Fungicide resistance management Fungicide resistance management Chemicals Regulation Directorate (CRD)
Fungicide resistance management Resistance management strategies should be based on evidence. A resistance management strategy should not compromise effective control.
Emergence and selection Emergence Selection Emergence: the resistant strain has to arise through mutation and successful invasion. Selection: resistant strain present and increasing in frequency.
Fungicides, insecticides, herbicides 0mortality 1 Low dose High dose SS SR RR Dose 0mortality 1 Low dose S Dose High dose R Most fungal plant pathogens are haploid and/or clonal.
Dose selection phase Spray programme is fixed. Does increased dose increase or decrease selection? Experimental published evidence. Increased dose selection increase no effect decrease Total experiments 16 1 2 (1) 19 models 8 0 0 8
Fungicide dose, missing evidence Mechanisms by which increased dose may reduce resistance risk. Stress induced mutation. Mutation limitation (emergence) Refugia. Converging dose response curves.
Are there generic principles?
Are there generic principles? Van den Bosch et al. 2011 Plant Pathology 60, 597-606
Generic principles Milgroom and Fry, 1988 Rate of increase of resistant strain. Rate of increase of sensitive strain. Exposure time. Strategy 1: Reduce both r R and r S. Strategy 2: Reduce r R relative to r S. Strategy 3: Reduce exposure time.
Generic principles
Generic principles increase No effect decrease total B Increase dose 16 1 2 19 C Increase spray number 6 0 0 6 D Split the dose 10 0 1 11 E Mix:adda fungicide 1 6 46 53 F alternate 1 4 0 5 G adjust timing 3 1 2 6
Generic principles increase no effect decrease total 7 Replace a spray 0 3 12 15 8 Mix and reduce dose 1 5 17 23 9 Alternate versus mixing 2 4 6 12
Generic principle Rate of increase of resistant strain. Rate of increase of sensitive strain. Exposure time. 84% of published cases agree with prediction. 5% of published cases contradict predictions. Qualitative instrument. Only selection phase.
Mixtures
Experiments and Models Experiments Model studies QoI, Azole, SDHI resistance monitoring.
Low risk + High risk, selection Rate of increase of resistant strain. Rate of increase of sensitive strain.
Low risk + High risk, selection Dose of the high-risk fungicide, DT 1.0 0.8 0.6 0.4 0.2 S=0.4 S=0.3 1 3 2 r S =0.2 r S =0.3 S=0.2 r S =0.4 S=0.1 r S =0.8 r S =0.6 0.0 0.0 0.2 0.4 0.6 0.8 1.0 Dose of the mixing partner, DM
Mixtures experiments Vast majority of cases mixing reduces selection for resistance. Mixing resistance selection Decreases Nodifference Increase Total 1 Multi site 27 1 1 29 Single site 14 2 0 16 2 Multi site 9 1 1 11 Single site 8 1 0 9
Model structure, selection leaf growth Healthy Infection* Sensitive/ Resistant strain Sporulation * Latent * senescence Infectious (dead/alive) Dead nonsporulating
Development of resistance in time Model validated against independent data (Hobbelen et al. 2011).
Low risk + High risk selection Mixing partner Low risk (% label dose) Max. effective life Constant dose Fungicide A Fungicide B 0 3 3 A B 40 5 6 80 7 8 120 8 10 160 9 12 200 10 14 Parameterised for Mycosphaerella graminicola, QoI type fungicide, Chlorothalonil type mixing partner
The model structure, emergence Deterministic Stochastic leaf growth Healthy senescence Infection* Infection Sensitive strain Latent * Resistant strain Latent Infectious mutation Infectious *) target parameters of the fungicide
Emergence of the resistant strain
Low risk + High risk Emergence Dose of Dose of high risk low risk 50 60 70 80 90 100 0 11 10 9 9 9 8 40 13 12 11 11 10 9 80 14 13 12 11 11 10 120 14 13 12 11 11 11 160 15 13 12 11 11 11 200 14 14 12 12 11 11 Variability in emergence time Larger dose of low-risk increases emergence time.
Summary: High risk + Low risk Conclusions: 1.Mixing does reduce selection. 2.By using an as large as acceptable low-risk dose: - Time till emergence is maximised - Time in selection phase is maximised. 3. Effective life is maximized by using the highest permitted dose of the low risk fungicide and using the dose of high risk fungicide needed for effective control.
Improved tools to rationalise and support stewardship programmes for SDHI fungicides to control cereal diseases in the UK Are model predictions correct? What are the practical consequences?
Experimental material: Prochloraz selects for the V136A mutation. Tebuconazole selects against the V136A mutation. Hypotheses: Increasing SDHI dose will reduce selection for azole resistant mutants. There will be an additional benefit from reducing dose of azole component
The slides with the data are removed. The data are owned by the SDHI-LINK consortium.
SDHI LINK conclusions and practical implications. Model predictions were good. The additional selection benefit of reducing the azole dose in the mix was small. If this is also true for epoxi and prothio, then we lose little selection benefit by using robust azole doses in SDHI mixtures.
Experiments and Models Generic principle predicts qualitative trends. Models and experiments are used to further quantify the efficacy. - Independent field data used to validate predictive models. - Models generate hypotheses to be field tested. The combination of field and modelling studies generates practical advise on fungicide resistance management tactics.
Resistance management Thank you for your attention.