Distribution analysis of myo and scyllo-inositol in natural grape must

In the context of sustainable viticulture, modern and efficient techniques to determine water status are required to optimize irrigation practices. Proximal techniques such as thermography and spectroscopy have shown promising results. When these techniques are incorporated into mobile systems is possible to evaluate the water status on-the-go, offering the possibility to generate variability maps. However, in most cases, complex protocols of data acquisition and analysis are required. Also, the inherent physiological behaviour of the plants under certain water stress conditions needs to be considered. Therefore, the aim of this study was to evaluate the effect of scion-rootstock combinations on the performance of a predefined plant-based method based on proximal near-infrared (NIR) spectroscopy.

Evoquer la notion de durabilité pour la vigne, plante multimillénaire, et le vin, tous deux intimement liés aux origines de notre civilisation, peut paraître un non-sens.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Nowadays, winemaking is dealing with great challenges, notably climate change, disease resistance and low pesticide inputs, desire for more sustainable agricultural productions and permanent changing of consumer preference. Trying to propose practice improvements, scientists are exploring vine hybridization a paradoxically old but still actual way to take up such challenges

New Plant Breeding Techniques (NPBTs) have the potential to revolutionize the genetic improvement of grapevine. However, the practical application of these techniques is limited by several challenges, such as the difficulty in generating embryogenic calluses, maintaining their competence during in vitro cultivation, and regenerating plants without defects. To overcome these challenges, we conducted a study to test the effect of two treatments on callus cultures derived from different grapevine varieties, with and without embryogenic competence. The tested substances were Silver Thiosulphate (STS) an ethylene inhibitor, and Salicylic Acid (SA), an elicitor with different effects depending on the concentration of use beyond the ethylene inhibitor activity.