Decision Support Systems in Agriculture: Administration of Meteorological Data, Use of Geographic Information Systems(GIS) and Validation Methods in Crop Protection Warning Service - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 344

disease onset
classification

early late sum correct (%)

early 54 39 93 58.06%
late 80 164 244 67.21%
sum 134 203 337 64.69%
Table 4. Results of the classification of the disease onset (powdery mildew on sugar beet)
forecasted by the model ERYBET1 using binary logistic regression with “cut off” value =
0.74

4.2 Validation of type 2 models
Type 2 models are examples for classical simulation models. Generally, they are very complex.
The aim is to predict the epidemic development (expressed as disease severity and/or disease
incidence) for the diseases or to predict the various development stages of insects. These
models are used, in the examination phase, as a basis for identifying the parameters and
variables for the construction of type 1 and 3 models. Examples of these models are
CERCODEP which is able to simulate the epidemics of Cercospora leaf spot on sugar beet
(Rossi , et al. , 1994), RUSTDEP for leaf rust ( Puccinia recondita ) on winter wheat (Rossi , et al. ,
1997b), SEPTRI2 for leaf blotch ( Septoria triciti ) on winter wheat (Erven , et al. , 2008, Erven , et al. ,
2010) , SIMPHYT2 for the potato leaf blight (Roßberg , et al. , 2001) and SIMLEP2 to forecast the
phenological development of the Colorado potato beetle (Roßberg , et al. , 1999).
The following three models are used as examples for validation methods: PUCREC for leaf
rust in winter rye ( Puccinia recondita ), PUCTRI for leaf rust in winter wheat ( Puccinia
triticina ) and SEPTRI for leaf blotch ( Septoria triciti ) in winter wheat.
The first two models simulate the development of the epidemics of rust on different leaf
layers expressed as disease incidence (Racca , et al. , 2008, Räder , et al. , 2007). Models were
validated with both subjective and statistical methods of field data, collected from 2002 to
2005. In total, 51 data sets for PUCREC and 37 for PUCTRI were available to investigate the
predictive ability of the models.

100

90

80

70

60

50

40

30

20

10

0

04/05/03 11/05/03 18/05/03 25/05/03 01/06/03 08/06/03 15/06/03

Date

Fig. 7. PUCREC - Simulated disease incidence (DI) on the flag leaf (F). weather station
Herxheimweyher (Rhineland-Palatinate - Germany) in 2003. (▬ simulation, • field data, +
confidence interval of the field data)