Screening table grape cultivars using cell wall ELISA and glycan microarrays for berry firmness and quality parameters

New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season.

Wine grape berries respond to postharvest treatments with specific gaseous elicitors in terms of metabolic changes and composition. Short-term (3 days) high (30 KPa) CO2 treatment affects phenol compound concentration in skins of ‘Trebbiano toscano’ berries.

Throughout the growing season, grapevine frequently encounters environmental challenges associated with heat and light radiation stress, especially during the ripening stage, thereby constraining the yield and quality of berries. MYB24 has been previously proposed to control light responses during late fruit ripening stages, and it has been found to require the co-factor MYC2. We have generated transcriptomic data from grapevine leaves transiently co-transformed with MYB24 and MYC2. Differential expression analysis revealed 179 up-regulated genes (URGs). Considering tissue specificity, where MYB24 is specifically and highly expressed in flowers and late-ripening berries, the expression of these URGs was explored using a previously published Berry Development Atlas gathering berry development data of cv. ‘Pinot Noir’ and ‘Cabernet Sauvignon’ in different vintages.

Sangiovese is one of Italy’s most cultivated grape varieties, and currently, over 130 different clones are registered in the national register of grape varieties. However, despite the sangiovese genome having been re-sequenced, limited molecular and genomic information is still available for this cultivar. The present study investigates the complexity of genotype-environment interactions of ten different Sangiovese clones, cultivated in the Chianti Rufina DOCG district over five consecutive vintages (2016-2020).

Malolactic fermentation (MLF) is a desired process to decrease acidity in wine. This fermentation, carried out mostly by Oenococcus oeni, is sometimes challenging due to the wine stress factors affecting this lactic acid bacterium. Wine is a harsh environment for microbial survival due to the presence of ethanol and the low pH, and with limited nutrients that compromise O. oeni development. This may result in slow or stuck fermentations. After the alcoholic fermentation the nutrients that remain in the medium, mainly released by yeast, can be used in a beneficial way by O. oeni during MLF.