Abstract

Although the use of biocontrol agents (BCAs) to manage plant pathogens has emerged as a sustainable means for disease control, global reliance on their use remains relatively insignificant and the factors influencing their efficacy remain unclear. In this work, we further developed an existing generic model for biocontrol of foliar diseases, and we parametrized the model for the Botrytis cinerea–grapevine pathosystem. The model was operated under three climate types to study the combined effects on BCA efficacy of four factors: (i) BCA mechanism of action, (ii) timing of BCA application with respect to timing of pathogen infection (preventative vs. curative), (iii) temperature and moisture requirements for BCA growth, and (iv) BCA survival capability. All four factors affected biocontrol efficacy, but factors iii and iv accounted for > 90% of the variation in model simulations. In other words, the most important factors affecting BCA efficacy were those related to environmental conditions. These findings indicate that the environmental responses of BCAs should be considered during their selection, BCA survival capability should be considered during both selection and formulation, and weather conditions and forecasts should be considered at the time of BCA application in the field.

Highlights

  • Biocontrol of plant pathogens has emerged as a sustainable method of disease management and as a viable way to reduce the application of chemicals in agriculture [1,2,3,4]

  • The model was used to study the effect of the following sources of variation on Botrytis bunch rot (BBR) development: (i) mechanisms of action (MOA) of the biocontrol agents (BCAs) (2 levels: mainly competition and mainly mycoparasitism); (ii) BCA application time (2 levels: preventative and curative); (iii) BCA strain (9 levels: 3 ranges of temperatures combined with 3 moisture requirements for BCA growth); and (iv) BCA survival capability (3 levels: low, medium, and high)

  • A factorial analysis of variance (ANOVA) was carried out for each climate type to determine whether the efficacy of each BCA combination was significantly affected by the main sources of variation (MOA, application time, strain, and survival capability) or their interactions

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Summary

Introduction

Biocontrol of plant pathogens has emerged as a sustainable method of disease management and as a viable way to reduce the application of chemicals in agriculture [1,2,3,4]. Jeger et al [28] developed a mean-field deterministic model that is able to predict the likelihood of the successful control of foliar diseases by a single BCA in relation to the biocontrol mechanisms involved The latter model is a standard susceptible-infected-removed (SIR) model, in which host–pathogen dynamics are coupled with pathogen–BCA dynamics through four biocontrol mechanisms: mycoparasitism, competition, antibiosis, and induced plant host resistance. Improved versions of this model were subsequently proposed to compare the effects of using a single BCA with two biocontrol mechanisms [29] vs the combined use of two BCAs, each with an individual mechanism [30], or the effects of constant vs fluctuating temperatures on biocontrol efficacy [31]. We describe the model, its parametrization for the BBR case-study (i.e., Botrytis bunch rot in grapes caused by Botrytis cinerea), and (iii) model simulations for different BCAs under different climate types

Model Description
State Variables and Connecting Flows
Driving Variables for the Pathogen
Driving Variables for the BCA
Model Output
Model Running
Examples of total the total occupied the pathogen as affected
Findings
Discussion and Conclusions
Full Text
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