Early in vitro selection of eutypine-tolerant plantlets. Application to screening of Vitis vinifera cv. Ugni lanc somaclones

Research Not

The stimulation by ethylene of the UDP glucose-flavonoid 3-O-glucosyltransferase (UFGT) in grape tissues is independent from the MybA transcription factors

Research Note

Purification of plasma membrane vesicles from Vitis vinifera cv. Gamay suspension cells by free electrophoresis

Research Not

Ultrastructural changes produced in plantlet leaves and protoplasts of Vitis vinifera cv. Cabernet Sauvignon by eutypine, a toxin from Eutypa lata

Eutypine is a toxin produced by Eutypa lata (Pers.: Pr.) Tul., the causal agent of dying-arm disease of the grapevine. Ultrastructural alterations induced by eutypine in leaf cells and protoplasts isolated from plantlets of Vitis vinifera cv. Cabernet Sauvignon, a very sensitive variety cultured in vitro, were observed for the first time by transmission electron microscopy. Eutypine caused early cytoplasm lysis and vesiculation followed by chloroplast swelling with thylakoid dilation. The eutypine-induced alterations of the cellular ultrastructure are similar to those previously described in vivo in the leaves of diseased grapevines. These results confirm that eutypine, synthesized by E. lata mycelium present in the trunk or arms, is involved in symptom expression of eutypiosis in the herbaceous parts of grapevine

Ethanol application at veraison decreases acidity in Cabernet Sauvignon grapes

Research NoteSpraying ethanol (5 % v/v in water) onto grape clusters at mid-veraison led to a 30 % drop in the malic acid concentration at harvest. As a consequence, titratable acidity also dropped by 10 %. The concentration of tartaric acid did not change significantly. The mode of action of ethanol on malic acid metabolism is discussed.

Accounting for meteorological biases in simulated plumes using smarter metrics

In the next few years, numerous satellites with high-resolution instruments dedicated to the imaging of atmospheric gaseous compounds will be launched, to finely monitor emissions of greenhouse gases and pollutants. Processing the resulting images of plumes from cities and industrial plants to infer the emissions of these sources can be challenging. In particular traditional atmospheric inversion techniques, relying on objective comparisons to simulations with atmospheric chemistry transport models, may poorly fit the observed plume due to modelling errors rather than due to uncertainties in the emissions. The present article discusses how these images can be adequately compared to simulated concentrations to limit the weight of modelling errors due to the meteorology used to analyse the images. For such comparisons, the usual pixel-wise ℒ2 norm may not be suitable, since it does not linearly penalise a displacement between two identical plumes. By definition, such a metric considers a displacement as an accumulation of significant local amplitude discrepancies. This is the so-called double penalty issue. To avoid this issue, we propose three solutions: (i) compensate for position error, due to a displacement, before the local comparison; (ii) use non-local metrics of density distribution comparison; and (iii) use a combination of the first two solutions. All the metrics are evaluated using first a catalogue of analytical plumes and then more realistic plumes simulated with a mesoscale Eulerian atmospheric transport model, with an emphasis on the sensitivity of the metrics to position error and the concentration values within the plumes. As expected, the metrics with the upstream correction are found to be less sensitive to position error in both analytical and realistic conditions. Furthermore, in realistic cases, we evaluate the weight of changes in the norm and the direction of the four-dimensional wind fields in our metric values. This comparison highlights the link between differences in the synoptic-scale winds direction and position error. Hence the contribution of the latter to our new metrics is reduced, thus limiting misinterpretation. Furthermore, the new metrics also avoid the double penalty issue.</p