Control of microbial development in wines elaborated by carbonic maceration

The timing of phenology is critical if grape quality potential is to be optimized. Phenological process based models are used to predict phenology. In this study, three different models

AIM: Cross-over applications are an emerging technological approach in food microbiology where a microorganism from one traditional specific fermentation process is used to improve quality and safety in another agri-food production/chain (Dank et al., 2021). A complex microbial diversity is found in association with fermentation in wine, including Saccharomyces, non-Saccharomyces and malolactic bacteria,  all microorganisms versatile in terms of enological utilisation (Tempère et al., 2018). Here, we propose a systematic literature review highlighting the existing trends and possible future applications related to cross-over exploitation of wine-related microbiota. 

Sulfonated monomeric and dimeric flavan-3-ols are recently discovered in wine and proved to have great importance in understanding wine chemistry and quality [1, 2].

In a context of reducing herbicide use, the most part of French vineyards are developing permanent grass cover crops on inter-rows alleys, while under the row chemical weeding remains the general case. The setting up of a controlled grass cover crop under the vine row could be a complementary alternative to mechanical weeding – which one is very restrictive – interesting from a technical and economical point of view. The present study aimed at assessing agronomic impacts of grass cover crop under the row in different climatic conditions and production objectives.

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.