Predicting crop disease from molecular assessment of the distribution and quantification of soilborne plant pathogens (PhD)


Cereals & Oilseeds
Project code:
01 September 2018 - 30 September 2021
AHDB sector cost:
Total project value:
Project leader:
FERA and the University of Newcastle (Scientific partners: AHDB-BBRO Soil Biology and Soil Health Research Partnership (NIAB, SRUC, ADAS, GWCT, ORC, University of Lincoln, Natural England) Industry partners AHDB-BBRO Soil Biology and Soil Health Research Partnership (LEAF, Innovation for Agriculture, The Wye & Usk Foundation, Frontier, NRM, BASF)

About this project

The challenge

Soil-borne pathogens constrain arable and horticultural production. The distribution and numbers of plant pathogenic fungi and nematodes in soils change in response to the rotation cycle and management practices, such as organic amendment, tillage and liming. A toolbox of validated molecular diagnostic methods, using real-time qPCR analysis, exists for almost all soil-borne fungal and nematode pathogens of crop plants. Confirmation of pathogen presence in the soil, however, does not always mean that disease will develop in the growing crop. 

The project

This PhD studentship compliments a five-year soil biology and soil health research partnership, funded by AHDB and BBRO, designed to help people maintain and improve the productivity of UK agricultural and horticultural systems through a better understanding of soil biology and soil health.

This project will validate molecular tools for monitoring the effects of soil management on soil-borne pathogens, in relation to the risks of crop disease and reduced yield. The hypothesis to be investigated is that molecular detection of soil-borne plant pathogens can be used to predict incidence and severity of key crop diseases.

Work in the first year of the research partnership demonstrated that pathogens can be quantified in field samples from different UK soil types, crop rotations and soil management strategies. The relationship between inoculum distribution and level in soils and the risk of disease development after planting has been established for some pathogens, but not all. This work will broaden the range of pathogens for which the risk of disease can be related to quantitative detection and distribution data obtained from pre-planting analysis of field soils.

Soils with known disease and management histories, from field demonstration plots and experiments already planned at various long-term soil management sites within the research partnership, will be sampled on a grid basis before planting and during three cropping seasons. Composite soil samples, each from up to 16 grid locations per site per crop, will be tested for multiple pathogen targets. DNA extraction methods and qPCR assays will be optimised for different pathogens and validation data on sensitivity and specificity of pathogen detection and quantification will be obtained. Field assessment of disease incidence at various cropping stages during each season will be used to model relationships between pathogen inoculum distribution and level in soils and the risk of disease development.  

The benefits

The work will extend efforts to develop and demonstrate robust DNA-based diagnostics for routine monitoring of soil-borne pathogens and identification of the best management practices to minimise disease risk.