Optimising composition and spatial deployment of diversity in agricultural crops for disease control and yield enhancement
1. What is the optimum patch size / pattern / distribution for cultivars (of cereals experimentally) for a) disease reduction, b) yield benefit.
This could be for between 2 and say 6 cultivars, (in equal or different proportions) and up to say 3 different diseases (presence / absence / quantitative variation / combinations), so various degrees of complexity. Parallel experimentation could be carried out but constrained by practicalities of either plot drills where individual genotype rows and plots can be sown in patterns, or commercial drills where the scale is larger but control over distribution is very crude.
2. What are the effects of scenarios in (1) on pathogen evolution / pathogen population stability / variation.
Pathogen populations can be complex, with individual genotypes having virulence/specificity and/or aggressiveness/fitness traits which are generally in repulsion (Marshall et al., 2009)
(e.g. high aggressiveness – low virulence complexity)
Again, this could be in parallel with experimental work where we sample and analyse pathogen population structure using molecular markers, using either natural populations or a marker-release approach.
3. How will a high complexity mixtures (say 10+ components) compare with a composite cross population from a similar number of parents for either yield benefit or pathogen population effects? (And how can spatial variation benefit such populations – if it can?)
All three questions can be addressed with respect to different pathogen pressures from different farming methods and crop protection options, e.g. conventional vs. organic vs. minimum tillage etc, and fungicides or resistance elicitors (work by enhancing the plants own defence mechanisms).
Proceedings of the 3rd Mathematics in the Plant Sciences study group