Shiraz grapes growing in South Australia's Barossa Valley

Shiraz grapes growing in South Australia's Barossa Valley

Precision Viticulture: understanding vineyard variability

Research into vineyard variability and the development of so-called ‘Precision Viticulture’ (PV) is helping grapegrowers and winemakers optimise vineyard performance according to yield, quality and natural resource management goals

  • 27 June 2006 | Updated 4 April 2014

In this article

  1. Overview
  2. Publishing History

Overview

Page 1 of 2

Optimising vineyard performance

Land is variable. As a consequence, productivity across farms and paddocks is also variable.

Grapegrowers and winemakers have known about vineyard variability for as long as they have been growing grapes and making wine.

However, without methods for observing or reacting to this variation, the default option has been to treat it as ‘noise’ and to manage large blocks as though they were uniform.

The ready availability of global positioning systems (GPS) and geographical information systems (GIS), coupled with tools for measuring and monitoring vineyards at high spatial resolution, such as remote and proximal canopy sensing, high resolution soil survey, yield monitoring and, in prototype form, fruit quality sensing, changes things considerably.

Grapegrowers and winemakers now have the opportunity to tailor their management to address limitations to production, or react to market opportunity through selective harvesting and product streaming.

There is therefore an increased likelihood that the outputs from the production system are the desired ones.

Understanding variability

Since publishing the first winegrape yield map in 1999, our research has focused on understanding the nature, extent and causes of vineyard variability and on helping grapegrowers and winemakers to use PV tools to better target their management.

In commercial vineyards operated by or collaborators, we have demonstrated that:

"Grapegrowers and winemakers have known about vineyard variability for as long as they have been growing grapes and making wine.

  • Zones delineated on the basis of yield monitoring and/or remotely sensed imagery are stable in time (i.e. between seasons, when assessed at the same stage of the season – typically veraison, the onset of ripening) and generally relate to variation in the land (soil, topography) underlying the vineyard
  • Zone delineation of grape quality parameters is less certain because it has relied on hand sampling at a much lower data density (typically 26 samples/ha) than that provided by remote sensing (40,000 pixels/ha for typical 50cm imagery). However, in almost all of the published examples, commercially important differences in fruit quality exist between zones delineated using yield and/or imagery; cane-pruned vineyards are a possible exception where yield maps may not offer commercially useful assistance
  • With the exception of some work in which we used an on-the-go modification to the Multiplex™ sensor mounted on a harvester, no-one has yet collected fruit quality data at a spatial density comparable to that underpinning yield maps or imagery, a fact that contributes to the uncertainty of fruit quality zone delineation and the yield:quality nexus
  • However, whilst it is thought that fruit quality zones follow the same spatial pattern as yield-imagery zones, their rank order may not be constant, in contrast to yield-imagery zones which do show constant rank order (i.e. high to low)
  • Selective harvesting, using information such as that alluded to above, may be highly profitable, whether employed in situations where winery infrastructure permits small tonnage ferments, or in production systems geared to large tonnage fermentation.

We have also demonstrated that the traditional approach to vineyard soil survey (75 m grid) is too blunt an instrument to provide an understanding of the reasons for variability in vineyard performance.

More effective is careful examination of soils at points strategically chosen by using high resolution survey tools such as electromagnetic measurements (EM38).

A recent survey of industry attitudes to Precision Viticulture (PV) and its adoption highlighted that 66 per cent of respondents believed that PV is already delivering or will deliver a clear benefit to their business.

Developing new experimental techniques

Much of our recent work has focused on using high resolution spatial data as an input to vineyard (re)-design, developing new methods for viticultural experimentation, using careful management to manipulate vine performance and using our understanding of variability to control wine flavour and aroma in the vineyard.

New approaches to experimentation, in which traditional plot-based vineyard experiments are replaced by whole-of-vineyard trials, give valuable insights into how vineyard variability can be managed.

Tools such as yield monitors are used to understand the variable response of vines to different management practices and to explore opportunities for improved, more targeted management.

To find out more information and resources about understanding variability in agricultural production.