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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. Evaluating process-based sugarcane models for simulating genotypic and environmental effects observed in an international dataset. Field Crops Research, 260:107983, 17 p.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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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.

Mots-clés Agrovoc : Modélisation des cultures, Intéraction génotype environnement, Génotype, facteurs abiotiques, Analyse de données, Amélioration des plantes, amélioration des cultures

Mots-clés complémentaires : jeu de données

Mots-clés libres : Crop model, Genotype, Environment, Radiation use efficiency, Radiation interception, Biomass, Thermal time, Genetic trait, Sugarcane

Classification Agris : F30 - Plant genetics and breeding
U10 - Computer science, mathematics and statistics

Champ stratégique Cirad : CTS 7 (2019-) - Hors champs stratégiques

Auteurs et affiliations

  • Jones M.R., SASRI (ZAF) - auteur correspondant
  • Singels A., SASRI (ZAF)
  • Chinorumba S., ZSAES (ZWE)
  • Poser Christophe, CIRAD-PERSYST-UPR AIDA (FRA)
  • Christina Mathias, CIRAD-PERSYST-UPR AIDA (REU) ORCID: 0000-0003-3618-756X
  • Shine J., SIRC (USA)
  • Annandale J., University of Pretoria (ZAF)
  • Hammer Graeme, University of Queensland (AUS)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/597151/)

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