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

Lead Research Organisation: Imperial College London
Department Name: Life Sciences

Abstract

A challenge within plant biology is determining response to combined stress, although there are many studies upon a single stress [Zhu,J.-K. 2002; Iba,K. 2002] there are few on combined. Recently, it has been identified that different stresses within plants can have synergistic or antagonistic influences upon each other [Pandey,Prachi et al. 2015; Ramegowda,Venkategowda and Senthil-Kumar, M 2015]. Therefore, these stresses should be considered in combination.

During this PhD, I will be investigating the response of model plants and crop species too complex stress within lab and field experiments.

Controlled Environment Trials: During the first year of the project Arabidopsis (model organism) and Brachypodium Distachyon (model organism for monocots [Brkljacic,Jelena et al. 2011]) will be grown under controlled environment and greenhouse conditions. These plants will be subjected to different stress and various commercial and novel biostimulant combinations and the spectral signatures of the leaves recorded. The spectra will then be analysed using multivariate analysis techniques to distinguish the regions in the spectra that change upon exposure to the different stresses.

Field Trials: Annually, Agrii (the industrial partner of this project) are planting a field trials using wheat. During the first year the trials will examine the effect of biostimulants on the growth of wheat upon exposure to stress and Septoria infection. The aim of this is to determine if any of the stimulants are able to prevent or reduce the effect of the Septoria or reduce the effects of combinatorial stress on yield. The response of the plants will be measured using hyperspectral techniques. The conditions and stresses considered in later trials will be decided as the project progresses, the second year trial will be used to determine the dosage levels or best application times of the biostimulants that induced the 'best' response from the first year. The third year will be a repeat experiment to determine if the response from the wheat is reliable and specific.

Controlled environment and field trial data will be used to identify signature peaks or troughs that are present upon exposure to certain stresses and stress combinations, using an ensemble regression approach [Feilhauer,Hannes et al. 2015] and machine learning methods. This will be used to help define minimal spectral regions required to distinguish complex stress and will be used to aid in the design of a custom multispectral camera.

As part of the third year field trials will deploy an unmanned aerial vehicle with the customised multispectral camera to collect data on the field trials to determine if this setup can be used as an early warning detection system for stress within the field. It will potentially allow for the identification of where stress responses overlap or a single stress predominates in the field.

Leaf and root samples collected throughout the PhD will be used for RNA-seq to determine the genes being expressed under the individual and combined stresses. We will use a network modelling approach to relate complex environmental stress exposure to in-field molecular responses. Resulting mutual information networks will be used to help identify potentially important transcriptional regulators of complex stress response.

The expected outcomes are: 1) A better understanding of the impact of different biostimulants on yield in complex stress environments. 2) A potential multispectral system to help with forcasting and mapping stress in field. 3) Better understanding of the molecular networks operating in fields in response to complex stress, identified regulators as potential targets for future breeding or crop protection efforts

Full reference list available on request, due to character limitations.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M011178/1 01/10/2015 30/09/2023
1877101 Studentship BB/M011178/1 01/10/2016 30/09/2020 Christopher Adams
 
Description Work is still ongoing and I would prefer to share this after publications or the award has finished
Exploitation Route Work is still ongoing and I would prefer to share this after publications or the award has finished
Sectors Aerospace, Defence and Marine,Agriculture, Food and Drink,Environment,Security and Diplomacy,Other

 
Description field trials 
Organisation Agrii
Country United Kingdom 
Sector Private 
PI Contribution collect and analyse field trial data
Collaborator Contribution run field trial
Impact Will report when published
Start Year 2015