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IVES 9 IVES Conference Series 9 Can the use of rootstocks enhance terroir?

Can the use of rootstocks enhance terroir?

Abstract

Rootstocks are an essential l management tool for diverse viticultural challenges. However, studies that combine sensory evaluation and compositional analysis of berries and wine, to determine whether the use of a particular rootstock in a terroir can influence wine quality are sparse. The aim of this study was to determine the influence of different rootstocks and own roots control on sensory and compositional differences in grape berries and resultant wines

Descriptive Sensory Analysis and compositional measures including GCMS were conducted on berries and wines of Vitis vinifera L. cv Shiraz vines grown on own roots or grafted to three different rootstocks (110 Richter, 1103 Paulsen, Schwarzmann). The study was conducted in an experimental rootstock vineyard in the Barossa Valley, South Australia, during two growing seasons (2009/10-2010/11).

Sensory and compositional differences were found in berries and wines from the rootstock treatments and the own roots control that were reflected in the wine quality scores.

DOI:

Publication date: June 24, 2020

Issue: Terroir 2016

Type: Article

Authors

Sandra M. OLARTE MANTILLA (1), Cassandra COLLINS (1), Patrick G. ILLAND (2) Catherine M. KIDMAN (1,3), Renata RISTIC (1), Paul K. BOSS (4), Charlotte JORDANS (1) and Susan E. P. BASTIAN (1)

(1) School of Agriculture, Food, & Wine, University of Adelaide, Waite Research Institute, PMB1, Glen Osmond, South Australia 5064, Australia
(2) Patrick IlandWine Promotions Pty Ltd, PO Box 131, Campbelltown, South Australia 5074, Australia
(3) Wynns Coonawarra Estate, Memorial Drive, Coonawarra, SA 5263, Australia
(4) CSIRO Agriculture Flagship, PMB2, Glen Osmond SA 5064, Australia

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IVES Conference Series | Terroir 2016

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Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., Guillaume, S. (2008). Is it possible to assess the spatial variability of vine water status? OENO One, 42(4), 203.
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Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France.
Scholander, P.F., Bradstreet, E.D., Hemmingsen, E.A., & Hammel, H.T. (1965). Sap pressure in vascular plants: Negative hydrostatic pressure can be measured in plants. Science, 148(3668), 339–346.