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作物学报 ›› 2016, Vol. 42 ›› Issue (01): 82-92.doi: 10.3724/SP.J.1006.2016.00082

• 耕作栽培·生理生化 • 上一篇    下一篇

光温要素对水稻群体茎蘖增长动态影响的分析及模拟

王萌萌1,2，杨沈斌1,2,* ，江晓东1,2，王应平3，陈德2，黄维2，于庚康4，石春林5   

  1. 1南京信息工程大学气象灾害预报预警与评估协同创新中心 / 江苏省农业气象重点实验室, 江苏南京 210044; 2南京信息工程大学应用气象学院, 江苏南京 210044; 3 CSIRO Marine and Atmospheric Research, PMB # 1, Aspendale, Victoria 3195, Australia; 4江苏省气象局, 江苏南京210008; 5江苏省农业科学院, 江苏南京 21001
  • 收稿日期:2015-03-25 修回日期:2015-09-06 出版日期:2016-01-12 网络出版日期:2015-10-08
  • 通讯作者: 杨沈斌, E-mail: jaasyang@163.com, Tel: 025-58731165
  • 基金资助:

    本研究由国家公益性行业(气象)科研专项(GYHY201306035, GYHY201306036, GYHY201206020), 国家“十二五”科技支撑计划项目(2011BAD32B01)和江苏高校优势学科建设工程项目(PAPD)资助。

Analysis and Simulation of Impact of Light and Temperature on Rice Tillering

WANG Meng-Meng1,2,YANG Shen-Bin1,2,*,JIANG Xiao-Dong1,2,WANG Ying-Ping3,CHEN De2,HUANG Wei2,YU Geng-Kang4,SHI Chun-Lin5   

  1. 1 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2 College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China; 3 CSIRO Marine and Atmospheric Research, PMB # 1, Aspendale, Victoria 3195, Australia; 4 Jiangsu Provincial Meteorological Bureau, Nanjing 210008, China; 5 Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China?
  • Received:2015-03-25 Revised:2015-09-06 Published:2016-01-12 Published online:2015-10-08
  • Contact: 杨沈斌, E-mail: jaasyang@163.com, Tel: 025-58731165
  • Supported by:

    This research was supported by Special Fund for Meteorological-scientific Research in the Public Interest (GYHY201306035, GYHY201306036, GYHY201206020) and Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2011BAD32B01) and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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摘要：

为研究水稻茎蘖增长阶段光温要素对茎蘖动态的影响，并验证现有茎蘖动态模拟模型中的光温影响方程，以籼型两系杂交稻陵两优268和两优培九为试验品种，进行了为期2年每年7个播期的大田试验。首先，采用Richards方程对茎蘖观测数据进行拟合，获取茎蘖增长动态的特征参数。然后，分析特征参数与茎蘖增长期内平均光温要素和气候要素的关系，并在此基础上，以光温组合因子为自变量，分别构建2个品种茎蘖增长速率和分蘖率的光温组合影响方程，将获取的方程替换水稻群体茎蘖动态模拟模型中的光温影响方程。最后，验证和比较替换前后模型的模拟结果及与实测茎蘖动态的误差。结果显示，受光温要素的共同作用，平均茎蘖增长速率和最大茎蘖密度均与光温要素显著正相关，表明光温要素不仅影响茎蘖增长速率，也影响实际最大群体茎蘖密度，这在构建的光温组合影响方程中得到了较好的反映。较现有模型，替换后模型在茎蘖增长动态上的模拟误差总体减小，模拟的茎蘖增长速率和最大茎蘖密度与实际吻合较好，但在部分验证数据上仍存在较大误差。然而，本文提出的验证和改进光温影响方程的方法，对了解光温影响机制和完善群体茎蘖动态模拟模型具有一定的参考价值。

关键词: 经验模型, 作物模型, 生长方程, 气候变化, 分蘖

Abstract:

In order to investigate the effects of light and temperature on rice tillering dynamics in tillering stage and validate the light and temperature effect equation in current dynamic tillering models. We performed two-year field-seeding experiments (2012–2013) using two indica two-line hybrid rice cultivars, Lingliangyou 268 and Liangyoupeijiu. And we collected the observation data in tillering. To fit Richards equation for retrieving characteristic parameters related to the maximum tiller density, average growth rate of tillers, and duration of the growing period. Moreover, we analyzed the relationships between all these characteristic parameters and average data of light, temperature and climatic variables during the growing period for each rice cultivar. Based on the relationships we established co-effect equations for the growth rate of tillers and maximum tiller density as a function of co-effect of light and temperature. The new co-effect functions for each cultivar were substituted for the effect functions of light and temperature in a widely used dynamic tillering model to simulate the dynamic tillering in tillering stage. Finally, validation and comparison were carried out for the models applied observation data in tillers period. The result showed that the light and temperature affected crop growth in tillering period. The growth rate of tillers and the actual maximum tiller density positively correlated with the two meteorological factors significantly. Compared with current dynamic tillering model, the model with the established co-effects of light and temperature functions decreased the error significantly in simulating the growth dynamics of tillers. The simulated rice tillering was well consistent with the observed in both growth rate and maximum tiller density for both rice cultivars. However, the discrepancy could also be found in some seeding periods and validation samples, which may be caused by rice adaptability to different light and temperature environments. In conclusion, the validation and improvement of the light and temperature co-effect functions put forward in this study can be used further for understanding the effects of light and temperature factors on rice tillering and improving dynamic tillering models in the future.

Key words:  Empirical model, Crop model, Growth equation, Climate change, Tillering

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