Modelling the in vitro pre-infection dynamics of Colletotrichum spp. isolated from yellow passion fruit in function of environmental variables

Abstract

AbstractBrazil is the largest world producer of yellow passion fruit, but the mean yield (14.3t.ha-1) is less than half the potential of the crop. Part of this difference can be explained by plant health problems, including anthracnose caused by Colletotrichum spp. In regions with favorable climatic conditions, anthracnose can be a factor of significant yield reduction, but these regions have not yet been zoned. The objective of this study was to model the pre-infection dynamics of the fungus. The influence of temperature and photoperiod was studied on mycelia growth, sporulation and conidia germination. Mathematical models were fitted to the results and the optima for the environmental variables were estimated. The maximum mycelia growth was estimated to occur at 26.5°C. Between 24.5°C and 28.5°C the fungus grew from 95% to 100% of the estimated maximum. Temperatures below 13°C or above 34°C were harmful to mycelia growth. Temperatures over 26°C were the most favorable to sporulation while below 13°C sporulation was only 5% of the maximum. Optimum germination occurred between 25°C and 29°C with the ideal wetness period between 11h and 13h. These results can be used as a basis for zoning the risk of anthracnose occurrence in passion fruit producing regions.Significance and Impact of the StudyMany diseases affect the yellow passion fruit crop, limiting its yield; among them anthracnose, caused by Colletotrichum spp. The disease occurs in both field (leaf and stem symptoms) and post-harvest (fruits) conditions. Understanding the role environmental conditions play in the biological cycle of such diseases is essential for developing management strategies. By modelling mycelial growth, spore production and spore germination of Colletotrichum spp. as affected by temperature, photoperiod and wetness period, it was possible to characterize the pathogen’s pre-infectional dynamics. The results should be used as a first approximation to estimate the risk of anthracnose occurrence in pre- or post-harvest.