Adaptation of Lactobacilli towards low ph and SO₂ to develop MLF in base musts for sparkling wines

The technique of crossing, whether free or controlled, has always been a source of variability allowing the selection of new varieties with improved fitness.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Nitrogen (N) uptake by grapevine roots in forms like nitrate, ammonium, urea, or amino acids influences vegetative and generative growth, impacting grape quality and wine sensory profile. The study examined nitrogen’s influence on phenolic compounds in leaves, berries, and wine across different scales — hydroponics, soil culture, and vineyard trials. Nitrogen forms altered metabolite patterns in leaves and wine significantly, affecting aroma and flavor. Key nitrogen assimilation enzymes (NR, NiR, GS) in grapevine rootstocks responded to nitrogen forms and timing. Hydroponically grown rootstocks fertilized with various forms showed differences in enzyme expression and activity, suggesting rootstocks can assimilate amino acid glutamine (Gln).

The amino acids in grape juice are an important nitrogen source for yeast during alcoholic fermentation. Additionally, certain AAs are precursors to some of the volatile compounds found in wine and overall

Úbeda-Aguilera, C a, b, Peña-Neira, A.b Del Barrio-Galán, R.b, c a Biomedical Sciences Institute, Science Faculty, Universidad Autónoma de Chile, Chile. b Department of Agro-Industry and Enology, Faculty of Agronomical Sciences, University of Chile, Post Office Box 1004, Santa Rosa 11315, La Pintana, Santiago, Chile c Lallemand Inc. Chile y Compañía Limitada, Rosario Norte 407, piso 6, Las Condes, Santiago, Chile The wine is a complex matrix made up of several compounds which can interact among themselves throughout the wine ageing process, thereby modifying their sensorial characteristics. It is well known that during ageing of wines on lees, polysaccharides (mainly mannoproteins) can be released and can interact with the aromatic fraction modifying its volatility.