Context

Wheat crop growth models from all over the world have been calibrated on the Groot and Verberne (1991) data set, collected between 1982 and 1984 in the Netherlands, in at least 28 published studies to date including various recent ones. However, the recent use of this data set for calibration of potential yield is questionable as actual Dutch winter wheat yields increased by 3.1 Mg ha^-1 over the period 1984 – 2015. A new comprehensive set of winter wheat experiments, suitable for crop model calibration, was conducted in Wageningen during the growing seasons of 2013–2014 and of 2014–2015.

Objective

The present study aimed to quantify the change of winter wheat variety traits between 1984 and 2015 and to examine which of the identified traits explained the increase in wheat yield most.

Methods

PCSE-LINTUL3 was calibrated on the Groot and Verberne data (1991) set. Next, it was evaluated on the 2013–2015 data set. The model was further recalibrated on the 2013–2015 data set. Parameter values of both calibrations were compared. Sensitivity analysis was used to assess to what extent climate change, elevated CO₂, changes in sowing dates, and changes in cultivar traits could explain yield increases.

Results

The estimated reference light use efficiency and the temperature sum from anthesis to maturity were higher in 2013–2015 than in 1982–1984. PCSE-LINTUL3, calibrated on the 1982–1984 data set, underestimated the yield potential of 2013–2015. Sensitivity analyses showed that about half of the simulated winter wheat yield increase between 1984 and 2015 in the Netherlands was explained by elevated CO₂ and climate change. The remaining part was explained by the increased temperature sum from anthesis to maturity and, to a smaller extent, by changes in the reference light use efficiency. Changes in sowing dates, biomass partitioning fractions, thermal requirements for anthesis, and biomass reallocation did not explain the yield increase.

Conclusion

Recalibration of PCSE-LINTUL3 was necessary to reproduce the high wheat yields currently obtained in the Netherlands. About half of the reported winter wheat yield increase was attributed to climate change and elevated CO₂. The remaining part of the increase was attributed to changes in the temperature sum from anthesis to maturity and, to a lesser extent, the reference light use efficiency.

Significance

This study systematically addressed to what extent changes in various cultivar traits, climate change, and elevated CO₂ can explain the winter wheat yield increase observed in the Netherlands between 1984 and 2015.

中文翻译：

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赶上遗传进步：模拟荷兰现代小麦品种的潜在产量

语境

来自世界各地的小麦作物生长模型已根据 Groot 和 Verberne (1991) 数据集进行了校准，该数据集于 1982 年至 1984 年间在荷兰收集，迄今为止至少有 28 项已发表的研究，包括最近的各种研究。然而，最近使用该数据集校准潜在产量是值得怀疑的，因为荷兰冬小麦的实际产量在 1984 年至 2015 年期间增加了 3.1 Mg ha ^-1 。一套新的综合冬小麦实验，适用于作物模型校准，在 2013-2014 年和 2014-2015 年的生长季节期间在瓦赫宁根进行。

客观的

本研究旨在量化 1984 年至 2015 年间冬小麦品种性状的变化，并检验哪些已鉴定的性状最能解释小麦产量的增加。

方法

PCSE-LINTUL3 在Groot 和 Verberne 数据集 (1991)上进行了校准。接下来，它在 2013-2015 数据集上进行了评估。该模型在 2013-2015 数据集上进一步重新校准。比较了两种校准的参数值。敏感性分析用于评估气候变化、CO ₂升高、播种日期变化和栽培品种性状变化在多大程度上可以解释产量增加。

结果

2013-2015 年估计的参考光利用效率和从开花到成熟的温度总和高于 1982-1984 年。PCSE-LINTUL3，根据 1982-1984 数据集校准，低估了 2013-2015 年的产量潜力。敏感性分析表明，模拟的 1984 年至 2015 年荷兰冬小麦产量增加的一半左右是由 CO ₂升高和气候变化引起的。其余部分可以通过从开花到成熟的温度总和增加来解释，并且在较小程度上通过参考光使用效率的变化来解释。播种日期、生物量分配分数、开花期的热需求和生物量重新分配的变化并不能解释产量增加。

结论

PCSE-LINTUL3 的重新校准对于重现荷兰目前获得的高小麦产量是必要的。报告的冬小麦产量增加的大约一半归因于气候变化和二氧化碳_浓度升高。增加的其余部分归因于从开花到成熟的温度总和的变化，并且在较小程度上归因于参考光利用效率。

意义

本研究系统地探讨了1984 年至 2015 年间在荷兰观察到的冬小麦产量增加在何种程度上可以解释各种栽培品种性状、气候变化和升高的 CO _{2的变化。}