Effects of spontaneous fermentation on Karalahna and Cabernet Sauvignon young red wines: volatile compounds, sensory profiles and identification of autochthonous yeasts

Uzkuç, Nesrin Merve Çelebi; Şişli, Burcu; Ay, Mustafa; Toğay, Sine Özmen; Yüceer, Yonca Karagül; Bayhan, Aslı; Toklucu, Ayşegül Kırca

doi:10.1007/s00217-019-03395-w

Cited by 25 publications

(10 citation statements)

References 34 publications

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“…Nonanal has a rose aroma, furfural has an incense and floral aroma, and usually exist in new wines or grape juice (Yahui et al, 2016;Benito et al, 2009). Benzaldehyde has an almond flavor, with a glycoside form in the nuts, makes a great contribution to Cabernet Sauvignon wine flavor (Çelebi Uzkuç et al, 2020), it was also detected in LRM and other berry fruits in a many work of literatures (Styger et al, 2011;Benito et al, 2009;Zhang et al, 2019).…”

Section: Aldehydesmentioning

confidence: 99%

“…In addition, the co-fermented fruit wines contain three kinds of terpene alcohol, (2E, 6E)-farnesol, geraniol and citronellol. These components were secondary metabolites formed by the synthesis of acetyl-coenzyme A (Morales et al, 2017;Silvia et al, 2004;Çelebi Uzkuç et al, 2020), commonly exist with free and glycosidic patterns in the fruit and peel, also not changed by the metabolism of yeast, exhibiting a pleasant lemon fragrance and rose scent. However, these alcohols were not detected in Changyu wine and 0# wine.…”

Section: Alcoholsmentioning

confidence: 99%

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Analysis on volatile components of co-fermented fruit wines by Lycium ruthenicum murray and wine grapes

Lu¹,

Mi²,

Chen³

et al. 2022

Food Sci. Technol

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LRM fruits with purple-black berry color, and rich in polyphenolic compounds, especially anthocyanins (about 200~380 mg/100 g fresh weight), much higher than other colored fruits and vegetables (Zhang et al., 2018a;Yahui et al., 2016). Numerous studies have demonstrated that LRM plays a vital role in anti-oxidation (Wu et al., 2016), decreasing the levels of blood lipid (Tang et al., 2017), regulating the intestinal flora (Yan et al., 2018), inhibiting the cellular oxidative damage (Peng et al., 2019).Although LRM is known to possess superior biological activity, maintaining the stability of anthocyanins can be an extremely difficult task owing to its degradation by various factors such as pH, temperature, oxygen concentration, light and acylation degree (Sui et al., 2016;Xu et al., 2018), which greatly limits its development and utilization. The technology of fermentation is a very different process from thermal processes in the field of food processing. The acidic conditions and micro-oxygen environment are more suitable for the preservation of anthocyanins during the fermentation and aging period (Nie et al., 2017;Heras-Roger et al., 2016). In addition, fermentation produces a large amount of esters, alcohols, fatty acids, and other substances by the metabolism of Saccharomyces cerevisiae and lactobacillus, which enhance the flavors of fruit wine (Styger et al., 2011).Volatile and aroma components are the vital indicators for the evaluation of alcoholic products. In recent years, gas chromatography-mass spectrometry (GC-MS) has demonstrated successful applications in the analysis of fruit wines (Lee et al., 2018;Kang et al., 2016;Villano et al., 2017). The origin and variety of grapes (Cheng et al., 2015), fermentation process (Albanese et al., 2012;Wang et al., 2016), oak barrels, and aging time (Liu et al., 2016) are potential influencing factors that are utilized in determine the distinct composition of volatile components in the wine. Some scholars employed the GC-MS method for the determination of the volatile components in the red wines from France, Italy, Spain, and Poland, and 13 kinds of alcohols, 9 kinds of acids, 7 kinds of esters, 3 kinds of aldehydes, 2 kinds of ketones and a volatile phenol were identified. In fact, the results showed a considerable difference in the components of diethyl succinate, 4-ethyl phenol, phenylethyl alcohol, and benzyl alcohol in the wines of the abovementioned four countries (Stój et al., 2017). A study has shown that 2-hydroxy-propanoic acid ethyl ester, butanedioic acid monomethyl ester, 4-oxopentanoic acid ethyl ester, 1-dodecene, and 1,2,3-trimethoxy-

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Section: Aldehydesmentioning

confidence: 99%

Section: Alcoholsmentioning

confidence: 99%

Analysis on volatile components of co-fermented fruit wines by Lycium ruthenicum murray and wine grapes

Lu¹,

Mi²,

Chen³

et al. 2022

Food Sci. Technol

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“…However, the distinctive characteristics of different wines, such as quality, geographic origin and vintage are attributed to a myriad of minor constituents [1,2]. Among these characteristics, aroma stands out as a crucial determinant of wine quality [3].…”

Section: Introductionmentioning

confidence: 99%

Wine quality assessment through lightweight deep learning: integrating 1D-CNN and LSTM for analyzing electronic nose VOCs signals

Nguyen,

Le,

Nakano

et al. 2024

ACI

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PurposeIn the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.Design/methodology/approachTo devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.FindingsThe outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.Originality/valueThis research has not been published anywhere else.

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“…4 Spontaneous fermentation (also called natural fermentation) wine generally involves organic cultivation of wine grapes, the use of natural microorganisms to produce a wine with local style, and the omission of commercial yeast, sulfur dioxide (SO 2 ), and other auxiliary materials to reduce human intervention. 7,8 The natural fermentation of wine was considered a traditional fermented food. Nutrients in grape fruits were transformed into alcohol and aroma substances by microorganisms in the natural environment.…”

Section: Introductionmentioning

confidence: 99%

Metagenomic analysis of the relationship between the microorganisms and the volatiles' development in the wines during spontaneous fermentation from the eastern foothills of the Ningxia Helan mountains in China

Yang

et al. 2023

J Sci Food Agric

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BACKGROUNDThe natural fermentation of multispecies microbial communities is responsible for unique flavors of winery regions of the eastern foothills of the Ningxia Helan Mountains in China. However, the participation of different microorganisms in the metabolic network for the development of important flavor substances is not clearly defined. Microbial population and diversity on different fermentation phases of Ningxia wine were analyzed by metagenomic sequencing approach.RESULTSGas chromatography–mass spectrometry and ion chromatography were used to identify flavor components, and 13 esters, 13 alcohols, nine aldehydes and seven ketones were detected in volatile substances with odor activity values > 1, and eight organic acids were detected as important flavor components in young wine. Thus, 52 238 predicted protein‐coding genes from 24 genera were identified in the Kyoto Encyclopedia of Genes and Genomes level 2 pathways of global and overview maps, and the genes were primarily involved in amino acid metabolism and carbohydrate metabolism. Major microbial genera (Saccharomyces, Tatumella, Hanseniaspora, Lactobacillus, and Lachancea) were closely related to self‐characteristic compound metabolism and further contributed to wine flavor.CONCLUSIONThis study clarifies the different metabolic roles of microorganisms in flavor formation during Ningxia wine spontaneous fermentation. Saccharomyces, dominant fungi involved in glycolysis and pyruvate metabolism, produces not only ethanol but also two important precursors, pyruvate and acetyl‐CoA, which are necessary for the tricarboxylic acid cycle, fatty acid metabolism, amino acid metabolism, and flavor formation. Lactobacillus and Lachancea, dominant bacteria involved in lactic acid metabolism. Tatumella, dominant bacteria involved in amino acid metabolism, fatty acid metabolism, and acetic acid metabolism to produce esters in the Shizuishan City region samples. These findings provide insights into the use of local functional strains to generate unique flavor formation, as well as improved stability and quality, in wine production. © 2023 Society of Chemical Industry.

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Effects of spontaneous fermentation on Karalahna and Cabernet Sauvignon young red wines: volatile compounds, sensory profiles and identification of autochthonous yeasts

Cited by 25 publications

References 34 publications

Analysis on volatile components of co-fermented fruit wines by Lycium ruthenicum murray and wine grapes

Analysis on volatile components of co-fermented fruit wines by Lycium ruthenicum murray and wine grapes

Wine quality assessment through lightweight deep learning: integrating 1D-CNN and LSTM for analyzing electronic nose VOCs signals

Metagenomic analysis of the relationship between the microorganisms and the volatiles' development in the wines during spontaneous fermentation from the eastern foothills of the Ningxia Helan mountains in China

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