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.

中文翻译：

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评估基于过程的甘蔗模型，以模拟在国际数据集中观察到的基因型和环境影响

摘要 作物建模有可能通过识别特定环境 (Es) 的有利基因型 (G) 性状来协助植物育种。尚未针对因子 GxE 数据集对甘蔗作物模型进行严格评估。在将模型应用于植物育种问题之前，必须以这种方式评估模型。我们的目标是 (1) 校准，(2) 评估，以及 (3) 识别三个甘蔗模型 DSSAT-Canegro、Mosicas 和 APSIM-Sugar 的弱点并提出改进建议，这些模型与它们对观察到的 E、G 和GxE 相互作用对非生物因素（温度和太阳辐射）的响应。使用了来自国际 GxE 增长分析试验的数据；这些包括在四个地点（美国佛罗里达州贝尔格莱德；津巴布韦奇雷兹；留尼汪岛拉马雷；和南非蓬戈拉），栽培品种为 N41、R570 和 CP88-1762。观察到的 G 和 E 对最终地上干物质 (ADM) 产量的影响用季节性辐射拦截 (FIPARa) 和季节性平均辐射利用效率 (RUEa) 来解释。在可能的情况下，通过将来自观察的表型参数转化为代表遗传性状的模型输入性状参数值来进行校准。E 和 G 对 FIPARa 的影响通常得到令人满意的模拟，而 GxE 相互作用的影响由于对温度的反应不足而难以预测。所有模型都对 E、G 和 GxE 对 RUEa 的影响预测不佳，尽管数据缺陷（由关于初生芽出现日期和倒伏影响的不确定性引起）阻止我们在这方面做出强有力的结论。在数据置信度更高的季节中期生物量采样期间，模型准确预测了 RUEa 中的 G 差异。尽管这些模型能够很好地预测每 G 和每 E 的最终 ADM 产量，但没有一个模型能很好地预测 GxE 相互作用效应。所有模型还低估了 RUEa 和 ADM 的变化。对探索 RUEa 的实验方案提出了建议。我们对未来改进甘蔗育种应用模型的主要建议是探索用于发芽和冠层发育过程的 G 特定热时基温度，并改善碳可用性与冠层发育之间的联系。尽管这些模型能够很好地预测每 G 和每 E 的最终 ADM 产量，但没有一个模型能很好地预测 GxE 相互作用效应。所有模型还低估了 RUEa 和 ADM 的变化。对探索 RUEa 的实验方案提出了建议。我们对未来改进甘蔗育种应用模型的主要建议是探索用于发芽和冠层发育过程的 G 特定热时基温度，并改善碳可用性与冠层发育之间的联系。尽管这些模型能够很好地预测每 G 和每 E 的最终 ADM 产量，但没有一个模型能很好地预测 GxE 相互作用效应。所有模型还低估了 RUEa 和 ADM 的变化。对探索 RUEa 的实验方案提出了建议。我们对未来改进甘蔗育种应用模型的主要建议是探索用于发芽和冠层发育过程的 G 特定热时基温度，并改善碳可用性与冠层发育之间的联系。