GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 GiESCO 2019 9 The myth of the universal rootstock revisited: assessment of the importance of interactions between scion and rootstock

The myth of the universal rootstock revisited: assessment of the importance of interactions between scion and rootstock

Abstract

Aim‐ Rootstocks provide protection against soil borne pests and are a powerful tool to manipulate growth, fruit composition and wine quality attributes. The present study aimed to assess the consistency of rootstock effects on growth and fruit composition of scion varieties and identify scion x rootstock interactions.

Methods and Results‐ Vine performance and fruit composition of hot climate, drip irrigated, spur pruned Chardonnay, Cabernet Sauvignon and Shiraz grafted on 7 rootstocks was assessed over 5 seasons, 2013‐2017. Rootstocks included Ramsey, 1103 Paulsen and 140 Ruggeri and 4 promising selections from the CSIRO rootstock development program. Vines were trained as quadrilateral cordons on a 1.8 m high 2‐wire vertical trellis with a 3.0 m x 1.8 m, row x vine spacing and irrigated with 5.5 – 6.0 Ml/ha of water each season. The study was conducted with mature vines established in 2006, as a randomized block design with 5 replicates.

There were significant effects of both variety and rootstock on yield, bunch number, bunch weight, berry weight (scion only), berries per bunch, pruning weight and the Ravaz Index (yield/pruning weight). Despite identical management practices, there were large differences between scion varieties in key growth characteristics across rootstocks. Chardonnay produced a high yield (mean 25.2 kg/vine) with low pruning weight (2.3 kg/vine) and a high mean Ravaz Index value of 12.1. Shiraz had the highest yield (27.4 kg/vine) with high pruning weight (5.1 kg/vine) and a Ravaz index of 6.3. Cabernet Sauvignon had the lowest yield (15.9 kg/vine) and highest pruning weight (6.6 kg/vine) and a very low Ravaz Index value of 3.0. Effects of rootstock on growth characteristics were smaller than the effects of variety, with mean yields ranging from 19.5 to 25.9 kg/vine, pruning weights ranging from 3.24 to 6.13 kg/vine and mean Ravaz Index values ranging from 5.54 to 8.63. Each variety was harvested when mean total soluble solids reached 25.0 oBrix. There were significant effects of variety and rootstock on fruit composition including pH, titratable acidity (scion only), malate, tartrate (scion only), yeast assimilable nitrogen (YAN) and for the red varieties, total anthocyanins (scion only) and phenolic substances (scion only). 

Significant interactions between scion variety and rootstocks were found for yield, bunch number, berry weight, pruning weight and Ravaz index. The effect of rootstock on bunch weight and berries per bunch was consistent across scions. Significant scion x rootstock interactions were also found for pH and YAN. For each variety, significant effects of rootstock on fruit composition were linked to growth characteristics. However, these relationships, based on correlation analyses, varied for each scion.

Conclusions

The study has shown that growth characteristics and fruit composition of the major varieties was not consistent across 7 rootstock genotypes, as significant scion x rootstock interactions were determined. Hence, different rootstocks may be required for each variety to optimise scion performance and fruit composition. The study has also shown that the new CSIRO rootstock selections, covering a range of vigour classifications, may be useful alternatives to those currently in use by industry.

Significance and impact of the study‐ The study has shown that the performance of scion varieties and to a lesser degree fruit composition, is dependent on rootstock choice. The inherent vigour of the scion variety must be considered in rootstock selection. Furthermore, individual scion/rootstock combinations may require specific irrigation, pruning or canopy management to achieve vine balance and optimise fruit and wine composition.

DOI:

Publication date: June 19, 2020

Issue: GiESCO 2019

Type: Article

Authors

Peter CLINGELEFFER (1), Norma MORALES (1), Hilary DAVIS (2) and Harley SMITH (1)

(1) CSIRO Agriculture and Food, Locked Bag 2, Glen Osmond SA, 5064, Australia.
(2) CSIRO Agriculture and Food, PO Box 447, Irymple Vic, 3498, Australia.

Contact the author

Keywords

Grapevine, Scion, Variety, Rootstock, Growth, Composition, Interactions

Tags

GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Climate modeling at local scale in the Waipara winegrowing region in the climate change context

In viticulture, a warming climate can have a very significant impact on grapevine development and therefore on the quality and characteristics of wines across different spatial scales, ranging from global to local. In order to adapt wine-growing to climate change, global climate models can be used to define future scenarios, but only at the scale of major wine regions. Despite the huge progress made over the last ten years in terms of the spatial resolution of climate models (now downscaled to a few square kilometres), they are not yet sufficiently precise to account for the local climate variability associated with such parameters as local topography, in spite of these parameters being decisive for vine and wine characteristics. This study describes a method to downscale future climate scenarios to vineyard scale. Networks of data loggers have been used to collect air temperature at canopy level in the Waipara winegrowing region (New Zealand) over five growing seasons. These measurements allow the creation of fine-scale geostatistical models and maps of temperature (at 100 m resolution) for the growing season. In order to model climate change at pilot site scale, these geostatistical models have been combined with regional climate change predictions for the periods 2031-2050 and 2081-2100 based on the RCP8.5 climate change scenario. The integration of local climate variability with regionalized climate change simulations allows assessment of the impacts of climate change at the vineyard scale. The improved knowledge gained using this methodology results from the increased horizontal resolution that better addresses the concerns of winegrowers. The results provide the local winegrowers with information necessary to understand current processes, as well as historical and future viticulture trends at the scale of their site, thereby facilitating decisions about future response strategies.

Updating the Winkler index: An analysis of Cabernet sauvignon in Napa Valley’s varied and changing climate

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

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.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

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.

Exploring resilience and competitiveness of wine estates in Languedoc-Roussillon in the recent past: a multi-level perspective

The Languedoc-Roussillon wineries are facing a decline in wine yields particularly PGI yields due to many factors. Climate change is just ones, but is expected to increase in the future. There is also structurally a large heterogeneity of yield profiles among terroirs, varieties and strategies. This work investigates the link between yield, competitiveness and resilience to explore how resilient winegrowers have been in the recent past. To this end two approaches have been combined; (i) an accountancy database analysis at estate scale and (ii) municipality level competitiveness analysis. A new resilience indicator that characterizes the capacity of an estate to absorb yield variation is also defined. The FADN database between 2000 and 2018 of ex-Languedoc-Roussillon (France) and other data are used to analyse the current situation and the past evolution of competitiveness and resilience by type of estate (type of farm: PGI and/or PDO & type of commercialization: bulk and/or bottles). The net margin, which defines competitiveness, is not correlated to yield for all types but depends on the type of commercialization and the level of specialisation. The resilience indicator shows that the net margin of estates specialized in PGI is particularly sensitive to yield declines. We also show that price evolutions seem to compensate the effect of yield losses for the majority of types. Municipality scale analysis shows the links between local pedoclimate, yield, commercialization strategies and price. Overlapping a PDO with a PGI does not always increase a municipality’s PGI competitiveness. It is difficult to make links between causes and effects due to the complexity of the wine production system. Production diversification may be a solution. Resorting to the two level of analysis helps resolving the data gap that is necessary to explore the links between yield and economic performance of the wine estates in the long term.