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…

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

VineyardFACE: Investigation of a moderate (+20%) increase of ambient CO2 level on berry ripening dynamics and fruit composition

Climate change and rising atmospheric carbon dioxide concentration is a concern for agriculture, including viticulture. Studies on elevated carbon dioxide have already been on grapevines, mainly taking place in greenhouses using potted plants or using field grown vines under higher CO2 enrichment, i.e. >650 ppm. The VineyardFACE, located at Hochschule Geisenheim University, is an open field Free Air CO2 Enrichment (FACE) experimental set-up designed to study the effects of elevated carbon dioxide using field grown vines (Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon). As the carbon dioxide fumigation started in 2014, the long term effects of elevated carbon dioxide treatment can be investigated on berry ripening parameters and fruit metabolic composition.
The present study aims to investigate the effect on fruit composition under a moderate increase (+20%; eCO2) of carbon dioxide concentration, as predicted for 2050 on both Riesling and Cabernet Sauvignon. Berry composition was determined for primary (sugars, organic acids, amino acids) and secondary metabolites (anthocyanins). Special focus was given on monitoring of berry diameter and ripening rates throughout three growing seasons. Compared to previous results of the early adaptative phase of the vines [1], our results show little effect of eCO2 treatment on primary metabolites composition in berries. However, total anthocyanins concentration in berry skin was lower for eCO2 treatment in 2020, although the ratio between anthocyanins derivatives did not differ.
[1] Wohlfahrt Y., Tittmann S., Schmidt D., Rauhut D., Honermeier B., Stoll M. (2020) The effect of elevated CO2 on berry development and bunch structure of Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon. Applied Science Basel 10: 2486

A predictive model of spatial Eca variability in the vineyard to support the monitoring of plant status

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Spatial determination of areas in the Western Balkans region favorable for organic production

In problematic conditions for production of grapes and wine caused by the COVID-19 pandemic and the resulting occurrence of wine surpluses, producers are increasingly turning to the innovative viticulture and winemaking of products that are more appealing to the market and the consumers. On the other hand, consumption of the food safety or organic products, and therefore of organic grapes and wine, is increasingly common in the world, in particular in Europe. The Regional Rural Development Standing Working Group (SWG RRD), as a regional intergovernmental organization gathers actors in the viticulture and winemaking sector from states and territories of the Western Balkans (South-East Europe) in the Expert Working Group for Wine, with the aim of improving viticulture and winemaking in this region through joint activities. In accordance with the aforementioned, the SWG RRD is working on advancing organic production of grapes and wine, and on recognition of specificities of the terroir of wine-growing areas in Western Balkans. In addition, as part of the project “Facilitation of Exchange and Advice on Wine Regulations in Western Balkan Countries” helmed by the German Federal Ministry of Food and Agriculture, in addition to harmonization of relevant legislation with EU regulations, efforts are being invested towards recognition of organic wines. Within activities and project implemented by this organization, expert analyses and scientific research of the terroir of Western Balkans were carried out, and some of the results are presented in this paper.

A multidisciplinary approach to evaluate the effects of the training system on the performance of “Aglianico del Vulture” vineyards

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.