The quality of yield prediction is linked to that of leaf area. We first analysed the consequences of flowering time and environmental conditions on the area of individual leaves in 127 genotypes presenting contrasting flowering times in fields of Europe, Mexico, and Kenya. Flowering time was the strongest determinant of leaf area. Combined with a detailed field experiment, this experiment showed a large effect of flowering time on the final leaf number and on the distribution of leaf growth rate and growth duration along leaf ranks, in terms of both length and width. Equations with a limited number of genetic parameters predicted the beginning, end, and maximum growth rate (length and width) for each leaf rank. The genotype-specific environmental effects were analysed with datasets in phenotyping platforms that assessed the effects (i) of the amount of intercepted light on leaf width, and (ii) of temperature, evaporative demand, and soil water potential on leaf elongation rate. The resulting model was successfully tested for 31 hybrids in 15 European and Mexican fields. It potentially allows prediction of the vertical distribution of leaf area of a large number of genotypes in contrasting field conditions, based on phenomics and on sensor networks.

中文翻译：

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在不同的环境情景下模拟开花时间对玉米单叶面积的影响。

产量预测的质量与叶面积的质量相关。我们首先分析了127种基因型中开花时间和环境条件对单叶面积的影响，这些结果在欧洲，墨西哥和肯尼亚的田间表现出相反的开花时间。开花时间是决定叶面积的最强因素。结合详细的田间试验，该试验显示了开花时间对最终叶数以及叶长和叶宽沿叶等级的生长速率和生长持续时间的分布影响很大。遗传参数数量有限的方程式预测了每个叶等级的开始，结束和最大生长速率（长度和宽度）。在表型分析平台上通过数据集分析了特定基因型的环境影响，该数据集评估了（i）截获的光量对叶片宽度的影响，以及（ii）温度，蒸发需求和土壤水势对叶片伸长率的影响。所生成的模型已成功在15个欧洲和墨西哥领域的31个杂种上进行了测试。根据表型和传感器网络，它有可能允许在对比田间条件下预测大量基因型叶片面积的垂直分布。