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作物学报 ›› 2013, Vol. 39 ›› Issue (02): 300-308.doi: 10.3724/SP.J.1006.2013.00300

• 耕作栽培·生理生化 • 上一篇    下一篇

基于动态模拟模型分析冬小麦干物质积累特征对产量的影响

赵姣,郑志芳,方艳茹,周顺利,廖树华*,王璞*   

  1. 中国农业大学农学与生物技术学院,北京 100193
  • 收稿日期:2012-06-29 修回日期:2012-10-09 出版日期:2013-02-12 网络出版日期:2012-12-11
  • 通讯作者: 廖树华,E-mail: sergzzl@cau.edu.cn, Tel: 010-62732930; 王璞, E-mail: wangpu@cau.edu.cn, Tel: 010-62733611
  • 基金资助:

    本研究由国家重点基础研究计划(973计划)项目(2009CB118602)和国家公益性行业(农业)科研专项(200903007)资助。

Effect of Dry Matter Accumulation Characteristics on Yield of Winter Wheat Analyzed by Dynamic Simulation Model

ZHAO Jiao,ZHENG Zhi-Fang,FANG Yan-Ru,ZHOU Shun-Li,LIAO Shu-Hua*,WANG Pu*   

  1. College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
  • Received:2012-06-29 Revised:2012-10-09 Published:2013-02-12 Published online:2012-12-11
  • Contact: 廖树华,E-mail: sergzzl@cau.edu.cn, Tel: 010-62732930; 王璞, E-mail: wangpu@cau.edu.cn, Tel: 010-62733611

摘要:

为揭示冬小麦产量形成与干物质积累的定量关系,2009—2011年利用3个田间试验建立了不同播种期、基本苗、底肥用量、追氮时期和用量、冬前灌水量、返青后灌水量和灌水时期等的冬小麦群体,分析了冬小麦干物质积累过程特征对产量及其构成因素的影响机制和定量关系。冬前干物质积累特征用单株干物重和冬前茎蘖数来表示,越冬后特征由基于相对积温(RGDDi)Logistic曲线特征来描述。结果表明,群体干物质积累最大速率、干物质积累速率的2个拐点等特征量与产量及其构成因子有紧密的联系,所建立的关系模型均达到极显著水平(P<0.01)。对有关模型进一步用独立样本进行配对t-检验,结果模拟值与实际值差异不显著(P>0.05)。基于相对积温(RGDDi)Logistic模型不仅能较好地描述小麦冬后干物质积累过程,而且其曲线特征也能用于分析冬小麦产量及其构成因素的形成规律,以此为基础的产量关系方程可用于冬小麦生产群体调控的理论分析。

关键词: 冬小麦, 干物质, Logistic方程, 特征参数

Abstract:

To disclose the quantitative relationship between yield and dry matter accumulation in winter wheat, we designed three field experiments to obtain wheat populations with varying sowing date, basic seedlings, amounts of basic fertilizers, date and quantity of topdressed nitrogen fertilizer, irrigation amounts before wintering, amounts and date of irrigation after regreening of wheat in 2009–2010 and 2010–2011 growing seasons. Dry matter accumulation before wintering was represented by dry weight per plant and total stem and tiller numbers at prewintering stage, while dry matter after wintering was described by the Logistic curve characteristics based on relative accumulated temperature (RGDDi). The grain yield and yield components of winter wheat were closely related to characteristic parameters such as maximum rate of dry matter accumulation and two inflection points in the curve for dry matter accumulation rate. Paired-sample t-test was used to validate the models established, and no significant difference was observed between the simulated and observed values. The results indicate that the Logistic model is able to describe the process of dry matter accumulation and the formation of grain yield and its components in winter wheat. The models established can be used in analysis of population regulation in winter wheat.

Key words: Winter wheat, Dry matter accumulation, Logistic function, Characteristic parameter

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