Decision support systems halve fungicide use compared to calendar-based strategies without increasing disease risk

Lázaro, Elena; Makowski, David; Civera, Antonio Vicent

doi:10.1038/s43247-021-00291-8

Cited by 33 publications

(23 citation statements)

References 36 publications

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“…This has motivated the development of integrated pest management (IPM) throughout the world [ 4 ]. The core of IPM is the process of decision-making, including the decision as to whether and when plant protection actions are required and/or economically justified; decision making in IPM increasingly depends on the development of disease models, decision rules, and risk algorithms [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

A Systematic Map of the Research on Disease Modelling for Agricultural Crops Worldwide

Fedele

Brischetto

Rossi

et al. 2022

Plants

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In this work, we developed a systematic map to identify and catalogue the literature pertaining to disease modelling for agricultural crops worldwide. Searches were performed in 2021 in the Web of Science and Scopus for papers reporting any type of disease model for 103 crops. In total, 768 papers were retrieved, and their descriptive metadata were extracted. The number of papers found increased from the mid-1900s to 2020, and most of the studies were from North America and Europe. More disease models were retrieved for wheat, potatoes, grapes, and apples than for other crops; the number of papers was more affected by the crop’s economic value than by its cultivated area. The systematic map revealed an underrepresentation of disease models for maize and rice, which is not justified by either the crop economic value or by disease impact. Most of the models were developed to understand the pathosystem, and fewer were developed for tactical disease management, strategic planning, or scenario analysis. The systematic map highlights a variety of knowledge gaps and suggests questions that warrant further research.

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Section: Introductionmentioning

confidence: 99%

A Systematic Map of the Research on Disease Modelling for Agricultural Crops Worldwide

Fedele

Brischetto

Rossi

et al. 2022

Plants

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“…A spatially explicit model would also allow reactive disease management to be optimised (Cunniffe et al, 2015b(Cunniffe et al, , 2016, which would correspond to levels of fungicide treatment depending on local disease intensity, or even the results of a decision support type system (Carisse, 2010;Jorgensen et al, 2017;Lázaro et al, 2021).…”

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confidence: 99%

Optimal Resistance Management for Mixtures of High-Risk Fungicides: Robustness to the Initial Frequency of Resistance and Pathogen Sexual Reproduction

Taylor

Cunniffe

2023

Phytopathology®

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There is a strong consensus that selection for fungicide resistant pathogen strains can be most effectively limited by using applications of mixtures of fungicides designed to balance disease control against selection. However, how to do this in practice is not entirely characterised. Previous work indicates optimal mixtures of pairs of fungicides which are both at a high risk of resistance can be constructed using pairs of doses which select equally for both single resistant strains in the first year of application. What has not been addressed thus far is the important real-world case in which the initial levels of resistance to each fungicide differ, for example because the chemicals have been available for different lengths of time. We show how recommendations based on equal selection in the first year can be sub-optimal in this case. We introduce a simple alternative approach, based on equalising the frequencies of single resistant strains in the year that achieving acceptable levels of control is predicted to become impossible. We show that this strategy is robust to changes in parameters controlling pathogen epidemiology and fungicide efficacy. We develop our recommendation using a pre-existing, parameterised model of Zymoseptoria tritici (the pathogen causing Septoria leaf blotch on wheat), which exemplifies the range of plant pathogens which predominantly spread clonally, but for which sexual reproduction forms an important component of the life cycle. We show that pathogen sexual reproduction can influence the rate at which fungicide resistance develops, but does not qualitatively affect our optimal resistance management recommendation.

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“…Another consideration is how risk-averse the grower is – in particularly high disease pressure years the improved control offered by higher numbers of application can be notable (Figure 4). One approach could be to use more applications in the highest disease pressure years but in general use the minimum number of applications possible to achieve a desired level of disease control, perhaps with the aid of a decision support system ( Lázaro et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Modelling quantitative fungicide resistance and breakdown of resistant cultivars: designing integrated disease management strategies for Septoria of winter wheat

Taylor

Cunniffe

2022

Preprint

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Plant pathogens respond to selection pressures exerted by disease management strategies. This can lead to fungicide resistance and/or the breakdown of disease-resistant cultivars, each of which significantly threaten food security. Both fungicide resistance and cultivar breakdown can be characterised as qualitative or quantitative. Qualitative (monogenic) resistance/breakdown involves a step change in the characteristics of the pathogen population with respect to disease control, often caused by a single genetic change. Quantitative (polygenic) resistance/breakdown instead involves multiple genetic changes, each causing a smaller shift in pathogen characteristics, leading to a gradual alteration in the effectiveness of disease control over time. Although resistance/breakdown to many fungicides/cultivars currently in use is quantitative, the overwhelming majority of modelling studies focus on the much simpler case of qualitative resistance. Further, those very few models of quantitative resistance/breakdown which do exist are not fitted to field data. Here we present a model of quantitative resistance/breakdown applied to Zymoseptoria tritici, which causes Septoria leaf blotch, the most prevalent disease of wheat worldwide. Our model is fitted to data from field trials in the UK and Denmark. For fungicide resistance, we show that the optimal disease management strategy depends on the timescale of interest. Greater numbers of fungicide applications per year lead to greater selection for resistant strains, although over short timescales this can be oﬀset by the increased control offered by more sprays. However, over longer timescales higher yields are attained using fewer fungicide applications per year. Deployment of disease-resistant cultivars is not only a valuable disease management strategy, but also offers the secondary benefit of protecting fungicide effectiveness by delaying the development of fungicide resistance. However, disease-resistant cultivars themselves erode over time. We show how an integrated disease management strategy with frequent replacement of disease-resistant cultivars can give a large improvement in fungicide durability and yields.

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Decision support systems halve fungicide use compared to calendar-based strategies without increasing disease risk

Cited by 33 publications

References 36 publications

A Systematic Map of the Research on Disease Modelling for Agricultural Crops Worldwide

A Systematic Map of the Research on Disease Modelling for Agricultural Crops Worldwide

Optimal Resistance Management for Mixtures of High-Risk Fungicides: Robustness to the Initial Frequency of Resistance and Pathogen Sexual Reproduction

Modelling quantitative fungicide resistance and breakdown of resistant cultivars: designing integrated disease management strategies for Septoria of winter wheat

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