Models on micrometeorological parameters for fungal pathogen spread prediction

Fungal risk models are aimed at foreseeing the development of plant infections over time and space by exploiting the relations between a pathogen, the host plant, and the environmental parameters. Currently, the development of fungal risk models is even more crucial to understand how pathogen spread will be modified by climate emergency. Indeed, air temperature, humidity, and precipitation are crucial factors in air-borne fungal infection. Fungal diseases are serious concerns in floriculture for their effects on growth and aesthetic appearance affecting the product marketability. Since roses are essential in floricultural sector, both as landscaping shrubs and for the production of cut flowers, some commercial species were used for testing fungal risk models. Thus, the aim of this work was the development of alert systems for fungal pathogen outbreaks in roses based on new models on micrometeorological parameters or the improvement of existing ones. The spread of two important fungi affecting roses, i.e., grey mould and powdery mildew, was monitored for one year in combination with a weekly record of plant symptoms. Two trials were set up by simulating the commercial rose production systems: i) landscaping shrubs in open-field, 384 roses belonging to three cultivars with different susceptibility to air-borne fungi; ii) cut flower roses into a greenhouse, 288 plants belonging to three cultivars with different susceptibility. Micrometeorological parameters were acquired by a weather station as well as by extra and intra-canopy air humidity and temperature sensors and substrate humidity and temperature sensors. Main results and issues are presented focusing on the differences between the model output and the symptom records.