How to develop smarter host mixtures to control plant disease?
  A looming challenge for agriculture is sustainable intensification of food production to feed the growing human population. Current chemical and genetic technologies used to manage plant diseases are highly vulnerable to pathogen evolution and are not sustainable. Pathogen evolution is facilitated by the genetic uniformity underlying modern agroecosystems, suggesting that one path to sustainable disease control lies through increasing genetic diversity at the field scale by using genetically diverse host mixtures. We investigate how host mixtures can improve disease control using a population dynamics model. We find that when a population of crop plants is exposed to host-specialized pathogen species or strains, the overall disease severity is smaller in the mixture of two host varieties than in each of the corresponding pure stands. The disease severity can be minimized over a range of mixing ratios. These findings may help in designing host mixtures that efficiently control diseases of crops. We then generalize the model to describe host mixtures with many components. We find that when pathogens exhibit host specialization, the overall disease severity decreases with the number of components in the mixture. As the degree of specialization increases, the decrease in disease severity becomes larger. Using these model outcomes, we propose ways to optimize the use of host mixtures to decrease disease in agroecosystems. 
Alexey Mikaberidze, Bruce McDonald and Sebastian Bonhoeffer
q-bio.PE