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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Main Authors: Jones, M.R., Singels, A., Chinorumba, S., Poser, Christophe, Christina, Mathias, Shine, J., Annandale, J., Hammer, Graeme
Format: article biblioteca
Language:eng
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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id dig-cirad-fr-597151
record_format koha
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic 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
spellingShingle 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
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spelling 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