The New Zealand Institute for Plant & Food Research Limited Botrytis Decision Support: Predicting and managing botrytis bunch rot Robert Beresford and Gareth Hill Plant & Food Research, Auckland
Managing botrytis risk In cool climate regions prone to botrytis, risk of rot at harvest must be managed In New Zealand, > 3% botrytis fruit rot at harvest adversely affects wine quality Management actions can include canopy density control, fungicides, biocontrols and inoculum removal.
Targeting botrytis management actions Fruit losses will be reduced and wine quality improved if stronger management is used when infection risk is greater Fungicides give reliable control, but are only available in NZ early in the season because of residue risks How can vineyard managers know early in crop development the degree of control that will be required for the entire season?
Understanding all the factors that contribute to botrytis risk is usually beyond the unaided perception of a vineyard manager. Weather Botrytis cinerea inoculum Vine phenology
Decision support Decision support tools can help with decision making about botrytis control by: Compiling and interpreting data on known risk factors Presenting key information in a way that helps with management decisions.
The research challenge for botrytis To enable botrytis prediction we needed variables that were easily measured in the vineyard, early in the season, which were reliable predictors of botrytis development during ripening This required specific data on the effects of weather, pathogen inoculum, vine phenology and botrytis management on the severity of botrytis epidemics.
Trans-Tasman Botrytis Project 2006-2009 Jointly funded by: New Zealand: Plant & Food Research, New Zealand Winegrowers Australia: Grape & Wine Research and Development Corporation New Zealand researchers (Plant & Food Research) Marlborough Hawke s Bay Auckland Dion Mundy Peter Wood Rob Beresford Rob Agnew Tracy Taylor Gareth Hill Warwick Henshall Australian researchers Univ. of Tasmania DPI Victoria Kathy Evans Justin Direen Jackie Edwards David Riches
Analysed botrytis epidemics from 50 vineyard trials Factors affecting botrytis severity at harvest in trial plots without botrytis fungicides Effect of fungicides, canopy management and inoculum management on botrytis control. Yarra Valley, Victoria Southern Tasmania Hawke s Bay Auckland Marlborough
The Bacchus infection risk model "Bacchus" risk index The Bacchus index: Botrytis infection in response to temperature when the vine canopy is wet Bacchus index hourly value 0.08 0.06 0.04 0.02 0.00 0 5 10 15 20 25 30 Temperature ( o C) during hours with wetness The seasonal index accumulation was used in the Trans- Tasman project to see how well it predicted regional botrytis severity.
Regional botrytis severity and Bacchus index Botrytis % severity at harvest 20 15 10 5 0 Bacchus index at 3% severity= 0.57 M T HB V y = 38.287x - 19.009 R 2 = 0.74 0.5 0.6 0.7 0.8 0.9 1.0 Mean Bacchus index, early-season A 3%
Latent infection measured at bunch closure 0-1 Logit botrytis severity at harvest -2-3 -4-5 Y= 0.7792 log10(x) - 3.394 Rsq= 19%; P=0.006 (3%) -6-7 -5 5 15 25 35 Latent botrytis incidence at PBC (%)
Botrytis-colonised bunch trash 12 y = 0.1695x + 0.1187 Mean botrytis severity at harvest (%) 10 8 6 4 2 R 2 = 0.65 3% 0 0 10 20 30 40 50 60 No. pieces botrytis-colonised trash per bunch
Botrytis decision support models From the Trans-Tasman project and other New Zealand vineyard trial data we identified: Weather and vine variables that were correlated with botrytis severity at harvest The effectiveness of different management actions in controlling botrytis across seasons and regions From these, the BDS models were developed with New Zealand Winegrowers and horticultural software company, HortPlus Ltd.
Botrytis Decision Support (BDS) Two separate models: 1. Early Season (flowering to véraison) Botrytis is unseen in the vineyard, but establishes the potential for a late-season epidemic.
Botrytis Decision Support (BDS) 2. Late Season (véraison to harvest) Apparition of rot during ripening and its exponential increase towards harvest.
Early Model user screen: Daily accumulation of the Bacchus index Pre-bunch closure Véraison Accumula3ng Bacchus index Rainfall Flowering Bacchus threshold line > 20 days above the threshold indicates risk of a major epidemic (> 3% botrytis rot at harvest).
Botrytis early-season management Sprays of fungicides (highly effective) and biocontrols (may help under low disease pressure)
Botrytis early-season management Reducing vine canopy density by leaf plucking, shoot thinning or vine trimming Unplucked vine canopy Leaf plucked canopy with 70% fruit exposure
Botrytis early-season management Bunch trash removal (by air blast) Botrytis-colonised aborted berries
Early Model user screen: Managed Bacchus risk threshold Véraison 55 days above, unmanaged Each management ac3on raises the Bacchus threshold step-wise Flowering 3 days above, managed Fungicides Canopy management
Botrytis late in the season (pre-harvest) For the vineyard manager, botrytis in the ripening bunches comes down to a race between sugar accumulation towards a harvestable level and the rate that rot progresses.
Late Season Model user screen: Target o Brix at harvest o Brix Botry3s Botry3s severity at harvest
Future predic3on o Brix observa3ons Botry3s observa3ons Current date
Harvest 5 days earlier
Botrytis Decision Support Models - conclusion As well decision support, BDS models provide education and training on botrytis biology and management For new areas local calibration trials are required for responses to climate and disease management The Early Model is also being used in Tasmania as part of a state-wide agricultural decision support project Currently being developed as a smartphone app see presentation by Gareth Hill (this session).
Thank you www.botrytis.co.nz www.plantandfood.co.nz robert.beresford@plantandfood.co.nz