puckering" and "sweet" flavors. Samples more frequently characterized as "fruity" and "floral" in CATA were preferred by the panelists (n = 93). High relative proportions of o-cymene, p-cymenene, 1-octen-3-one and 3-ethylphenol in a sample (described as "ginger" and "chili") resulted in a lower liking rating. Similarly, generally disliked sample described with "Chinese herbs" and "licorice" was characterized by compounds 3-methylpentan-1-ol, 1,1,6-trimethyl-1,2-dihydronaphthalene, and 4-vinylphenol. The data will give novel information for berry wine and beverage industry on the quality factors of BB wines linked to higher acceptance.

Non-targeted identification of unknown chemical hazardous substances in infant teether toys by gas chromatography-Orbitrap high resolution mass spectrometry

Chemical hazardous substances in teethers may migrate into infant's body through oral exposure, resulting in a potential health risk. In recent years, researchers have performed a series of studies for detecting target chemicals in teethers and other toys, but the presence of unknown chemicals has not been systematically investigated yet. This paper reports the non-targeted identification of unknown chemical hazards that may have migrated from teethers to infants based on gas chromatography-Orbitrap high resolution mass spectrometry. In view of the difficulties that may be encountered in the qualitative analysis of substances, several typical cases and the corresponding reliable solutions are given from the perspective of comprehensive score and retention index, isotope-aided qualitative analysis, chemical ionization identification formula, and fragment ion detail comparison for distinguishing isomers. Finally, 28 substances are identified in 10 teether samples. Among them, phenol, N-methylaniline, 1,6-dioxacyclododecane-7,12-dione and cyclohexanone have higher detection rates. This study not only has valuable reference for the identification of unknown substances, but also has positive guiding role in monitoring potential chemical hazards in toys and promoting the safety of products.

Feasibility of Applying Untargeted Metabolomics with GC-Orbitrap-HRMS and Chemometrics for Authentication of Black Pepper (Piper nigrum L.) and Identification of Geographical and Processing Markers

Black pepper is one of the most consumed spices all over the world. Due to its high demand and nutritional value, a metabolomics approach based on GC-Orbitrap-HRMS fingerprinting and chemometrics was applied to assess its geographical traceability and processing authenticity. GC-HRMS-based fingerprints were obtained using a simple ultrasound-assisted extraction method, which may be easily implemented in routine activities of quality control. Unsupervised methods, such as principal component analysis (PCA), were performed for sample overview according to the investigated origins (Brazil, Vietnam, and Sri Lanka) and processing (sterilized vs nonsterilized samples). Further orthogonal partial least squares discriminant analysis (OPLS-DA) models were validated by cross- and external validation, providing satisfactory performance for geographical and processing authentication, as well as excellent predictive ability for further samples. Furthermore, reliable putative identification of 12 key metabolites (markers) was performed, highlighting the feasibility of combining untargeted GC-HRMS analysis with chemometrics for quality control of black pepper.

Volatile compounds sorption during the aging of Chinese Liquor (Baijiu) using Pottery Powder

Pottery jar is the preferred storage vessel for aging baijiu, Chinese liquor, and it could sorb liquor micro-compounds. The objective of this work was to identify the sorption of liquor micro-compounds onto pottery powder, and gained insights regarding the sorption processes and mechanism. The sorption of liquor micro-compounds onto pottery powder of different sizes was studied using different kinetic models. The results showed that the sorption capacity varied among particle size of pottery powder, which also affected equilibrium time. The sorption process could be well described by the pseudo-second-order model, and the external diffusion was the rate-limiting step. Liquor volatiles in pottery powder at equilibrium were characterized, which detected alcohols, esters, acids, and furan by gas chromatography-mass spectrometry (GC-MS). These findings demonstrated pottery could not only cause subtractive changes that occur to liquor during the aging period, but also as a vector for transferring aromas sorbed when reused.

Characterization of rums sold in Spain through their absorption spectra, furans, phenolic compounds and total antioxidant capacity

A total of 42 different rums currently marketed in Spain were analyzed to study the effect of aging time and manufacturing steps (filtration, addition of additives or spices, solera aging method, use of different types of aging barrels) on several parameters: color, non-enzymatic browning, antioxidant capacity and phenolic profile. Different analytical techniques to obtain a broader descriptions of the samples were employed: absorption and UV-vis spectrophotometry, antioxidant capacity (DPPH, FRAP, ABTS methods), total phenols and HPLC to detect individual phenolic and furanic compounds. Results showed that spectrophotometric techniques could potentially be used to detect adulteration and frauds, as well as to differentiate rums by aging time. Those rums aged longer, especially those aged in oak barrels that had previously contained Bourbon or wine, showed higher phenolic content, antioxidant capacity and concentration of furanic compounds. Filtration results in the loss of antioxidant compounds while adding spices increases their concentration in rums.

Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets

Aroma and taste are the most important attributes of alcoholic beverages. In the study, the self-developed electronic tongue (e-tongue) and electronic nose (e-nose) were used for evaluating the marked ages of rice wines. Six types of feature data sets (e-tongue data set, e-nose data set, direct-fusion data set, weighted-fusion data set, optimized direct-fusion data set, and optimized weighted-fusion data set) were used for identifying rice wines with different wine ages. Pearson coefficient analysis and variance inflation factor (VIF) analysis were used to optimize the fusion matrixes by removing the multicollinear information. Two types of discrimination methods (principal component analysis (PCA) and locality preserving projections (LPP)) were used for classifying rice wines, and LPP performed better than PCA in the discrimination work. The best result was obtained by LPP based on the weighted-fusion data set, and all the samples could be classified clearly in the LPP plot. Therefore, the weighted-fusion data were used as independent variables of partial least squares regression, extreme learning machine, and support vector machines (LIBSVM) for evaluating wine ages, respectively. All the methods performed well with good prediction results, and LIBSVM presented the best correlation coefficient (R² ≥ 0.9998).

Untargeted and targeted metabolomics strategy for the classification of strong aroma-type baijiu (liquor) according to geographical origin using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry

A metabolomics strategy was developed to differentiate strong aroma-type baijiu (SAB) (distilled liquor) from the Sichuan basin (SCB) and Yangtze-Huaihe River Basin (YHRB) through liquid-liquid extraction coupled with GC×GC-TOFMS. PCA effectively separated the samples from these two regions. The PLS-DA training model was excellent, with explained variation and predictive capability values of 0.988 and 0.982, respectively. As a result, the model demonstrated its ability to perfectly differentiate all the unknown SAB samples. Twenty-nine potential markers were located by variable importance in projection values, and twenty-four of them were identified and quantitated. Discrimination ability is closely correlated to the characteristic flavor compounds, such as acid, esters, furans, alcohols, sulfides and pyrazine. Most of the marker compounds were less abundant in the SCB samples than in the YHRB samples. The quantitated markers were further processed using hierarchical cluster analysis for targeted analysis, indicating that the markers had great discrimination power to differentiate the SAB samples.

Evolution of the key odorants and aroma profiles in traditional Laowuzeng baijiu during its one-year ageing

Changes of key odorants and aroma profiles of Chinese Laowuzeng baijiu during its one-year ageing were determined by HS-SPME-AEDA and direct injection-AEDA (DI-AEDA). Ethyl hexanoate, (E,E)-2,4-decadienal, and 2-phenylethyl acetate showed the highest FD value (486) in all ageing stages. With regards to aroma profiles, fruity, floral, acidic, sweet/honey and cheesy aromas were enhanced during storage, while pickled vegetable, grain and alcoholic notes weakened during the ageing. Quantitation and OAVs showed that most of the aroma compounds (OAVs > 1), including ethyl esters, aldehydes, and acids, increased their contents within the same period, whereas nonanal, 2-phenylethyl acetate, ethyl benzoate, 4-ethylguaiacol, propanol and 3-methyl-1-butanol decreased in content after the storage of 365 days. Simulated aged samples, in which fresh samples were spiked with 18 compounds, were examined by triangle tests, which indicated that the "fruity" compounds were crucial for maintaining the special aroma profile of an aged sample.

An Innovative Metabolomic Approach for Golden Rum Classification Combining Ultrahigh-Performance Liquid Chromatography-Orbitrap Mass Spectrometry and Chemometric Strategies

A comprehensive fingerprinting strategy for golden rum classification considering different categories such as fermentation barrel, raw material, and aging is provided, using a metabolomic fingerprinting approach. A nontarget fingerprinting of 30 different rums using liquid chromatography coupled to high-resolution mass spectrometry (Exactive Orbitrap mass analyzer, LC-HRMS) was applied. Principal component analysis (PCA) was used to assess the overall structure of the data and to identify potential outliers. Different chemometric analyses such as partial least-squares discriminant analysis (PLS-DA) were used. A variable importance in projection (VIP) selection method was applied to identify the most significant markers that allow group separation. Compounds related to aging and fermentation processes such as furfural derivates (e.g., hydroxymethylfurfural) and sugars (e.g., glucose, mannitol) were found as the most discriminant compounds (VIP threshold value >1.5). Suitable separation according to selected categories was achieved, and a classification ability of the models of close to 100% was achieved.