Non-targeted metabolomic approach as a tool to evaluate the chemical profile of sparkling wines fermented with autochthonous yeast strains

Tufariello, Maria; Rizzuti, Antonino; Palombi, Lorenzo; Ragone, Rosa; Capozzi, Vittorio; Gallo, Vito; Mastrorilli, Piero; Grieco, Francesco

doi:10.1016/j.foodcont.2021.108099

Cited by 13 publications

(12 citation statements)

References 45 publications

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“…Also, Raposo et al ( 2016) reported a similar value (0.24 g/l) of acetic acid in white wine. Furthermore, Tufariello et al (2021) measured a low level of volatile acidity (<0.3 g/l) in bottled sparkling wines, which is really important for sparkling wines quality, as it affects the development of yeasts in the secondary stage of alcoholic fermentation (Vigentini et al, 2017). Likewise, a volatile acidity value of 0.23 g/l in a sparkling wine was recently reported by Martinez-Garcia et al (2021).…”

Section: (A) (B)mentioning

confidence: 75%

“…In the study of Sandez et al (2019) total acidity values in white wines ranging from 4.5 to 6.85 g/l were obtained. Also, Tufariello et al (2021) recently reported that the total acidity in sparkling wines ranged from 5.11 g/l to 5.97 g/l, whereas Martinez-Garcia et al (2021) reported a total acidity of 6.4 g/l for tartaric acid in a sparkling wine. The acidity is a chemical parameter that decisively affects the character and the quality of the wine as a final product.…”

Section: (A) (B)mentioning

confidence: 99%

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Quality study of PDO (Protected Designation of Origin) Greek white wines of the grape variety ‘Debina’

Tsiraki

SAVVAIDIS²

2022

Not Bot Horti Agrobo

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In this study ‘Debina’ (Zitsa, Ioannina, Greece) wines (WD: white dry and WDS: white dry sparkling) were examined in terms of their quality (chemical, physicochemical and sensory) parameters. The concentration of alcohol in both wines was practically stable (p>0.05) from the stage of fermentation to packaging and specifically, the rates were 12 and 11.4% vol for WD and WDS wines, respectively. Total sugar concentrations were equal to 1.4 g/l and 1.2 g/l in WD and WDS wines, respectively. WD wine had final total acidity, volatile acidity and pH values of 4.9 g/l tartaric acid, 0.19 g/l acetic acid and 3.15, respectively. While, WDS wine had final total acidity, volatile acidity and pH value of 6.0 g/l tartaric acid, 0.15 g/l acetic acid and 3.11, respectively. Τotal sulfite content of wine samples decreased and final values of 90.6 mg/l and 99.8 mg/l, in the last production stage, for the WD and WDS wines, were recorded, respectively. According to the data of the study, all wines received a high acceptability sensory score, as judged by the panellists. It must be reported that the sensory scores were on average, 1 point higher for the WDS wines, as compared to the WD wines.

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Section: (A) (B)mentioning

confidence: 75%

Section: (A) (B)mentioning

confidence: 99%

Quality study of PDO (Protected Designation of Origin) Greek white wines of the grape variety ‘Debina’

Tsiraki

SAVVAIDIS²

2022

Not Bot Horti Agrobo

View full text Add to dashboard Cite

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“…In conclusion, research on the role of yeast VOCs in the biocontrol of mycotoxigenic postharvest fungi has greatly progressed during recent years. The increasing range of new, effective yeast strains whose mechanism of action includes, or is based on, the emission of bioactive volatile compounds, along with the development of sensitive metabolomics approaches [ 150 , 151 , 152 ], will expand the arsenal of new molecules showing great potential for practical application in the control of mycotoxin-producing spoilage fungi. Despite our growing knowledge on the structure–activity relationship of yeast volatilome, further studies are still needed to better define the food safety risks associated with VOCs affecting multiple metabolic processes in the target fungi.…”

Section: Discussionmentioning

confidence: 99%

Perfume Guns: Potential of Yeast Volatile Organic Compounds in the Biological Control of Mycotoxin-Producing Fungi

Oufensou

Hassan

Balmas

et al. 2023

Toxins

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Pathogenic fungi in the genera Alternaria, Aspergillus, Botrytis, Fusarium, Geotrichum, Gloeosporium, Monilinia, Mucor, Penicillium, and Rhizopus are the most common cause of pre- and postharvest diseases of fruit, vegetable, root and grain commodities. Some species are also able to produce mycotoxins, secondary metabolites having toxic effects on human and non-human animals upon ingestion of contaminated food and feed. Synthetic fungicides still represent the most common tool to control these pathogens. However, long-term application of fungicides has led to unacceptable pollution and may favour the selection of fungicide-resistant mutants. Microbial biocontrol agents may reduce the incidence of toxigenic fungi through a wide array of mechanisms, including competition for the ecological niche, antibiosis, mycoparasitism, and the induction of resistance in the host plant tissues. In recent years, the emission of volatile organic compounds (VOCs) has been proposed as a key mechanism of biocontrol. Their bioactivity and the absence of residues make the use of microbial VOCs a sustainable and effective alternative to synthetic fungicides in the management of postharvest pathogens, particularly in airtight environments. In this review, we will focus on the possibility of applying yeast VOCs in the biocontrol of mycotoxigenic fungi affecting stored food and feed.

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“…As an example, Tufariello and co-workers [ 53 ] applied PCA to identify the volatile compounds that best discriminated wines produced by yeast strains selected in the two different areas, i.e., north and south Salento in the Apulia region of Italy. In addition, PCA was used for highlighting the differences among sparkling wines produced using different autochthonous yeast strains for the secondary fermentation step [ 54 ]. PCA coupled with discriminant analysis (DA) analysis has recently been used as a chemometric tool to identify the ageing process (barrel- or chip-aged) the wine undergoes, by selecting key volatile molecules detected via GC-MS [ 55 ].…”

Section: Processing Of Hs-spme-gc-ms Data On Wine Volatiles By Multiv...mentioning

confidence: 99%

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

Tufariello

Pati

Palombi

et al. 2022

Foods

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This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.

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Non-targeted metabolomic approach as a tool to evaluate the chemical profile of sparkling wines fermented with autochthonous yeast strains

Cited by 13 publications

References 45 publications

Quality study of PDO (Protected Designation of Origin) Greek white wines of the grape variety ‘Debina’

Quality study of PDO (Protected Designation of Origin) Greek white wines of the grape variety ‘Debina’

Perfume Guns: Potential of Yeast Volatile Organic Compounds in the Biological Control of Mycotoxin-Producing Fungi

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

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