phenomics and from crops to landscape
Image of clover rig
[A] Example of original 0.18 mm pixel size image [E] classification associated with image [A]. [B], [C] and [D] are examples of the resampled images used to simulate an increase in capture altitude; with pixel resolutions of 0.36 mm, 0.90 mm and 1.8 mm respectively. [F], [G] and [H] are the classifications produced from the resampled images, whereby [F] is associated to [B], [G] to [C] and [H] to [D]
Approach: To use precision phenotyping at different scales (molecular, organ, trait, yield) under different environments to enable the prediction of genotype x environment.
Potential impact: An understanding of the effect of alleles under different climatic scenarios and how they can lead to unexpected agronomic and quality trade-offs. Develop an understanding of genotype to phenotype and how data from different scales (experimental, spatial, and temporal) can be used to enable predictive modelling of performance to help improve future crop breeding.
Key research insights and findings: Repeated measurements of plant performance and quality, across the life cycle, provide longitudinal trait information which can be used to better understand how different genotypes respond to their environment and agronomic management decisions. Emerging technologies in automated plant handling, robotics, imaging and computer science (deep learning, semantic reasoning, etc), extending through to Remote Sensing and Earth Observation permit non-destructive collection of physical and physiological parameters across scales, from sub cellular through to field and landscape.
Bespoke platforms and/or methodology have been developed for clover and Miscanthus with the CSPG. Instrumented field plots provide extensive and diverse growing environments that are largely uncontrolled but these can be intensively monitored. Crop models are being developed to understand and potentially predict yield in the context of environmental variables with a view to application to agricultural productivity and supply chains.
Evaluation of phenotypic variation in diverse germplasm and mapping populations of cereal, energy and forage crops have been undertaken in the CSPG. The identification of key genetic variants underpins our understanding of plant response to environmental variables, with a view to producing more resilient and higher yielding crops. Traits relevant to UK and global agriculture have been targeted for study so far including flowering time, water use and nutrient responses, thermal tolerance around the time of meiosis in cereals and in root traits of cereal and forage crops.
Nature of insights or findings
1. Phosphate is particularly important for legume forages. Biparental populations display remarkable variation both in their ability to take up phosphate and in their responses to phosphate. Identification of genetic markers for allelic variants conferring phosphate efficiency will inform future plant breeding cycles. [View]
2. Water stress limits crop productivity. Different species have been evaluated for drought and universal drought response indices have been developed for grasses and shown to be species- and location- independent (Duan et al., 2018, dx.doi.org/10.3389/fpls.2018.00492).
3. Plants rarely experience single stresses in isolation. As part of a multinational consortium, we have developed approaches to impose thermal and water stresses at meiosis and quantify the resultant effects on crop productivity, dx.doi.org/10.1186/s13007-017-0229-8.
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