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在中国西北部雨养条件下使用CERES-小麦模型进行不同施氮量下的季内产量预测。

Within-season yield prediction with different nitrogen inputs under rain-fed condition using CERES-Wheat model in the northwest of China.

作者信息

Li Zhengpeng, Song Mingdan, Feng Hao, Zhao Ying

机构信息

Institute of Soil and Water Conservation, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi, 712100, China.

Institute of Water Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi, 712100, China.

出版信息

J Sci Food Agric. 2016 Jun;96(8):2906-16. doi: 10.1002/jsfa.7467. Epub 2015 Oct 26.

Abstract

BACKGROUND

Yield prediction within season is of great use to improve agricultural risk management and decision making. The objectives of this study were to access the yield forecast performance with increasing nitrogen inputs and to determine when the acceptable predicted yield can be achieved using the CERES-Wheat model.

RESULTS

the calibrated model simulated wheat yield very well under various water and nitrogen conditions. Long-term simulation demonstrated that nitrogen input enlarged the annual variability of wheat yield generally. Within-season yield prediction showed that, regardless of nitrogen inputs, yield forecasts in the later growing season improved the accuracy and reduced the uncertainty of yield prediction. In a low-yielding year (2011-2012) and a high-yielding year (1991-1992), the date of acceptable predicted yield was achieved 62 and 65 days prior to wheat maturity, respectively. In a normal-yielding year (1983-1984), inadequate precipitation after the jointing stage in most historical years led to the underestimation of wheat yield and the date of accurate yield prediction was delayed to 235-250 days after simulation (7-22 days prior to maturity) for different N inputs.

CONCLUSION

Yield prediction was highly influenced by the distribution of meteorological elements during the growing season and may show great improvement if future weather can be reliably forecast early. © 2015 Society of Chemical Industry.

摘要

背景

季内产量预测对于改善农业风险管理和决策具有重要意义。本研究的目的是评估随着氮素投入增加的产量预测性能,并确定使用CERES - 小麦模型何时能够实现可接受的预测产量。

结果

校准后的模型在各种水分和氮素条件下都能很好地模拟小麦产量。长期模拟表明,氮素投入总体上扩大了小麦产量的年际变异性。季内产量预测显示,无论氮素投入如何,生长季后期的产量预测提高了预测准确性并降低了产量预测的不确定性。在低产年份(2011 - 2012年)和高产年份(1991 - 1992年),分别在小麦成熟前62天和65天达到可接受预测产量的日期。在正常产量年份(1983 - 1984年),大多数历史年份拔节期后降水不足导致小麦产量被低估,对于不同氮素投入,准确产量预测的日期推迟到模拟后235 - 250天(成熟前7 - 22天)。

结论

产量预测受生长季气象要素分布的影响很大,如果能够早期可靠地预测未来天气,产量预测可能会有很大改善。© 2015化学工业协会。

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