Determinants of optimal insecticide resistance management strategies.

The use of insecticides to control agricultural pests has resulted in resistance developing to most known insecticidal modes of action. Strategies by which resistance can be slowed are necessary to prolong the effectiveness of the remaining modes of action. Here we use a flexible mathematical model of resistance evolution to compare four insecticide application strategies: (i) applying one insecticide until failure, then switching to a second insecticide (sequential application), (ii) mixing two insecticides at their full label doses, (iii) rotating (alternating) two insecticides at full label dose, or (iv) mixing two insecticides at a reduced dose (with each mixture component at half the full label dose). The model represents target-site resistance. Multiple simulations were run representing different insect life-histories and insecticide characteristics. The analysis shows that none of the strategies examined were optimal for all the simulations. The four strategies: reduced dose mixture, label dose mixture, sequential application and label dose rotation, were optimal in 52%, 22%, 20% and 6% of simulations respectively. The most important trait determining the optimal strategy in a single simulation was whether or not the insect pest underwent sexual reproduction. For asexual insects, sequential application was most frequently the optimal strategy, while a label-dose mixture was rarely optimal. Conversely, for sexual insects a mixture was nearly always the optimal strategy, with reduced dose mixture being optimal twice as frequently as label dose mixture. When sequential application of insecticides is not an option, reduced dose mixture is most frequently the optimal strategy whatever an insect's reproduction.

Changes in field dose-response curves for demethylation inhibitor (DMI) and quinone outside inhibitor (QoI) fungicides against Zymoseptoria tritici, related to laboratory sensitivity phenotyping and genotyping assays.

BACKGROUND: Insensitivity of Zymoseptoria tritici to demethylation inhibitor (DMI) and quinone outside inhibitor (QoI) fungicides has been widely reported from laboratory studies, but the relationships between laboratory sensitivity phenotype or target site genotype and field efficacy remain uncertain. This article reports field experiments quantifying dose-response curves, and investigates the relationships between field performance and in vitro half maximal effective concentration (EC50 ) values for DMIs, and the frequency of the G143A substitution conferring QoI resistance. RESULTS: Data were analysed from 83 field experiments over 21 years. Response curves were fitted, expressed as percentage control, rising towards an asymptote with increasing dose. Decline in DMI efficacy over years was associated with a decrease in the asymptote, and reduced curvature. Field ED50 values were positively related to in vitro EC50 values for isolates of Z. tritici collected over a 14-year period. Loss of QoI efficacy was expressed through a change in asymptote. Increasing frequency of G143A was associated with changes in field dose-response asymptotes. CONCLUSION: New resistant strains are often detected by resistance monitoring and laboratory phenotyped/genotyped before changes in field performance are detected. The relationships demonstrated here between laboratory tests and field performance could aid translation between laboratory and field for other fungicide groups. © 2017 Society of Chemical Industry.

The Evolution of Fungicide Resistance Resulting from Combinations of Foliar-Acting Systemic Seed Treatments and Foliar-Applied Fungicides: A Modeling Analysis.

For the treatment of foliar diseases of cereals, fungicides may be applied as foliar sprays or systemic seed treatments which are translocated to leaves. Little research has been done to assess the resistance risks associated with foliar-acting systemic seed treatments when used alone or in combination with foliar sprays, even though both types of treatment may share the same mode of action. It is therefore unknown to what extent adding a systemic seed treatment to a foliar spray programme poses an additional resistance risk and whether in the presence of a seed treatment additional resistance management strategies (such as limiting the total number of treatments) are necessary to limit the evolution of fungicide-resistance. A mathematical model was developed to simulate an epidemic and the resistance evolution of Zymoseptoria tritici on winter wheat, which was used to compare different combinations of seed and foliar treatments by calculating the fungicide effective life, i.e. the number of years before effective disease control is lost to resistance. A range of parameterizations for the seed treatment fungicide and different fungicide uptake models were compared. Despite the different parameterizations, the model consistently predicted the same trends in that i) similar levels of efficacy delivered either by a foliar-acting seed treatment, or a foliar application, resulted in broadly similar resistance selection, ii) adding a foliar-acting seed treatment to a foliar spray programme increased resistance selection and usually decreased effective life, and iii) splitting a given total dose-by adding a seed treatment to foliar treatments, but decreasing dose per treatment-gave effective lives that were the same as, or shorter than those given by the spray programme alone. For our chosen plant-pathogen-fungicide system, the model results suggest that to effectively manage selection for fungicide-resistance, foliar acting systemic seed treatments should be included as one of the maximum number of permitted fungicide applications.

Fungicide resistance risk assessment based on traits associated with the rate of pathogen evolution.

BACKGROUND: A new fungicide resistance risk assessment method is described, based on traits (of pathogens, fungicides and agronomic systems) that are associated with rapid or slow occurrence of resistance. Candidate traits tested for their predictive value were those for which there was a mechanistic rationale that they could be determinants of the rate of resistance evolution. RESULTS: A dataset of 61 European cases of resistance against single-site-acting fungicides was assembled. For each case, the number of years from product introduction to first detection of resistance (the FDR time) was quantified - varying from 2 to 24 years. Short and long predicted FDR times represent high and low resistance risk respectively. Regression analysis identified traits that were statistically associated with FDR time. A model combining these traits explained 61% of the variation in FDR time. Validation showed that this predictive power was highly unlikely to have occurred by chance. CONCLUSION: Unlike previous methods, trait-based risk assessment can be used to assess resistance risk for fungicides with new modes of action, when there is no prior knowledge of resistance behaviour. Risk predictions using the new method provide a more reliable basis for resistance management decisions. © 2014 Society of Chemical Industry.

The emergence of resistance to fungicides.

Many studies exist about the selection phase of fungicide resistance evolution, where a resistant strain is present in a pathogen population and is differentially selected for by the application of fungicides. The emergence phase of the evolution of fungicide resistance--where the resistant strain is not present in the population and has to arise through mutation and subsequently invade the population--has not been studied to date. Here, we derive a model which describes the emergence of resistance in pathogen populations of crops. There are several important examples where a single mutation, affecting binding of a fungicide with the target protein, shifts the sensitivity phenotype of the resistant strain to such an extent that it cannot be controlled effectively ('qualitative' or 'single-step' resistance). The model was parameterized for this scenario for Mycosphaerella graminicola on winter wheat and used to evaluate the effect of fungicide dose rate on the time to emergence of resistance for a range of mutation probabilities, fitness costs of resistance and sensitivity levels of the resistant strain. We also evaluated the usefulness of mixing two fungicides of differing modes of action for delaying the emergence of resistance. The results suggest that it is unlikely that a resistant strain will already have emerged when a fungicide with a new mode of action is introduced. Hence, 'anti-emergence' strategies should be identified and implemented. For all simulated scenarios, the median emergence time of a resistant strain was affected little by changing the dose rate applied, within the range of doses typically used on commercial crops. Mixing a single-site acting fungicide with a multi-site acting fungicide delayed the emergence of resistance to the single-site component. Combining the findings with previous work on the selection phase will enable us to develop more efficient anti-resistance strategies.

Evaluation of a matrix to calculate fungicide resistance risk.

BACKGROUND: In the European Union, assessments of resistance risk are required by the regulatory authorities for each fungicide product and are used to guide the extent of anti-resistance strategies. This paper reports an evaluation of a widely used 'risk matrix', to determine its predictive value. Sixty-seven unique cases of fungicide resistance in Europe were identified for testing the risk assessment scheme, where each case was the first occurrence of resistance in a pathogen species against a fungicide group. RESULTS: In most cases, high-, moderate- and low-risk categories for fungicide, pathogen and agronomic systems were each associated with significant differences in the number of years from fungicide introduction to the first detection of resistance (FDR time). The combined risk, calculated by multiplying the individual risk factors using the risk matrix, had useful predictive power (72.8% of FDR time variance accounted for; VAF) for all fungicides, but only limited predictive power (25.8% VAF) for single-site acting fungicides (the predominant type). CONCLUSION: The resistance risk matrix has significant, but limited, predictive value. New fungicide modes of action, or pathogens that have become newly prevalent, cannot be assigned to risk categories until new methods of resistance risk assessment are developed.

Foliar pathogenesis and plant water relations: a review.

As the world population grows, there is a pressing need to improve productivity from water use in irrigated and rain-fed agriculture. Foliar diseases have been reported to decrease crop water-use efficiency (WUE) substantially, yet the effects of plant pathogens are seldom considered when methods to improve WUE are debated. We review the effects of foliar pathogens on plant water relations and the consequences for WUE. The effects reported vary between host and pathogen species and between host genotypes. Some general patterns emerge however. Higher fungi and oomycetes cause physical disruption to the cuticle and stomata, and also cause impairment of stomatal closing in the dark. Higher fungi and viruses are associated with impairment of stomatal opening in the light. A number of toxins produced by bacteria and higher fungi have been identified that impair stomatal function. Deleterious effects are not limited to compatible plant-pathogen interactions. Resistant and non-host interactions have been shown to result in stomatal impairment in light and dark conditions. Mitigation of these effects through selection of favourable resistance responses could be an important breeding target in the future. The challenges for researchers are to understand how the effects reported from work under controlled conditions translate to crops in the field, and to elucidate underlying mechanisms.