Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset
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.
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Subjects: | F30 - Génétique et amélioration des plantes, U10 - Informatique, mathématiques et statistiques, modélisation des cultures, intéraction génotype environnement, génotype, facteurs abiotiques, analyse de données, amélioration des plantes, amélioration des cultures, http://aims.fao.org/aos/agrovoc/c_9000024, http://aims.fao.org/aos/agrovoc/c_24577, http://aims.fao.org/aos/agrovoc/c_3225, http://aims.fao.org/aos/agrovoc/c_5b384c25, http://aims.fao.org/aos/agrovoc/c_15962, http://aims.fao.org/aos/agrovoc/c_5956, http://aims.fao.org/aos/agrovoc/c_331560, |
Online Access: | http://agritrop.cirad.fr/597151/ http://agritrop.cirad.fr/597151/1/1-s2.0-S0378429020312673-main.pdf |
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F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 |
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F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 Jones, M.R. Singels, A. Chinorumba, S. Poser, Christophe Christina, Mathias Shine, J. Annandale, J. Hammer, Graeme Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
description |
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. |
format |
article |
topic_facet |
F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 |
author |
Jones, M.R. Singels, A. Chinorumba, S. Poser, Christophe Christina, Mathias Shine, J. Annandale, J. Hammer, Graeme |
author_facet |
Jones, M.R. Singels, A. Chinorumba, S. Poser, Christophe Christina, Mathias Shine, J. Annandale, J. Hammer, Graeme |
author_sort |
Jones, M.R. |
title |
Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
title_short |
Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
title_full |
Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
title_fullStr |
Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
title_full_unstemmed |
Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
title_sort |
evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset |
url |
http://agritrop.cirad.fr/597151/ http://agritrop.cirad.fr/597151/1/1-s2.0-S0378429020312673-main.pdf |
work_keys_str_mv |
AT jonesmr evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT singelsa evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT chinorumbas evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT poserchristophe evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT christinamathias evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT shinej evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT annandalej evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset AT hammergraeme evaluatingprocessbasedsugarcanemodelsforsimulatinggenotypicandenvironmentaleffectsobservedinaninternationaldataset |
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1792500071033470976 |
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dig-cirad-fr-5971512024-01-29T03:12:41Z http://agritrop.cirad.fr/597151/ http://agritrop.cirad.fr/597151/ Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset. Jones M.R., Singels A., Chinorumba S., Poser Christophe, Christina Mathias, Shine J., Annandale J., Hammer Graeme. 2021. Field Crops Research, 260:107983, 17 p.https://doi.org/10.1016/j.fcr.2020.107983 <https://doi.org/10.1016/j.fcr.2020.107983> Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset Jones, M.R. Singels, A. Chinorumba, S. Poser, Christophe Christina, Mathias Shine, J. Annandale, J. Hammer, Graeme eng 2021 Field Crops Research F30 - Génétique et amélioration des plantes U10 - Informatique, mathématiques et statistiques modélisation des cultures intéraction génotype environnement génotype facteurs abiotiques analyse de données amélioration des plantes amélioration des cultures http://aims.fao.org/aos/agrovoc/c_9000024 http://aims.fao.org/aos/agrovoc/c_24577 http://aims.fao.org/aos/agrovoc/c_3225 http://aims.fao.org/aos/agrovoc/c_5b384c25 http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_5956 http://aims.fao.org/aos/agrovoc/c_331560 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/597151/1/1-s2.0-S0378429020312673-main.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.fcr.2020.107983 10.1016/j.fcr.2020.107983 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fcr.2020.107983 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.fcr.2020.107983 |