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“Towards a knowledge-base approach for an integrated control of Alternaria spp. in potatoes” (2013 – 2018)

Marc Goeminne1 Pieter Vanhaverbeke1

Kürt Demeulemeester2

Bernard De Baets3 Sofie Landschoot3

Jasper Carrette3

Michiel Vandecasteele3 Kris Audenaert3

Geert Haesaert3

o extensive monitoringo study of epidemiologyo diagnostics and population studieso implementation of DSS

with financial support of:Arysta LifeScience

BASFBayer CropScience

BelchimBoerenbond

De AardappelhoeveEastman

LutosaPhytoSystem

SanacSyngenta

WarnezEuroBlight | Freising, May 2018

2013 - 2017: monitoring on >100 fields per season + field trialsweekly assessments + sampling of leaf lesions (avg. 250 /year)

EuroBlight | Freising, May 2018

+ registration of cultural practices and weather data >> correlation analysis

2016201520142013 2017

= share of A. solani (%) in the total number of analysed leaf lesions


Some conclusions | 2013 – ‘17

In our climatic conditions, physiological resistance of the potato crop is at least as important as climate factors and presence of inoculum▪ leaf wetness has the most important effect on epidemics▪ crop rotation has a significant influence on disease occurrence (both onset

and level)

A certain level of senescence seems to be a condition for epidemic development, with A. solani being the pathogen in action in these cases

▪ only relatively early and severe epidemics result in significant crop losses

Although spread of the disease is slower compared to late blight, lesions can grow rapidly and destroy a leaf within 8 to 10 days

In the pathogen population, mutations with reduced sensitivity for QoI- and SDHI-fungicides are found in increasing numbers


F129L mutation in A. solani isolates


Year F129L mutations

2014(n = 52)

genotype I : 88%genotype II: 12%

0%83% 10%

2015(n = 46)


0%100% 50%

2016(n = 37)


0%87% 70%

G143A mutations inA. alternata:from 60% in 2013 (n = 47) to 91% in 2016 (n = 35)

a subset of isolates was also screened for the presence of different point mutations, which lead to a partial or total loss of sensitivity towards SDHI-fungicides, such as a.i. boscalid:

SDHI-fungicides


A. solani2014(n=41)

2015(n=42)

2016(n=37)

point mutations 63% 76% 54%

Wildtype 37% 24% 46%

▪ 2017: a not-so-typical potato growing season…• (very) high water deficit: was there an influence of

stress on early blight disease?

• how did the disease models react to the weather?

▪ …but, after all, a typical early blight -year:• (very) late start of disease incidence

• increase of A. solani towards end of season

• epidemic only in senescent crop

• no impact on yield or quality


some lessons learned from season 2017

June / July 2017: increased susceptibilitycaused by drought stress?

conidiophores

+

spore formation

spread by wind

and rain

germination

infection

lesion growth

spore-potential

diseasecycle

A. solani

• light|darkness• temperature• leaf wetness

• rainfall• LAI• wind speed• dry leaves!

• temperature• leaf wetness• RH

• leaf wetness• temperature

• temperature• leaf wetness

(~ totallesion size)

Epidemiologicalsimulation


Mean hours with leaf wetness

May 4.3

June 4.6

July 7.7

August 11.2

September 14.4

Total 9.3

4.34.6

7.7

11.2

14.4

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

May June July August September

Mean daily hours with leaf wetness

▪ the crop was certainly exposed to drought stress: what was the effect on early blight?• very difficult to assess

▪ we could also reverse the reasoning:• what is the stress factor we should take into account to

‘fit’ the model with our observations in field trials and untreated crop?




start disease (%)

28 aug 0.9

4 sept 25.6

11 sept 24.1

untreated 37.5


+ susceptibility of the potato cropincreased with 33% (factor 1.33)


start disease (%)

28 aug 0.9

4 sept 25.6

11 sept 24.1

untreated 37.5

IWT Alternaria | Gebruikersgroep, 8 dec 2017


▪ the crop was certainly exposed to drought stress:what was the effect on early blight?• very difficult to assess

▪ we could also reverse the reasoning:• what is the stress factor we should take into account to

‘fit’ the model with our observations?

➢ an increased susceptibility of 33% fits the model with the observations in untreated crop

➢ throughout the season, both models were run with an increased crop susceptibility of 50% to generate weekly advice for the potato growers.


2 0 1 3

2 0 1 4

2 0 1 5

2 0 1 6

2 0 1 7

“with the wisdom of hindsight”“It is easy to be wise after the event…”

- Arthur Conan Doyle


Season Early Blight -applications

Date

2013 0 – (1) (30 Aug)

2014 3 – (4)(21 Jul) ; 30 Jul ;8 Aug ; 25 Aug

2015 1 – (2) (14 Aug) ; 26 Aug

2016 2 – (4)(31 Jul) ; 9 Aug ;20 Aug ; (26 Aug)

2017(*) 3 – (4)17 Aug ; 27 Aug ; 3 Sep ; (10 Sep)

(*) taking into account an increased crop susceptibility (+33%) due to drought stress


Fungicide effectiveness

2016 2017

Avg. min max Avg. min max

Late blight + side effect

8,9 2 18 7,0 3 14

Early blight + late blight

0,9 0 4 0,4 0 3

Early blight 2,3 0 6 2,4 0 6

Total specific EB treatments (*) 3,2 2,8

(*) North of France (2016): 1,8 treatments

Number of treatments with EB-effect | 2016 & ‘17

Large gap & much room for improvement, without increasing the risk

The increase in the level of mutations is disturbing, considering the broad range of fungicides used

Better timing of applications - adapted toreal disease pressure - together with soundanti-resistance management should lead toless exposure of useful fungicides

Current practice vs. an IPM-approach


Current practice vs. an IPM-approach

formation of conidiophore + sporulation

spread by wind (and

rain)

germination

infection

lesion growth

sporulation potential

taking into accountthe physiological

resistance of the cropwhich influences

infection efficiency


interactions and

crop factors

modulation ofstart inoculum level

according to crop rotation

Simulation of the number of lesions caused by A. solani

based on weather data (Kruishoutem 2015) and taking

into account physiological resistance of the crop


0

10

20

30

40

50

60

70

80

29/jul 3/aug 10/aug 17/aug 25/aug 31/aug 7/sep 16/sep

onbehandeld

Observations of early blight

disease levels (%) in an untreated crop

(cv. Bintje) – Kruishoutem 2015


EB-fungicides 2018 | strategy?

add e.g. mancozeb (min. 1,5 kg /ha) to fungicides with known resistance issues [FRAC Guidelines: “QoI fungicides only in mixture with partners

contributing to the effective control”]

respect maximum number, dose rate and interval

alternate between different modes of action

alternating between different modes of action

Broad spectrum,

no resistance issues, moderate to good

efficiency

Specific,

no resistance issues (yet),very good efficiency

Specific,

excellent efficiency but real chance of a lesser result

due to mutations

mancozeb, maneb (+ late

blight fungicides with these a.i.),Unikat Pro

a.i. difenoconazole(Carial Star, Narita)

Amistar, Terminett, CabrioDuo, …;a.i. famoxadone (Tanos)


thanks for your attention!


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