PhD - Manuscript: The tolerance of wheat (Triticum aestivum L.) to Septoria tritici blotch

Check the manuscript.

2018-12-12

Ph.D degree, The University of Nottingham/AgroParisTech (UK/France), 4 years.

• Advanced applied statistics: protocol design, inferential/predictive modelling, network study(mixed models), machine-learning (Random Forest), 1-week Bayesian training.
• Project management: 1 meta-analysis + 3 experiments during 3 years in 2 countries and interaction with 3 institutes.
• Efficient communication: international conferences, peer-review article, English-written thesis.
• Qualities: strong analytical skills, rigorous and accurate, adaptable, I take the initiative.

Abstract

The Septoria tritici blotch disease (STB, pathogen Zymoseptoria tritici) is the most damaging foliar infection of wheat crops in Europe. Disease management strategies include cultivar resistance, disease escape strategy and fungicides. However, these strategies have failed to provide a complete protection of wheat crops. The STB tolerance is a complementary approach which aims to maintain yield in the presence of the symptoms. The tolerance of STB relies on plant physiology and source/sink balance: the sink demand (the grain growth) must be satisfied in spite of reduced source availability (photosynthetic capacity as affected by the STB symptoms on the leaves). Check out the complete abstract and manuscript.

Extracts

Wheat Growth as Functions

The grain yield and senescence observations were fit against logistic and Gompertz function, respectively; the estimates (lines) and observations (points) can be represented in joint graphic (Manuscript p.147).

Predict Scenescence Timing with Random Forest

The scenescence was predicted by a rather large number of predictors, the model was then use to classify candidate predictors of interest. (Manuscript p.67).

Credits

Image by PublicDomainPictures from Pixabay