Predicting future biomass yield in Miscanthus using the carbohydrate metabolic profile as a biomarker

Maddison, Anne L.; Camargo-Rodriguez, Anyela; Scott, Ian M.; Jones, Charlotte M.; Elias, Dafydd M.O. ORCID: https://orcid.org/0000-0002-2674-9285; Hawkins, Sarah; Massey, Alice; Clifton-Brown, John; McNamara, Niall P. ORCID: https://orcid.org/0000-0002-5143-5819; Donnison, Iain S.; Purdy, Sarah J.. 2017 Predicting future biomass yield in Miscanthus using the carbohydrate metabolic profile as a biomarker. Global Change Biology Bioenergy, 9 (7). 1264-1278. https://doi.org/10.1111/gcbb.12418

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Abstract/Summary

In perennial energy crop breeding programmes, it can take several years before a mature yield is reached when potential new varieties can be scored. Modern plant breeding technologies have focussed on molecular markers, but for many crop species, this technology is unavailable. Therefore, prematurity predictors of harvestable yield would accelerate the release of new varieties. Metabolic biomarkers are routinely used in medicine, but they have been largely overlooked as predictive tools in plant science. We aimed to identify biomarkers of productivity in the bioenergy crop, Miscanthus, that could be used prognostically to predict future yields. This study identified a metabolic profile reflecting productivity in Miscanthus by correlating the summer carbohydrate composition of multiple genotypes with final yield 6 months later. Consistent and strong, significant correlations were observed between carbohydrate metrics and biomass traits at two separate field sites over 2 years. Machine-learning feature selection was used to optimize carbohydrate metrics for support vector regression models, which were able to predict interyear biomass traits with a correlation (R) of >0.67 between predicted and actual values. To identify a causal basis for the relationships between the glycome profile and biomass, a 13C-labelling experiment compared carbohydrate partitioning between high- and low-yielding genotypes. A lower yielding and slower growing genotype partitioned a greater percentage of the 13C pulse into starch compared to a faster growing genotype where a greater percentage was located in the structural biomass. These results supported a link between plant performance and carbon flow through two rival pathways (starch vs. sucrose), with higher yielding plants exhibiting greater partitioning into structural biomass, via sucrose metabolism, rather than starch. Our results demonstrate that the plant metabolome can be used prognostically to anticipate future yields and this is a method that could be used to accelerate selection in perennial energy crop breeding programmes.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/gcbb.12418
UKCEH and CEH Sections/Science Areas:	Shore
ISSN:	1757-1693
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	13C, bioenergy, biomarkers, carbohydrates, cell wall, Miscanthus, soluble sugars, starch
NORA Subject Terms:	Agriculture and Soil Science Biology and Microbiology
Date made live:	25 Apr 2017 09:56 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/516921

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