Understanding and simulating blackgrass seed persistence and soil seed bank dynamics
Lead Research Organisation:
Royal Holloway University of London
Department Name: Biological Sciences
Abstract
Background, rational, importance: Weeds are a major threat to modern agriculture and global food security; about 10% (30-70% without herbicides) of crop production is currently lost to weeds (FAO). The effectiveness of herbicide technology is however threatened by the rapid advance of resistant weeds (1,2). The annual cost of weed herbicide resistance in England alone is £0.4 billion in lost gross profit and an annual wheat yield loss of 0.8 million tonnes. Along with tightening herbicide regulations in Europe, it drives a need for more sustainable weed control strategies.
Problem weeds owe their success, at least in part, to the formation of large and persistent soil seed banks. Weed soil seed bank dynamics is determined by seed persistence and the agro-environment's weather, soil, cultivated crop and agronomical practices (3,4). Weed genotype-environment interactions define seasonal emergence patterns with seed bank persistence by three traits: (i) seasonal dormancy cycling, (ii) longevity by unknown dynamic ageing and repair mechanisms, and (iii) defense and decay by microbial activity (3). Blackgrass (Alopecurus myosuroides) is an annual weed solely propagated by seed and considered to be the most destructive weed in European agriculture (1). The proposed project is therefore focused on blackgrass seed longevity as affected by interaction with the soil seed bank and microbial activity (traits ii and iii). This is highly synergistic with a currently running LIDo project on trait (i). By addressing traits (ii) and (iii) in this proposed LIDo project, the student has the potential to improve Syngenta's existing mathematical model for weed emergence prediction.
Aims & objectives: The proposed programme aims to understand the mechanisms underpinning traits (ii) and (iii) for blackgrass persistence in the soil seed bank and to use these to refine weed emergence models.
Objective 1. To characterise longevity and ageing of blackgrass lots. Existing standard seed longevity assays will be refined to provide a blackgrass-specific accelerated ageing assay. This will be used to identify molecular marker genes for ageing/longevity of seed lots.
Objective 2. To investigate the effects of microbial communities both in soil samples and adhering to the seed surface of samples from different locations. This will provide field-related input parameters (soil, temperature, moisture, microbes) for the simulation model.
Objective 3. To test effects of soil properties and microbial activity on blackgrass seed longevity. Results from objectives 1 (lab) and 2 (field) will be collectively analysed using population-based threshold models (4).
Objective 4. To integrate the obtained results into a "simulated model soil seed bank" and connect it to existing "real-field data" in collaboration with Syngenta's weed modelling experts. This interdisciplinary approach will extend the capability to more complex simulation models and thereby develop more effective control strategies for blackgrass
Problem weeds owe their success, at least in part, to the formation of large and persistent soil seed banks. Weed soil seed bank dynamics is determined by seed persistence and the agro-environment's weather, soil, cultivated crop and agronomical practices (3,4). Weed genotype-environment interactions define seasonal emergence patterns with seed bank persistence by three traits: (i) seasonal dormancy cycling, (ii) longevity by unknown dynamic ageing and repair mechanisms, and (iii) defense and decay by microbial activity (3). Blackgrass (Alopecurus myosuroides) is an annual weed solely propagated by seed and considered to be the most destructive weed in European agriculture (1). The proposed project is therefore focused on blackgrass seed longevity as affected by interaction with the soil seed bank and microbial activity (traits ii and iii). This is highly synergistic with a currently running LIDo project on trait (i). By addressing traits (ii) and (iii) in this proposed LIDo project, the student has the potential to improve Syngenta's existing mathematical model for weed emergence prediction.
Aims & objectives: The proposed programme aims to understand the mechanisms underpinning traits (ii) and (iii) for blackgrass persistence in the soil seed bank and to use these to refine weed emergence models.
Objective 1. To characterise longevity and ageing of blackgrass lots. Existing standard seed longevity assays will be refined to provide a blackgrass-specific accelerated ageing assay. This will be used to identify molecular marker genes for ageing/longevity of seed lots.
Objective 2. To investigate the effects of microbial communities both in soil samples and adhering to the seed surface of samples from different locations. This will provide field-related input parameters (soil, temperature, moisture, microbes) for the simulation model.
Objective 3. To test effects of soil properties and microbial activity on blackgrass seed longevity. Results from objectives 1 (lab) and 2 (field) will be collectively analysed using population-based threshold models (4).
Objective 4. To integrate the obtained results into a "simulated model soil seed bank" and connect it to existing "real-field data" in collaboration with Syngenta's weed modelling experts. This interdisciplinary approach will extend the capability to more complex simulation models and thereby develop more effective control strategies for blackgrass
People |
ORCID iD |
| Gerhard Leubner (Primary Supervisor) | |
| Jonathan Binder (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/T008709/1 | 01/10/2020 | 30/09/2028 | |||
| 2725956 | Studentship | BB/T008709/1 | 01/10/2022 | 30/09/2026 | Jonathan Binder |