Modeling Spatial Characteristics in the Biological Control of Fungi at Leaf Scale: Competitive Substrate Colonization by Botrytis cinerea and the Saprophytic Antagonist Ulocladium atrum

Synergism: biocontrol agents and biostimulants in reducing abiotic and biotic stresses in crop

In today's fast-shifting climate change scenario, crops are exposed to environmental pressures, abiotic and biotic stress. Hence, these will affect the production of agricultural products and give rise to a worldwide economic crisis. The increase in world population has exacerbated the situation with increasing food demand. The use of chemical agents is no longer recommended due to adverse effects towards the environment and health. Biocontrol agents (BCAs) and biostimulants, are feasible options for dealing with yield losses induced by plant stresses, which are becoming more intense due to climate change. BCAs and biostimulants have been recommended due to their dual action in reducing both stresses simultaneously. Although protection against biotic stresses falls outside the generally accepted definition of biostimulant, some microbial and non-microbial biostimulants possess the biocontrol function, which helps reduce biotic pressure on crops. The application of synergisms using BCAs and biostimulants to control crop stresses is rarely explored. Currently, a combined application using both agents offer a great alternative to increase the yield and growth of crops while managing stresses. This article provides an overview of crop stresses and plant stress responses, a general knowledge on synergism, mathematical modelling used for synergy evaluation and type of in vitro and in vivo synergy testing, as well as the application of synergism using BCAs and biostimulants in reducing crop stresses. This review will facilitate an understanding of the combined effect of both agents on improving crop yield and growth and reducing stress while also providing an eco-friendly alternative to agroecosystems.

Mode of Action of Microbial Biological Control Agents Against Plant Diseases: Relevance Beyond Efficacy

Microbial biological control agents (MBCAs) are applied to crops for biological control of plant pathogens where they act via a range of modes of action. Some MBCAs interact with plants by inducing resistance or priming plants without any direct interaction with the targeted pathogen. Other MBCAs act via nutrient competition or other mechanisms modulating the growth conditions for the pathogen. Antagonists acting through hyperparasitism and antibiosis are directly interfering with the pathogen. Such interactions are highly regulated cascades of metabolic events, often combining different modes of action. Compounds involved such as signaling compounds, enzymes and other interfering metabolites are produced in situ at low concentrations during interaction. The potential of microorganisms to produce such a compound in vitro does not necessarily correlate with their in situ antagonism. Understanding the mode of action of MBCAs is essential to achieve optimum disease control. Also understanding the mode of action is important to be able to characterize possible risks for humans or the environment and risks for resistance development against the MBCA. Preferences for certain modes of action for an envisaged application of a MBCA also have impact on the screening methods used to select new microbials. Screening of MBCAs in bioassays on plants or plant tissues has the advantage that MBCAs with multiple modes of action and their combinations potentially can be detected whereas simplified assays on nutrient media strongly bias the selection toward in vitro production of antimicrobial metabolites which may not be responsible for in situ antagonism. Risks assessments for MBCAs are relevant if they contain antimicrobial metabolites at effective concentration in the product. However, in most cases antimicrobial metabolites are produced by antagonists directly on the spot where the targeted organism is harmful. Such ubiquitous metabolites involved in natural, complex, highly regulated interactions between microbial cells and/or plants are not relevant for risk assessments. Currently, risks of microbial metabolites involved in antagonistic modes of action are often assessed similar to assessments of single molecule fungicides. The nature of the mode of action of antagonists requires a rethinking of data requirements for the registration of MBCAs.

A numerical study of combined use of two biocontrol agents with different biocontrol mechanisms in controlling foliar pathogens

Effective use of biocontrol agents is an important component of sustainable agriculture. A previous numerical study of a generic model showed that biocontrol efficacy was greatest for a single biocontrol agent (BCA) combining competition with mycoparasitism or antibiosis. This study uses the same mathematical model to investigate whether the biocontrol efficacy of combined use of two BCAs with different biocontrol mechanisms is greater than that of a single BCA with either or both of the two mechanisms, assuming that two BCAs occupy the same host tissue as the pathogen. Within the parameter values considered, a BCA with two biocontrol mechanisms always outperformed the combined use of two BCAs with a single but different biocontrol mechanism. Similarly, combined use of two BCAs with a single but different biocontrol mechanism is shown to be far less effective than that of a single BCA with both mechanisms. Disease suppression from combined use of two BCAs was very similar to that achieved by the more efficacious one. As expected, a higher BCA introduction rate led to increased disease suppression. Incorporation of interactions between two BCAs did not greatly affect the disease dynamics except when a mycoparasitic and, to a lesser extent, an antibiotic-producing BCA was involved. Increasing the competitiveness of a mycoparasitic BCA over a BCA whose biocontrol mechanism is either competition or antibiosis may lead to improved biocontrol initially and reduced fluctuations in disease dynamics. The present study suggests that, under the model assumptions, combined use of two BCAs with different biocontrol mechanisms in most cases only results in control efficacies similar to using the more efficacious one alone. These predictions are consistent with published experimental results, suggesting that combined use of BCAs should not be recommended without clear understanding of their main biocontrol mechanisms and relative competitiveness, and experimental evaluation.

Combined use of biocontrol agents to manage plant diseases in theory and practice

Effective use of biological control agents (BCAs) is a potentially important component of sustainable agriculture. Recently, there has been an increasing interest among researchers in using combinations of BCAs to exploit potential synergistic effects among them. The methodology for investigating such synergistic effects was reviewed first and published results were then assessed for available evidence for synergy. Correct formulation of hypotheses based on the theoretical definition of independence (Bliss independence or Loewe additivity) and the subsequent and statistical testing for the independence-synergistic-antagonistic interactions have rarely been carried out thus far in studies on biocontrol of plant diseases. Thus, caution must be taken when interpreting reported "synergistic" effects without assessing the original publications. Recent theoretical modeling work suggested that disease suppression from combined use of two BCAs was, in general, very similar to that achieved by the more efficacious one, indicating no synergistic but more likely antagonistic interactions. Only in 2% of the total 465 published treatments was there evidence for synergistic effects among BCAs. In the majority of the cases, antagonistic interactions among BCAs were indicated. Thus, both theoretical and experimental studies suggest that, in combined use of BCAs, antagonistic interactions among BCAs are more likely to occur than synergistic interactions. Several research strategies, including formulation of synergy hypotheses in relation to biocontrol mechanisms, are outlined to exploit microbial mixtures for uses in biocontrol of plant diseases.

Numerical studies of biocontrol efficacies of foliar plant pathogens in relation to the characteristics of a biocontrol agent

A previously published generic mathematic model has been used in a numerical study to understand the dynamics of foliar pathogens in relation to mechanisms, and timing and coverage of biocontrol agent (BCA) applications. With the model parameter values used, it was demonstrated that a BCA possessing either competition or induced resistance as the main mechanism of biological control was more effective in reducing disease development than a BCA with either mycoparasitism or antibiosis as its mechanism. Application coverage, ranging from 50 to 90%, had little effect on biocontrol efficacy, particularly for a BCA with competition and induced resistance as the main mechanism of biocontrol. Conversely, delayed application of BCA had more profound effects on biocontrol efficacy for those with competition or induced resistance as their main mechanism than those with mycoparasitism and antibiosis. Biocontrol efficacy was greatest for a single BCA combining competition with mycoparasitism or antibiosis. The efficacy for a single BCA combining induced resistance with competition critically depended on application time; the efficacy was greatly reduced for delayed applications. The present study suggests that development of an effective strategy for BCA application is critically dependent upon our quantitative understanding of several key biocontrol processes and their interactions. Without reliable quantitative estimation of these processes, it is impossible to make quantitative predictions about biological control and hence to optimize BCA application strategies.

A generic theoretical model for biological control of foliar plant diseases

We have developed a generic modelling framework to understand the dynamics of foliar pathogen and biocontrol agent (BCA) populations in order to predict the likelihood of successful biocontrol in relation to the mechanisms involved. The model considers biocontrol systems for foliar pathogens only and, although it is most applicable to fungal BCA systems, does not address a specific biocontrol system. Four biocontrol mechanisms (competition, antibiosis, mycoparasitism and induced resistance) were included within the model rubric. Because of the wide range of mechanisms involved we use Trichoderma/Botrytis as an exemplar system. Qualitative analysis of the model showed that the rates of a BCA colonising diseased and/or healthy plant tissues and the time that the BCA remains active are two of the more important factors in determining the final outcome of a biocontrol system. Further evaluation of the model indicated that the dynamic path to the steady-state population levels also depends critically on other parameters such as the host-pathogen infection rate. In principle, the model can be extended to include other potential mechanisms, including spatio-temporal heterogeneity, fungicide effects, non-fungal BCA and strategies for BCA application, although with a cost in model tractability and ease of interpretation.