中国农业气象 ›› 2019, Vol. 40 ›› Issue (06): 357-367.doi: 10.3969/j.issn.1000-6362.2019.06.003

• 论文 • 上一篇    下一篇

基于归一化法模拟分析东北地区春玉米干物质积累对播期和品种的动态响应

张兵兵,吴航,杨璐,吕晓,张放,张慧,高全,杨扬   

  1. 1.中国气象局沈阳大气环境研究所,沈阳 110166;2.锦州市生态与农业气象中心,锦州 121000;3.锦州市气象局,锦州 121000
  • 出版日期:2019-06-20 发布日期:2019-06-11
  • 作者简介:张兵兵(1983-),女,学士,工程师,主要从事应用气象研究。E-mail:810587878@qq.com
  • 基金资助:
    中国气象局沈阳大气环境研究所开放基金(2019SYIAE06);中国气象局沈阳大气环境研究所和辽宁省农业气象灾害重点实验室联合开放基金课题;辽宁省气象局科研项目(201716);国家自然科学基金(41775110)

Simulation of the Dynamic Response of Dry Matter Accumulation of Spring Maize in Northeast China to Sowing Dates and Varieties Based on Normalization Method

ZHANG Bing-bing, WU Hang, YANG Lu, Lv Xiao, ZHANG Fang, ZHANG Hui, GAO Quan, YANG Yang   

  1. 1.The Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166,China;2.Jinzhou City Ecological and Agricultural Meteorological Center, Jinzhou 121000;3.Jinzhou Meteorological Administration, Jinzhou 121000
  • Online:2019-06-20 Published:2019-06-11

摘要: 为探讨东北地区不同播期的主栽品种春玉米的干物质(MDA)积累的生长特性,实现对春玉米干物质积累的有效预估,本研究基于2014-2015年3个春玉米品种(丹玉39、丹玉99和农华101)每年6个播期的试验资料,利用归一化处理方法建立了考虑相对积温(RATi)的干物质重动态模拟模型,并利用推导出的关键生长参数定量分析春玉米干物质积累对播期和品种的动态响应特征。结果表明:基于归一化法筛选并建立了以相对积温为自变量的干物质积累动态模型(Richards模型),方程表达式为y=a/(1+eb?cx)(1/d),决定系数R2在0.99以上,符合生物学意义,对东北地区春玉米有较好的模拟性能。试验验证表明,模型对早播春玉米干物质动态积累的模拟精确度更好,且丹玉39的模拟效果优于丹玉99及农华101。DMA总体表现为随着播期推迟而降低,品种间表现为丹玉39>丹玉99>农华101,差异达极显著水平;干物质积累过程分为积累渐增期、直线快增期和减速积累期3个阶段,其中直线快增期为干物质积累的主要阶段,随着播期的推迟,直线快增期经历的积温、干物质积累量、干物质积累平均速率、速率峰值及其对应的干物质积累量占干物质总量的积累比例都不同程度减小。丹玉39的快增期较丹玉99、农华101明显延长,干物质积累平均速率、速率峰值及其对应的干物质积累量较丹玉99、农华101显著提升。

关键词: 春玉米, 播期, Richards 模型, 干物质积累, 生长特性

Abstract: For effectively estimating the dry matter accumulation (DMA) process of spring maize, based on the experiments of six sowing dates for spring maize of three varieties including ‘Danyu 39’, ‘Danyu 99’ and ‘Nonghua 101’ during 2014?2015, considering relative accumulation temperature (RAT), the dynamic simulation model of DMA i.e. Richards model was built by using normalization method and the dynamic responses of DMA of spring maize in Northeast China to varieties and sowing dates were investigated by taking the calculated key growing parameters into account. The results showed that the Richards model was built based on the relationship between the relative dry matter weight (RDMA) and the RAT and demonstrates a satisfactory simulation performance for spring maize in northeast China. Further analyzing showed that the model had higher simulation accuracy for early sowing date and the model performance for ‘Danyu39’ was better than those for ‘Danyu 99’ and ‘Nonghua’. In addition, the DMA decreased with the sowing date delaying and presented a descending order by ‘Danyu 39’ , ‘Danyu 99’ and ‘Nonghua101’ with significant differences. Besides, the dry matter accumulation process could be divided into three stages including gradual, linearly accelerating and decelerating growth period. More specifically, the linearly accelerating growth period (LAGP) was the major phase of DMA during which accumulated temperature, the mean rate of DMA and its peak value as well as the amount of DMA and its proportion to total DMA were gradually decreasing to different degrees with the sowing time delaying. Whereas, the above-mentioned characters indicated significant differences among varieties. To be specific, the LAGP, the mean rate of DMA and its peak value as well as the amount of DMA for ‘Danyu39’ was longer and larger than those for ‘Danyu 99’ and ‘Nonghua 101’, respectively.

Key words: Spring maize, Sowing date, Richards model, Dry matter accumulation, Growth characteristic