Predicting infection of strawberry fruit by Mucor and Rhizopus spp. under protected conditions

Abstract

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Postharvest spoilage of strawberry grown under protection, caused by Mucor spp. and Rhizopus spp., has recently become more common in the UK, but there is insufficient knowledge to develop and implement integrated management against Mucor and Rhizopus. Field sampling was conducted to obtain field data for developing models to predict the infection of Mucor and Rhizopus on strawberry fruit. Fruits were exposed to naturally occurring inoculum for a period of 24 hours before surface-sterilisation and incubation to estimate the level of infection by Mucor and Rhizopus. The observed incidence data, together with climatic conditions and inoculum trap counts, were used analysed firstly within the framework of (1) generalised linear model (GLM), and (2) classification tree. Field sampling confirmed previous research that ripening/ripe strawberry fruits are more susceptible to infection by Mucor and Rhizopus. Climatic variability, particularly in vapour pressure deficit, appears to be more important in influencing the rotting incidence of both Mucor and Rhizopus. However, the predictability of both Mucor and Rhizopus, whether as a continuous variable (incidence) in the GLM analysis or as a categorical risk in classification tree analysis, is too low to be of practical value based on those predictors used in the present study. Thus, current management may have to be based on scheduled preharvest application of alternative products to reduce infection and local pathogen inoculum as well as adopting management practice to minimise pathogen inoculum in the planting. Future research is needed to develop methods for rapid yet accurate in situ quantification of pathogen inoculum to improve disease risk predictions.

Keywords

• strawberry soft rot
• classification
• recursive trees
• fruit maturity
• variability in climatic conditions