Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

Identification of characteristic volatiles and metabolomic pathways during the fermentation of red grapefruit by Monascus purpureus using HS-SPME-GC-MS and metabolomics

Fermentation of red grapefruit by Monascus purpureus (M. purpureus) results in complex changes in flavor compounds and metabolic profiles, but the specifics of these alterations are not well understood. This study aimed to investigate the changes in flavor compounds and metabolomic traits during this fermentation process. Using Headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) with non-targeted metabolomics, we analyzed flavor compounds and measured physicochemical indices throughout the fermentation period. We identified 23 volatile flavor metabolites before and after fermentation, focusing on acids, alcohols, and aldehydes, of these, 9 showed an upward effect and 14 showed a downward effect. Key metabolic pathways involved included butyric acid, taurine, and hypotaurine, with notable downregulation of acetone and 1-butanol in the butyric acid pathway. The study reveals that butyric acid-related metabolism influences other pathways such as glycolysis, fatty acid metabolism, and the tricarboxylic acid cycle in M. purpureus. These findings provide insights into the generation of flavor compounds during fermentation and offer a theoretical basis for the industrial production of fermented citrus fruits.

Determination of Elemental Content in Vineyard Soil, Leaves, and Grapes of Sangiovese Grapes from the Chianti Region Using ICP-MS for Geographical Identification

To fight counterfeits and to protect the consumer, the interest in certifying the origin of agricultural goods has been steadily growing in the last years. While numerous works focus on the finished product, an aspect often overlooked is the origin of the raw materials and the direct correlation between chemicals in the soil and the plants. With inductively coupled plasma mass spectrometry (ICP-MS) analysis, trace and ultratrace elements in Sangiovese grapes (the main component of Chianti wine) were measured and their levels were used to investigate the geographical origin of the samples. This was achieved despite the extreme closeness of some of the vineyard partners of this study (10-20 km range) by computing a multivariate model using selected elements as levels. The model was then validated on samples coming from different zones of the Chianti area, with good results for discriminating even extremely close regions.

Fermentation Performances and Aroma Contributions of Selected Non-Saccharomyces Yeasts for Cherry Wine Production

This study evaluates the fermentation performances of non-Saccharomyces strains in fermenting cherry must from Italian cherries unsuitable for selling and not intended to be consumed fresh, and their effects on the chemical composition of the resulting wine. Fermentation trials in 100 and 500 mL of must were carried out to select 21 strains belonging to 11 non-Saccharomyces species. Cherry wines obtained by six select strains were chemically analyzed for fixed and volatile compounds. Quantitative data were statistically analyzed by agglomerative hierarchical clustering, partial least squared discriminant analysis, and principal component analysis. Wines revealed significant differences in their composition. Lactic acid and phenylethyl acetate levels were very high in wines produced by Lachancea and Hanseniaspora, respectively. Compared to S. cerevisiae wine, non-Saccharomyces wines had a lower content of fatty acid ethyl esters 4-vinyl guaiacol and 4-vinyl phenol. The multivariate analysis discriminated between wines, demonstrating the different contributions of each strain to aroma components. Specifically, all wines from non-Saccharomyces strains were kept strictly separate from the control wine. This study provided comprehensive characterization traits for non-conventional strains that enhance the aroma complexity of cherry-based wine. The use of these yeasts in cherry wine production appears promising. Further investigation is required to ascertain their suitability for larger-scale fermentation.

Pattern-based colorimetric sensor array chip for discrimination of Baijiu aromas

Gas mixtures are comprised of numerous complex components, making the accurate identification a continuing challenge due to the significant limitations of existing detection methods. Herein, we developed a low-cost and sensitive pattern-based colorimetric sensor array chip for the identification of typical gas mixtures - Baijiu aroma. Specifically, three nanomaterials (AuNPs, MoS2 and ZIF-8) were prepared to adsorb gas molecules and enhance the reaction of trace gases with sensor arrays. The colorimetric sensor array chip took only 5 min to complete the recognition of Baijiu aromas and effectively avoided recognition errors caused by sommelier olfactory fatigue. Notably, the hierarchical cluster analysis (HCA) revealed no confusion or errors in the results of 80 tests across the five trials involving 16 commercial Baijius. Even fake Baijius with similar ingredients could be easily identified, demonstrating the excellent analytical capabilities of the system in Baijiu identification and its significant potential for quality control of Baijius.

Volatilomics of Fruit Wines

Volatilomics is a scientific field concerned with the evaluation of volatile compounds in the food matrix and methods for their identification. This review discusses the main groups of compounds that shape the aroma of wines, their origin, precursors, and selected metabolic pathways. The paper classifies fruit wines into several categories, including ciders and apple wines, cherry wines, plum wines, berry wines, citrus wines, and exotic wines. The following article discusses the characteristics of volatiles that shape the aroma of each group of wine and the concentrations at which they occur. It also discusses how the strain and species of yeast and lactic acid bacteria can influence the aroma of fruit wines. The article also covers techniques for evaluating the volatile compound profile of fruit wines, including modern analytical techniques.

Comprehensive Two-Dimensional Gas Chromatography with a TOF MS Detector-An Effective Tool to Trace the Signature of Grape Varieties

Varietal volatile compounds are characteristic of each variety of grapes and come from the skins of the grapes. This work focuses on the development of a methodology for the analysis of free compounds in grapes from Trincadeira, Cabernet Sauvignon, Syrah, Castelão and Tinta Barroca from the 2021 and 2022 harvests, using HS-SPME-GC × GC-TOFMS. To achieve this purpose, a previous optimization step of sample preparation was implemented, with the optimized conditions being 4 g of grapes, 2 g of NaCl, and 2 mL of H2O. The extraction conditions were also optimized, and it was observed that performing the extraction for 40 min at 60 °C was the best for identifying more varietal compounds. The fiber used was a triple fiber of carboxen/divinylbenzene/polydimethylsiloxane (CAR/DVB/PDMS). In addition to the sample preparation, the analytical conditions were also optimized, enabling the adequate separation of analytes. Using the optimized methodology, it was possible to identify fifty-two free volatile compounds, including seventeen monoterpenes, twenty-eight sesquiterpenes, and seven C13-norisoprenoids. It was observed that in 2021, more free varietal volatile compounds were identifiable compared to 2022. According to the results obtained through a linear discriminant analysis (LDA), the differences in volatile varietal signature are observed both among different grape varieties and across different years.

Evaluation of fifteen processing methods of hellgrammites based on the flavor characteristics

To investigate suitable processing methods for improve the flavor while maintaining quality, hellgrammites were subjected to fifteen different processing methods. The samples were tested by sensory evaluation and were analyzed using HS-SPME-GC-MS. The sensory evaluation revealed that five methods for head and chest removal, three wine-fried methods, and three vinegar-roasting methods significantly reduced the levels of hexanal (3129.05 ± 45.77 μg/kg) and heptanal (436.72 ± 7.42 μg/kg), compounds responsible for fishy and earthy flavors, compared to raw samples. The latter two methods exhibited increased aroma flavor. PCA and OPLS-DA analyses suggested that acids, alcohols, and esters played a crucial role in flavor modification. Notably, vinegar-roasting methods demonstrated the highest acid content and had a substantial impact on volatile compounds. Additionally, boiling methods effectively reduced the levels of hazardous compounds, such as toluene and 1,3-Dimethyl-benzene. However, other methods did not exhibit similar efficacy in reducing hazardous compounds. The accumulation of hazardous compounds showed a decreasing trend in the whole insect, head removal, and head and chest removal groups. Moreover, the relative odor activity value consistently identified aldehyde compounds, including hexanal and heptanal, as the main contributors to aroma. Overall, boiling and head and chest removal procedures were suggested as precautionary measures during the initial processing of hellgrammites-based food products. The vinegar-roasting and wine-fried methods could be employed to impart desired flavors, aligning with consumers' preferences. These findings lay the foundation for standardizing processing techniques and ensuring the quality control of products derived from hellgrammites.

Changes in the Sensory Odor Profile during Chorizo Maturation and Their Relationship with Volatile Compound Patterns by Partial Least Square Regression (PLS)

Odor is one of the most important attributes to determine the overall acceptance of a product. The aim of this investigation is to evaluate the changes in the odor profile and the volatile compounds during thirty-three days of ripening to obtain the pattern of volatile compounds necessary to integrate the odor profile of chorizo (fermented sausage), using Partial Least Squares (PLS). The chili and pork meat odors were predominant during the first five days, vinegar and fermented odors at days twelve and nineteen days, and finally a rancid odor predominated at the end. Only the vinegar, rancid, and fermented odors could be predicted with a good fit model, with the R² coefficient above 0.5, using linear PLS, and the pork meat odor using logarithmic PLS. Each group of volatile compounds interacted in different ways; esters had a positive influence on the vinegar and rancid odors, but a negative on the fermented odor. Some volatile compounds contributed to more than one odor, such as hexanal, ethanol, and ethyl octanoate. This work allowed us to understand the pattern of volatile compounds required to generate some of the specific odors of chorizo; further studies are required to explore the effect of other food components on these patterns of odors.

Effect of Bentonite Addition to Pedro Ximénez White Grape Musts before Their Fermentation with Selected Yeasts on the Major Volatile Compounds and Polyols of Wines and Tentative Relationships with the Sensorial Evaluation

In this work, we study the effect of bentonite addition to the grape must before alcoholic fermentation on the chemical composition and sensorial profile of the obtained wines. Fermentations were carried out with two Saccharomyces cerevisiae commercial active dry yeasts treated or not with bentonite and were compared with a control wine obtained by spontaneous fermentation (using the grape must microbiota). Several significant effects on the chemical and sensorial attributes were established by statistical treatments. The selection by multiple variable analysis of seven volatile molecules (ethyl acetate; methanol; 1-propanol; isobutanol; 2-methyl-1-butanol; 3-metyl-1-butanol and 2-phenylethanol) provided several footprints that provide an easy visualization of bentonite effects on wine volatile compounds. A Principal Component Analysis carried out with all the compounds quantified by Gas-Chromatography revealed that the first two Principal Components explain 60.15 and 25.91%, respectively, of the total variance and established five groups that match with the five wines analyzed. Lastly, predictive models at p ≤ 0.05 level for the attributes sight, smell and taste were obtained by Partial Least Squared regression analysis of selected chemical variables.