Modelling approaches to improve plant resistance deployment (equation-free)
Date
17 July 2018, Tuesday
Time and Venues
| Venues | Local Time | Time Zone |
| Armidale – B55-FG-R00-Small | 12:30 pm | AEST |
| Brisbane St Lucia QBP – Level 3 South telepresence room (3.323) | 12:30 pm | AEST |
| Canberra Black Mountain – Discovery Lecture Theatre; Crace – Bld44- Meeting Room 3 | 12:30 pm | AEST |
| Narrabri Myall Vale – Conference Room | 12:30 pm | AEST |
| Perth Floreat – B1b Boardroom | 10:30 am | AWST |
| Hobart Sandy Bay – River View Room | 12:30 pm | AEST |
| Toowoomba – Meeting Room | 12:30 pm | AEST |
| Waite (SA): B101-FG-R00-BoardWICWest (alternative is SmallWICWest) | 12:00 pm | ACST |
| Werribee (Melbourne) – Peacock Room | 12:30 pm | AEST |
Speaker
Dr Loup Rimbaud, Postdoctoral Fellow – Engineer, Biotic Interactions, CSIRO Agriculture and Food.
Synopsis
Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs very quickly after resistance is deployed in the field, resulting in significant crop losses and a continuing need to breed new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolutionary potential of pathogen populations and thus increase resistance durability. These strategies mainly rely on using different combinations of resistance sources (e.g. qualitative and/or quantitative resistance) in time, space, or both (e.g. via gene pyramiding, crop rotations, cultivar mixtures, field mosaics). However, experimental assessment of their performance presents a major challenge.
In this seminar, I will present these strategies and highlight how simulation models can help optimise the deployment of plant resistance in agricultural landscapes. In particular, we developed a spatiotemporal simulation model to compare different deployment strategies in the context of wheat resistance to rusts, caused by fungi of the genus Puccinia. Our main results show that resistance durability and disease control are not always compatible, and that no deployment strategy is universally optimal.
This talk is intended for a broad audience, thus, unless I am asked to do so, I will not show any mathematical equations!
About the speaker
Loup’s main research interests focus on plant-pathogen interactions and the management of plant disease epidemics, using simulation models complemented with field and glasshouse experiments.
He did his PhD in plant epidemiology and modelling at Montpellier SupAgro (France). In this context, he used both simulation models and laboratory experiments to optimise the surveillance-roguing strategy used to manage sharka disease, a devastating viral disease affecting peach, apricot and plum orchards worldwide.
Then, he joined CSIRO in the beginning of 2016 as a post-doctoral scientist, with the aim to design sustainable deployment strategies of resistant cultivars using epidemiological and evolutionary modelling. The goal is to develop modelling approaches to identify strategies which are both efficient (able to reduce disease impact) and durable (able to limit or prevent pathogen adaptation to the resistance). He specifically applied this approach to two fungal diseases damaging Australian cereal crops: wheat stripe rust (caused by Puccinia striiformis) and canola blackleg (caused by Leptosphaeria maculans).
This is a public seminar.
Open-access to The CSIRO Discovery Theatre @ Black Mountain