Poster Presentation Science Protecting Plant Health 2017

Simulation of the progression of yellow spot on wheat using a functional-structural plant model (#251)

Katarina Streit 1 , Christopher Bahr 1 2 , Jochem B Evers 3 , Michael Renton 1
  1. Schools of Biological Sciences, Agriculture & Environment, University of Western Australia, Crawley, WA 6009, Australia
  2. Department Ecoinformatics, Biometrics and Forest Growth, University of Göttingen, 37077 Göttingen, Germany
  3. Centre for Crop Systems Analysis, Wageningen University, 6708, PB, Wageningen, The Netherlands

Functional-structural plant models (FSPMs) aim at simulating mutual interactions between plant architecture and physiological processes in plants, affected by environmental conditions. Typically, an FSPM represents processes at the scale of plant organs, such as leaves and stem segments. This kind of approach can then be combined with an epidemiological model for a foliar plant pathogen. This combination then allows us to investigate how the growing plant structure interacts with climatic conditions (rain, temperature, wind) to affect the life cycle of the pathogen, its spread through the crop canopy, and its impact on the growth and development of the plant.

In our study we couple an FSPM of wheat (Triticum) with a model of the life cycle and dispersal of the yellow spot pathogen (Pyrenophora tritici-repentis). In our model, the growth of the wheat is driven by light interception and temperature, which control photosynthesis calculation and carbon allocation among different organs, respectively. The model of yellow spot is driven by temperature, rain and wind data. It predicts maturation and release of ascospores, initiation and maturation of primary and secondary infection of leaves, as well as release and dispersal of conidia spores across the simulated canopy. The pathogen model operates at the scale of leaf segments.

The overall aim of the study is to give deeper insights into plant-pathogen-environment interactions, and to help farmers predict disease risk and manage their crops based on weather conditions. The model will be tested for different locations and weather conditions across Western Australia.