The variety mixture strategy assessed in a G × G experiment with rice and the blast fungus Magnaporthe oryzae.

Frequent and devastating epidemics of parasites are one of the major issues encountered by modern agriculture. To manage the impact of pathogens, resistant plant varieties have been selected. However, resistances are overcome by parasites requiring the use of pesticides and causing new economical and food safety issues. A promising strategy to maintain the epidemic at a low level and hamper pathogen's adaptation to varietal resistance is the use of mixtures of varieties such that the mix will form a heterogeneous environment for the parasite. A way to find the good combination of varieties that will actually constitute a heterogeneous environment for pathogens is to look for genotype × genotype (G × G) interactions between pathogens and plant varieties. A pattern in which pathogens have a high fitness on one variety and a poor fitness on other varieties guarantees the efficiency of the mixture strategy. In the present article, we inoculated 18 different genotypes of the fungus Magnaporthe oryzae on three rice plant varieties showing different levels of partial resistance in order to find a variety combination compatible with the requirements of the variety mixture strategy, i.e., showing appropriate G × G interactions. We estimated the success of each plant-fungus interaction by measuring fungal fitness and three fungal life history traits: infection success, within-host growth, sporulation capacity. Our results show the existence of G × G interactions between the two varieties Ariete and CO39 on all measured traits and fungal fitness. We also observed that these varieties have different resistance mechanisms; Ariete is good at controlling infection success of the parasite but is not able to control its growth when inside the leaf, while CO39 shows the opposite pattern. We also found that Maratelli's resistance has been eroded. Finally, correlation analyses demonstrated that not all infectious traits are positively correlated.