In vitro tissue culture as a tool for Croatian grapevine germplasm management

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.

Downy mildew, caused by Plasmopara viticola, is the most economically impactful disease affecting grapevines. This polycyclic pathogen triggers both primary and secondary infection cycles, resulting in significant yield losses when effective disease control measures are lacking. Over the winter, the pathogen survives by forming resting structures, the oospores, derived from sexual reproduction, which produce the inoculum for primary infections. To optimize grapevine downy mildew control and obtain the desired levels of production while minimizing chemical inputs, it is crucial to optimize the timeframe for fungicide application. Disease forecasting models are useful to identify the infection risk.

Effervescence and foaming properties are the main visual characteristics assessed by the consumer during
sparkling wine tasting.

Grapevine (Vitis vinifera L.) is a challenging plant species to transform and regenerate due to its complex genome and biological characteristics. This limits the development of cisgenic and gene-edited varieties. One hurdle is selecting the best starting tissue for the transformation process, much like isolating suitable tissue for protoplasts. One promising method involves delivering CRISPR/Cas components to protoplasts isolated from embryogenic calli, which are then induced to regenerate. However, this process is inefficient, time-consuming, and only applicable to a few genotypes. To enhance grapevine regeneration efficiency, the expression of developmental and plant growth regulators shows promise in escaping the recalcitrance encountered in traditional tissue culture methods.

Proton relaxation in model and real wines was investigated by fast field cycling NMR relaxometry. Albeit protons of wine are largely belonging to water molecules, their magnetic relaxation rates actually depend on various physico-chemical parameters related to the state of the wine and to its composition.