Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset

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dc.contributor.author Jones, Matthew R.
dc.contributor.author Singels, Abraham
dc.contributor.author Chinorumba, S.
dc.contributor.author Poser, C.
dc.contributor.author Christina, M.
dc.contributor.author Shine, J.
dc.contributor.author Annandale, John George
dc.contributor.author Hammer, G.L.
dc.date.accessioned 2021-04-13T05:34:55Z
dc.date.issued 2021-01
dc.description.abstract Crop modelling has the potential to assist plant breeding by identifying favourable genotypic (G) traits for specific environments (Es). Sugarcane crop models have not been rigorously evaluated against a factorial GxE dataset. It is imperative that models are evaluated in this way before they are applied to plant breeding problems. Our objectives were to (1) calibrate, (2) assess, and (3) identify weaknesses and recommend improvements to, three sugarcane models, DSSAT-Canegro, Mosicas and APSIM-Sugar, in relation to their predictions of observed E, G and GxE interaction effects in response to abiotic factors (temperature and solar radiation). Data from an international GxE growth analysis trial were used; these consisted of five irrigated experiments at four sites (Belle Glade, Florida, USA; Chiredzi, Zimbabwe; La Mare, Reunion Island; and Pongola, South Africa), with cultivars N41, R570 and CP88-1762. Observed G and E effects on final above-ground dry mass (ADM) yields were explained in terms of seasonal radiation interception (FIPARa) and seasonal average radiation use efficiency (RUEa). Calibration was undertaken where possible by translating phenotypic parameters derived from observations into model input trait parameter values representing genetic traits. E and G effects on FIPARa were generally simulated satisfactorily, while GxE interaction effects were poorly predicted due to inadequate responses to temperature. E, G and GxE effects on RUEa were poorly predicted by all models, although data shortcomings (arising from uncertainty regarding date of primary shoot emergence and impacts of lodging) prevented us from making strong conclusions in this regard. Models accurately predicted G differences in RUEa during mid-season biomass sampling periods where data confidence was greater. Although the models were able to predict final ADM yield per G and per E reasonably well, none of the models predicted GxE interaction effects well. All models also under-estimated the variation in RUEa and ADM. Recommendations for experimental protocols for exploring RUEa are made. Our key recommendations for future work to improve models for sugarcane breeding applications are to explore G-specific thermal time base temperatures for germination and canopy development processes, and to improve linkages between carbon availability and canopy development. en_ZA
dc.description.department Plant Production and Soil Science en_ZA
dc.description.embargo 2021-11-05
dc.description.librarian hj2021 en_ZA
dc.description.sponsorship The International Consortium for Sugarcane Modelling (ICSM) en_ZA
dc.description.uri http://www.elsevier.com/locate/fcr en_ZA
dc.identifier.citation Jones, M.R., Singels, A., Chinorumba, S. et al. 2021, 'Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset', Field Crops Research, vol. 260, art. 107983, pp. 1-17. en_ZA
dc.identifier.issn 0378-4290 (print)
dc.identifier.issn 1872-6852 (online)
dc.identifier.other 10.1016/j.fcr.2020.107983
dc.identifier.uri http://hdl.handle.net/2263/79401
dc.language.iso en en_ZA
dc.publisher Elsevier en_ZA
dc.rights © 2020 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Field Crops Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Field Crops Research, vol. 260, art. 107983, pp. 1-17, 2021. doi : 10.1016/j.fcr.2020.107983. en_ZA
dc.subject Crop modeling en_ZA
dc.subject Genotype en_ZA
dc.subject Environment en_ZA
dc.subject Radiation use efficiency (RUEa) en_ZA
dc.subject Radiation interception en_ZA
dc.subject Biomass en_ZA
dc.subject Thermal time en_ZA
dc.subject Genetic trait en_ZA
dc.subject Sugarcane en_ZA
dc.title Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset en_ZA
dc.type Postprint Article en_ZA


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