Using Spectral Signatures of Plant Leaf Biochemistry to Understand and Diagnose Plant Stress

BBSRC iCASE PhD Studentship- Using Spectral Signatures of Plant Leaf Biochemistry to Understand and Diagnose Plant Stress
Dr Oliver Windram, Imperial College London, Department of Life Sciences, Silwood Park Campus

A currently unresolved challenge in plant biology is developing a detailed understanding of the molecular systems governing response and adaption to environmental stress. Significant progress has been made but previous attempts to understand this have been limited with many studies initially driven by preliminary data gathered in controlled lab and greenhouse trials often only observing single stress treatments. More recently it has been realised that different stress types can have synergistic and antagonistic influences on each other. We thus find that many crop protection solutions fail at early stages because of lack of a holistic understanding of complex stresses and their interactions. Remote sensing is emerging as a powerful technology with which to monitor plant health. Spectral imaging techniques can provide detailed measurements of plant leaf biochemistry at the field scale both rapidly and non-invasively. However current solutions only provide generic identification of stress occurrence in plants. This studentship will seek to answer if multispectral imaging can be used to detect, diagnose and differentiate different environmental stresses and stress combinations in field plants. Furthermore the project will use this novel methodology to sample plants of known stress exposure for subsequent RNA-Seq analysis to allow inference of transcriptional response networks governing these stress responses.

Objectives and Methodology: This studentship will use a novel multi-disciplinary approach bridging the fields of crop science, molecular systems biology and computer science to diagnose and map single and combination crop stress occurrence throughout the field and assess the transcriptome of affected plants.

1. The initial objective of the project will establish which spectral signatures correspond to particular stresses in the field. Identified instances of compound stresses on plants will also be studied to investigate the influence of multiple stresses on resulting spectral signatures.
2. This ground-truthing data will allow mapping the influence of multiple stresses in the field using drone based multi-spectral imaging. Machine learning will be used to help classify where stresses overlap and where single stresses predominate in fields.
3. The final objective will be to develop a method for sampling plant tissue with known stress exposure for transcriptome profiling. Multispectral images will be used to identify specific plants or groups of plants in the field with known stress exposure. Plants will be sampled for RNA-seq analysis. The resulting gene expression data will be used in a Systems Biology approach to build co-expression networks of plant responses to these complex stress patterns.

The project will be highly interdisciplinary and will focus on the constellation of stresses that occur in conjunction with Septoria infections in wheat. You will work alongside agronomists at a precision agriculture company (Agrii) to obtain ground-truthing and multispectral image data. Work will also involve machine learning and image analysis performed in conjunction with computer scientists as well as generation and analysis of RNA-seq data. The project is likely to suit a student with a background in Systems Biology.

Requirements and eligibility: You should have experience in computational analysis of complex data and ideally, but not necessarily, experience in working with image analysis tools and/or next generation sequencing data. Backgrounds in agronomy and molecular biology will also be extremely beneficial although not essential.

Applicants should have a BSc degree, or equivalent, at 2:1 level or better and preferably should hold, or expect to obtain by October 2016, a Masters degree.

Eligible candidates are only UK or EU citizens who have been resident in the UK for 3 years prior to October 2016.

The scholarship covers tuition fees and a tax free stipend of £16,296 pa, over a period of 4 years maximum.

Deadline for applications is 5pm on Thursday 30 June 2016 but applications will be considered as they are received so early applications are encouraged. A full CV, a personal statement and full contact details of 2 academic referees should be send to Dr Oliver Windram ([Email Address Removed])