Influence du terroir et de la conduite du verger sur la vigueur, le développement et la productivité des pommiers. Conséquences sur la teneur en sucres des pommes

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.

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.

Vegetative growth and yield are reported to affect grape and wine quality. They can be controlled through different techniques linked to vine management. The objective of this research was to determine the effect of vine vigour and number of clusters per vine on physicochemical composition and phenolic profile of red wines. The experiment was carried out during two vegetative cycles, with cv. Cabernet Sauvignon grafted onto Paulsen 1103. Three vine vigour were defined, according to shoot weight at previous harvests, being low, medium and high. Five treatments of number of clusters were used for each vigour, with 15, 22, 29, 36, and 45 clusters per vine. Grapes from all treatments were harvested in the same day from Brix and total acidity criteria. Thirty days after bottling, classical analyzes and phenolic compounds were performed. As results, different responses were obtained from each vintage. In 2020, a dry season from veraison to harvest, grapes and wines obtained from low vigour treatment and 45 clusters per vine was the highest in sugar and alcohol content respectively, while grapes and wines from high vigour and 15 clusters presented the lowest sugar and alcohol content. Total anthocyanins were higher in treatment with low vigour and 15 clusters, while the lowest amounts were found in low vigour with 45 clusters, as well as medium and high vigour with 36 clusters per vine. Total tannins were higher in high vigour with 22 clusters and medium vigour with 29 clusters, while were lower in low vigour with 36 clusters. In 2021, a wet season at harvest, responses were different, and great variations were observed between treatments. As conclusions, yield and vine vigour had strong influence on grape and wine quality, promoting different enological potentials on which can be indicated/used for aging strategies of red and even rosé wines.

Grapevine physiology and production are challenged by forecasted increases in temperature and water deficits. Within this scenario, photoselective overhead shade films are promising tools in warm viticulture areas to overcome climate change related factors. The aim of this study was to evaluate the vulnerability of ‘Cabernet Sauvignon’ grape berry to solar radiation overexposure and optimize shade film use for berry integrity. A randomized complete block design field study was conducted across two years (2020-2021) in Oakville, Napa Valley, CA, with four shade films (D1, D3, D4, D5) differing in the percent of radiation spectra transmitted and compared to an uncovered control (C0). Integrals for gas exchange parameters and mid-day stem water potential were unaffected by the shade films in 2020 and 2021. By harvest, berries from uncovered and shaded vines did not differ in their size or primary metabolism in either year. Despite precipitation exclusion during the dormant season in the shaded treatments, yield did not differ between them and the control in either season. In 2020, total skin anthocyanins (mg/g fresh mass) in the shaded treatments was greater than C0 during berry ripening and at harvest. Conversely, flavonol concentrations in 2020 were reduced in shaded vines compared to C0. The 2020 growing season highlighted the impact of heat degradation on flavonoids. Flavonoid concentrations in 2021 increased until harvest while flavonoid degradation was apparent from veraison to harvest in 2020 across shaded and control vines. Wine analyses highlighted the importance of light spectra to modify wine composition. Wine color intensity, tonality and anthocyanin values were enhanced in D4 whereas antioxidant properties were enhanced in C0 and D5 wines. Altogether, our results highlighted the need of new approaches in warm viticulture areas given the impact that composition of light has on berry and wine quality.

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.