2.8.11 MODELLING THE DYNAMICS OF SIMULTANEOUSLY OCCURRING FUNGAL LEAF DISEASES AND THEIR INTERACTIONS WITH HOST GROWTH AND DEFOLIATION OF PHASEOLUS BEANSB HAU and MEIER Institut für Pflanzenkrankheiten und Pflanzenschutz, Universität Hannover, Herrenhäuser Strasse 2, D-30419 Hannover, Germany
The progression of the diseases was modelled using Jeger’s [3] approach with coupled differential equations for the disease categories but given in area units. As the infectious periods of the three diseases were much longer than the life time of the leaves, only differential equations for the latent and the infectious disease categories were needed for each disease. An additional term was added to both equations to take into account the reduction due to defoliation. While the latent infected area decreased proportional to the total defoliation, the loss of infectious area was more than proportional. The parameter estimation of the five data sets was carried out using an iterative approach. In all cases the observed disease progress curves including their decreases at the end of the season could be well described by the model. Similarly, the leaf area of a single plant could be simulated under the influence of the three diseases. The coupling of disease progression with host growth and defoliation decreased the leaf area available for infection and for yield formation. Based on the experiment 1995 in Piracicaba with a total maximum disease severity of less than 5%, the reduction in HLAD was estimated to be 2.7%. If the effects of the diseases on host growth would have been neglected, the reduction in HLAD would be only 1.9%. When higher disease severities were simulated, for instance for angular leaf spot an epidemic with a maximum severity of 11.2% which is in the range observed in [1], the reduction in HLAD would be 6.6%. Applying the model with the same parameter values but excluding the effects on leaf area growth and defoliation, HLAD would be reduced by 4.8% although the maximum disease severity would be slightly higher (13.3%). In the model, the parameters are assumed to be constant during a season which leads to different parameter values in the experiments conducted. As disease progression and host development are influenced by external factors, like temperature and relative humidity, their effects on the rates have to be quantified in order to generalize the model for variable environments.
The financial support of the European Commission (Project ERBIC18CT960037) is gratefully acknowledged. |