Mileos ® is a web-based, on-farm Decision Support System (DSS) available to potato growers to control potato late blight (LB) caused by Phytophthora infestans. It results from a collaboration between ARVALIS and the French Ministry of Agriculture (SRAL Nord-Pas de Calais). The 2 pre-existing DSS’s (MILPV and Mildi-LIS) have been fused, in 2009, into an optimized tool, entirely reviewed and up-dated in order to better meet national demand and help farmers to comply with EU regulations.
With Mileos® (see www.mileos.fr), the fungicide application on potato crops is optimized, triggered according a real-time LB risk assessment taking into account environmental data (climatic and disease pressure), agronomical data such as cultivar’s LB resistance and crop health practices for potato fields such as chemical input, cultivar choice and irrigation.
Mileos ® is an Decision Support System (DSS) based on the epidemiological model Milsol by calculating the number of live spores available on the crop foliage, and in the environment. More recently, the model was revised and set up as 4 different compartments (Figure 1) strictly simulating the different steps of a LB epidemiological cycle, from contamination to dispersal as well as the overlapping successive cycles. Required input variables are hourly temperature, relative humidity and rainfall. Additional environmental data: crop growth rate, cultivar resistance level, disease pressure in the environment, irrigation) are daily updated & contribute to the set up of action thresholds: treat or not, and which fungicide to choose (Figure 2).
To tune up the recommendation given by the DSS, methods of sensitivity analysis were applied to quantify the amount of uncertainty in the model outputs attributable to the ‘historical’ parameters: LB primary inoculum, incubation level, multiplication rate of potential sporulation, maximal temperature for sporulation and minimal temperature for survival. Observed field data will be compared with the simulated ones in order to have a more accurate value for each of these parameters. These updated values will be validated by running historical sets of climatic data.
The results of sensitivity analysis have shown that two parameters, ie primary inoculum and multiplication rate of potential sporulation, have a very large contribution to the output data (high LB risk/low LB risk) given by the model. New revised values for these parameters were suggested by comparing simulated data with field observations (Figures 3 and 4).
Concerning the primary inoculum prediction, the analysis has identified: - available variables of interest that could better predict primary inoculum and that they were region specific. These variables are disease enhancing factors such as (Figure 5) i) the total amount of LB risk in the previous season, ii) the number of days with rain in September and November of the previous year and in January (same year), and iii) the number of days with frozen soil in February -for each region, a reduction of the standard value for primary inoculum could be tempted without compromising an efficient crop protection. -the adjusted R² of this model is 0.9.
Lastly, concerning the parameter “weight of P. infestans contamination”, the data analysis suggested to define as unique criteria to trigger the first and subsequent LB treatments for the protection according to the cultivar’s level of resistance. The adding values for ‘contamination-weight’ during the season (March to August) seems to be a good indicator to compare LB pressure within different potato production regions as well as within years (Figure 6).
D. GAUCHER (1), A. CHAIGNEAU(1), F. LARRIEU(1), A. VAUDATIN(1) and C. CHATOT (2)
(1) ARVALIS-Institut du végétal, Experimental Station, F-91720 BOIGNEVILLE email@example.com
(2) GERMICOPA R&D, Kerguivarc’h, F-29520 CHATEAUNEUF du FAOU firstname.lastname@example.org