Volatile aroma constituents of Noble muscadine grapes

Reduced expression of MADS-box gene AGAMOUS-LIKE11 (VviAGL11) is responsible for stenospermocarpic seedlessness in bunch grapes. This study is aimed to characterize the VviAGL11 orthologous gene (VroAGL11) in native muscadine grapes (Vitis rotundifolia) at the molecular level and analyze its divergence from other plants. The VroAGL11 transcripts were found in all muscadine cultivars tested and highly expressed in berries while barely detectable in leaves. RT-PCR and sequencing of predicted ORFs from diverse grape species showed that AGL11 transcripts were conservatively spliced. The encoded VroAGL11 protein contains highly conserved MADS-MEF2-like domain, MADS domain, K box, putative phosphorylation site and two sumoylation motifs. The muscadine VroAGL11 proteins are almost identical (99%) to that of seeded bunch cultivar, Chardonnay, except in one amino acid (A79G), but differs from mutant protein of seedless bunch grape, Sultanina, in two amino acids, R197L and T210A. Phylogenetic analysis showed that AGL11 gene of muscadine and other Vitis species formed a separate clade than that of other eudicots and monocots. Muscadine grape cultivar “Jane Bell” containing the highest percentage of seed content in berry (7.2% of berry weight) had the highest VroAGL11 expression, but almost none to nominal expression in seedless cultivars Fry Seedless (muscadine) and Reliance Seedless (bunch). These findings suggest that VroAGL11 gene controls the seed morphogenesis in muscadine grapes like in bunch grape and can be manipulated to induce stenospermocarpic seedlessness using gene editing technology.

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Digital Smoke Taint Detection in Pinot Grigio Wines Using an E-Nose and Machine Learning Algorithms Following Treatment with Activated Carbon and a Cleaving Enzyme

Fermentation ◽

10.3390/fermentation7030119 ◽

2021 ◽

Vol 7 (3) ◽

pp. 119

Author(s):

Vasiliki Summerson ◽

Claudia Gonzalez Viejo ◽

Damir D. Torrico ◽

Alexis Pang ◽

Sigfredo Fuentes

Keyword(s):

Machine Learning ◽

Activated Carbon ◽

Low Cost ◽

Aroma Compounds ◽

Machine Learning Algorithms ◽

Enzyme Treatment ◽

Mean Values ◽

Volatile Aroma ◽

Carbon Treatment ◽

Volatile Aroma Compounds

The incidence and intensity of bushfires is increasing due to climate change, resulting in a greater risk of smoke taint development in wine. In this study, smoke-tainted and non-smoke-tainted wines were subjected to treatments using activated carbon with/without the addition of a cleaving enzyme treatment to hydrolyze glycoconjugates. Chemical measurements and volatile aroma compounds were assessed for each treatment, with the two smoke taint amelioration treatments exhibiting lower mean values for volatile aroma compounds exhibiting positive ‘fruit’ aromas. Furthermore, a low-cost electronic nose (e-nose) was used to assess the wines. A machine learning model based on artificial neural networks (ANN) was developed using the e-nose outputs from the unsmoked control wine, unsmoked wine with activated carbon treatment, unsmoked wine with a cleaving enzyme plus activated carbon treatment, and smoke-tainted control wine samples as inputs to classify the wines according to the smoke taint amelioration treatment. The model displayed a high overall accuracy of 98% in classifying the e-nose readings, illustrating it may be a rapid, cost-effective tool for winemakers to assess the effectiveness of smoke taint amelioration treatment by activated carbon with/without the use of a cleaving enzyme. Furthermore, the use of a cleaving enzyme coupled with activated carbon was found to be effective in ameliorating smoke taint in wine and may help delay the resurgence of smoke aromas in wine following the aging and hydrolysis of glycoconjugates.

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