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首页> 外文期刊>Field Crops Research >Crop yield response to soil fertility and N, P, K inputs in different environments: testing and improving the QUEFTS model.
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Crop yield response to soil fertility and N, P, K inputs in different environments: testing and improving the QUEFTS model.

机译：作物在不同环境下对土壤肥力和氮，磷，钾输入量的响应：测试和改进QUEFTS模型。

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摘要

Global food production strongly depends on availability of nutrients. Assessment of future global phosphorus (P) fertilizer demand in interaction with nitrogen (N) and potassium (K) fertilizers under different levels of food demand requires a model-based approach. In this paper we tested use of the QUEFTS model (Quantitative Evaluation of Fertility of Tropical Soils) for assessing crop yields in response to N, P and K application in different environments. QUEFTS was initially developed to simulate interactions between N, P and K for tropical soils under maize crop. We performed an extensive model analysis of crop yields in relation to soil and fertilizer nutrients for six field data sets with maize, rice, and wheat crops grown in tropical and temperate regions. The model equations had to be adapted to broaden the model applicability beyond the original boundary conditions of pH, rain-fed cropping systems, optimum harvest index and temperature. Recalibration and modification resulted in a good agreement between model predicted and observed yields. Our results indicate that the adjustments increased the applicability of the model. However, for application in global studies QUEFTS is data demanding and, also, further testing (and probably improvement) is needed, since various processes (e.g. inputs of other nutrients than N, P and K, sub-soil properties and water supply) are ignored in the model, but may differ dramatically across the globe.
机译：全球粮食生产在很大程度上取决于营养素的供应。在不同的粮食需求水平下，评估未来全球磷（P）肥料与氮（N）和钾（K）肥料的相互作用需要一种基于模型的方法。在本文中，我们测试了使用QUEFTS模型（热带土壤肥力的定量评估）来评估在不同环境中施用氮，磷和钾对作物的响应。 QUEFTS最初是为了模拟玉米作物下热带土壤中氮，磷和钾之间的相互作用而开发的。我们针对热带和温带地区种植的玉米，水稻和小麦作物的六个田间数据集，对与土壤和肥料养分相关的作物产量进行了广泛的模型分析。必须对模型方程进行调整，以扩大模型的适用范围，使其超出pH值，雨育作物系统，最佳收获指数和温度的原始边界条件。重新校准和修改使模型的预测产量与观察到的产量之间具有良好的一致性。我们的结果表明，调整增加了模型的适用性。但是，要在全球研究中应用，QUEFTS需要数据，并且还需要进一步测试（可能还有改进），因为需要进行各种过程（例如，输入除N，P和K以外的其他养分，地下土壤性质和供水）。在模型中被忽略，但在全球范围内可能会大不相同。

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