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作物学报 ›› 2015, Vol. 41 ›› Issue (01): 123-135.doi: 10.3734/SP.J.1006.2015.00123

• 耕作栽培·生理生化 • 上一篇    下一篇

GECROS模型在黄淮海地区模拟夏玉米生长的适应性评价

吴玮1,2,3,马玉平1,*,俄有浩1,孙琳丽1,2,景元书2   

  1. 中国气象科学研究院, 北京 100081; 2南京信息工程大学, 江苏南京 210044; 3无为县气象局, 安徽无为 238300 
  • 收稿日期:2014-04-30 修回日期:2014-09-30 出版日期:2015-01-12 网络出版日期:2014-11-11
  • 通讯作者: 马玉平, E-mail: mayp@cams.cma.gov.cn
  • 基金资助:

    本研究由国家公益性行业(气象)科研专项(GYHY201006027)和中国气象科学研究院基本科研业务费专项(2009Y005)资助。

Adaptability Evaluation of GECROS Simulateing Summer Maize Growth in the Yellow-Huaihe-Haihe Rivers

WU Wei1,2,3,MA Yu-Ping1,*,E You-Hao1,SUN Lin-Li1,2,JING Yuan-Shu2   

  1. 1 Chinese Academy of Meteorological Sciences, Beijing 100081, China; 2 Nanjing University of Information Science & Technology, Nanjing 210044, China; 3 Wuwei County Bureau of Meteorology, Wuwei 238300, China
  • Received:2014-04-30 Revised:2014-09-30 Published:2015-01-12 Published online:2014-11-11
  • Contact: 马玉平, E-mail: mayp@cams.cma.gov.cn

摘要:

GECROS是荷兰瓦赫宁根农业大学近些年开发的机理性更强、算法更简要的作物生长模型。本文利用黄淮海地区夏玉米试验数据进行GECROS模型的适应性评价, 为模型进一步开展区域应用提供依据。结果表明, GECROS基本能够反映黄淮海地区夏玉米的发育进程。模型模拟夏玉米抽雄期的绝对偏差在6.0 d以内, 平均为2.1 d; 模拟成熟期的绝对偏差在8.0 d以内, 平均为3.4 dGECROS描述夏玉米干物质积累和叶面积扩展过程的准确度较高。模拟雌穗总重的归一化均方根误差在7.8%~33.8%之间, 平均为18.6%; 模拟植株地上总重的归一化均方根误差在11.2%~32.6%之间, 平均为20.7%; 模拟LAI的绝对偏差在0.28~0.55之间, 平均为0.41, 模拟籽粒产量的绝对偏差在20.3~229.0 g m-2之间, 平均为80.9 g m-2。利用GECROS模型相对评价作物生长状况或环境影响基本可行。但GECROS模拟夏玉米发育进程仍存在低值偏高、高值偏低的现象; 在土壤水分胁迫较重时, 描述的生物量积累过程有偏低情况; 描述LAI扩展的总体效果差于生物量累积的效果。GECROS仍需进一步完善。

关键词: GECROS, 适应性, 夏玉米, 黄淮海地区

Abstract:

The evaluation of crop model is a key process for its application. GECROS model had been developed by Wageningen in recent years. GECROS uses stronger mechanism and more concise algorithms to summarize the current knowledge of individual physiological processes and their interactions and feedback mechanisms. To provide a foundation for the future localization and regional application of GECROS model, in this study, the field observations of summer maize from several agrometeorological stations in Yellow-Huaihe-Haihe Rivers were used to conduct the adaptability evaluation of GECROS model. The results showed that GECROS model could basically reflect the growing process of summer maize in Yellow-Huaihe-Haihe Rivers. The absolute deviations at the period from emergence to tasseling simulated by GECROS were less than 6.0 d, with an average of 2.1 d. The absolute deviations at the period from tasseling to mature were less than 8.0 d, with an average of 3.4 d. The dry matter accumulation and leaf area expansion process of summer maize were accurately described by GECROS. The normalized mean square root errors (%) of total ear weight simulated by GECROS were 7.8%–33.8%, with an average of 18.6%, and these of total plant weight were 11.2%–32.6%, with an average of 20.7%. The absolute deviations of LAI were 0.28–0.55, with an average of 0.41. The relative evaluation on crop growth and impact of environmental conditions was basically feasible. But the developmental process of summer maize simulated by GECROS had the phenomenon of low values tengding to higher and high values tengding to lower. When the soil water stress was severe, GECROS gave a lower value for the biomass accumulation process, and the overall effect of description for the LAI expansion was inferior to that for biomass accumulation. GECROS still needs to be further improved.

Key words: GECROS, Adaptability, Summer maize, The Yellow-Huaihe-Haihe Rivers

[1]王石立, 马玉平. 作物生长模拟模型在我国农业气象业务中的应用研究进展及思考. 气象, 2008, 34(6): 3–9



Wang S L, Ma Y P. The progress in application of crop growth simulation models to agro-meteorological services in China. Meteorol Monthly, 2008, 34(6): 3–9 (in Chinese with English abstract)



[2]马玉平, 王石立, 王馥棠. 作物模拟模型在农业气象业务应用中的研究初探. 应用气象学报, 2005, 16: 293–302



Ma Y P, Wang S L, Wang F T. A preliminary study on the application of crop simulation models in agrometeorological services. J Appl Meteorol Sci, 2005, 16: 293–302 (in Chinese with English abstract)



[3]马玉平, 王石立, 李维京. 基于作物生长模型的玉米生殖期冷害致灾因子研究. 作物学报, 2011, 37: 1642–1649



Ma Y P, Wang S L, Li W J. Chilling disaster factors in maize reproductive stage based on crop growth model. Acta Agron Sin, 2011, 37: 1642–1649 (in Chinese with English abstract)



[4]Jing Q, Bouman B A M, Hengsdijk H, van Keulen H, Cao W. Exploring options to combine high yields with high nitrogen use efficiencies in irrigated rice in China. Eur J Agron, 2007, 26: 166–177



[5]罗毅, 郭伟. 作物模型研究与应用中存在的问题. 农业工程学报, 2008, 24(5): 307–311



Luo Y, Guo W. Development and problems of crop models. Trans CSAE, 2008, 24(5): 307–311 (in Chinese with English abstract)



[6]曹宏鑫, 赵锁劳, 葛道阔, 刘永霞, 刘岩, 孙金英, 岳延滨, 张智优, 陈煜利. 作物模型发展探讨. 中国农业科学, 2011, 44: 141–150



Cao H X, Zhao S L, Ge D K, Liu Y X, Liu Y, Sun J Y, Yue Y B, Zhang Z Y, Chen Y L. Discussion on development of crop models. Sci Agric Sin, 2011, 44: 3520–3528 (in Chinese with English abstract)



[7]高峰, 刘爽, 赵光远. 作物模拟研究进展. 热带生物学报, 2010, 1(1): 95–98



Gao F, Liu S, Zhao G Y. Progresses of simulation on crop growth and development. J Trop Organisms, 2010, 1(1): 95–98 (in Chinese with English abstract)



[8]马波, 田军仓.作物生长模拟模型研究综述. 节水灌溉, 2010, (2): 1–4



Ma B, Tian J C. A review on crop growth simulation model research. Water-Saving Irrigation, 2010, (2): 1–4 (in Chinese with English abstract)



[9]陈恩波. 作物生长模拟研究综述. 中国农学通报, 2009, 25(22): 114–117



Chen E B. A review on the research of crop growth simulation. Chin Agric Sci Bull, 2009, 25(22): 114–117 (in Chinese with English abstract)



[10]帅细强, 王石立, 马玉平, 李迎春, 谢佰承. 基于ORYZA2000模型的湘赣双季稻气候生产潜力. 中国农业气象, 2009, 30: 575–581



Shuai X Q, Wang S L, Ma Y P, Li Y C, Xie B C. Studies on potential climate productivity of double rice in Hunan and Jiangxi Provinces based on ORYZA 2000 model. Chin J Agrometeorol, 2009, 30: 575–581 (in Chinese with English abstract)



[11]张雪芬, 余卫东, 王春乙, 白凌霞. WOFOST模型在冬小麦晚霜冻害评估中的应用. 自然灾害学报, 2006, 15: 337–341



Zhang X F, Yu W D, Wang C Y, Bai L X. Application of WOFOST model to assessment of winter wheat’s chilling damage by late frost. J Nat Disasters, 2006, 15: 337–341 (in Chinese with English abstract)



[12]Yin X Y, van Larr H H. Crop Systems Dynamics—an Ecophysiological Simulation Model for Genotype-by-Environment Interactions. Wageningen: Pudoc, 2005. pp 1–45



[13]Gao L Z, Jin Z Q, Huang Y, Zhang L Z. Rice clock model—a computer model to simulate rice development. Agric For Meteorol, 1992, 60: 1–16



[14]王冬妮, 马玉平, 王石立, 郭春明. 东北玉米生长模型中土壤水分参数的敏感性分析. 中国农业气象, 2010, 31: 219–224



Wang D N, Ma Y P, Wang S L, Guo C M. Sensitivity analysis on the soil water parameters in maize growth model in north east China. Chin J Agrometeorol, 2010, 31: 219–224 (in Chinese with English abstract)



[15]Kobayashi K, Salam M U. Comparing simulated and measured values using mean squared deviation and its components. Agron J, 2000, 92: 345–352



[16]Gauch H G Jr, Gene Hwang J T, Fick G W. Model evaluation by comparison of model-based predictions and measured values. Agron J, 2003, 95: 1442–1446



[17]袁刘正, 柳家友. 不同玉米品种农艺性状及产量研究. 中国种业, 2010, (增刊): 38–40



Yuan L Z, Liu J Y. Agronomic traits and yield of different maize varieties. China Seed Industry, 2010, (suppl): 38–40 (in Chinese with English abstract)



[18]刘志斋. 中国玉米地方品种的多样性研究与种族划分. 西南大学博士学位论文, 重庆, 2008. pp 21–74



Liu Z Z. Diversity Analysis and Racial Classification of Maize Landraces in China. PhD Dissertation of Southwest University, Chongqing, Chian, 2008. pp 21–74 (in Chinese with English abstract)



[19]吕贞龙, 徐寿军, 庄恒扬. 作物发育温度非线性效应Beta模型的特征分析. 生态学报, 2008, 28: 3738–3742



Lü Q L, Xu S J, Zhuang H Y. Characteristics of the Beta function for nonlinear effects of temperature on crop phonological development. Acta Ecol Sin, 28: 3738–3742 (in Chinese with English abstract)



[20]郑国清. 浅论对水稻发育期模型的认识. 中国农业气象, 1995, 20(2): 31–34



Zheng G Q. On the simulation models for rice development. Chin J Agrometeorol, 1995, 20(2): 31–34 (in Chinese with English abstract)



[21]马玉平, 王石立, 张黎, 庄立伟. 基于升尺度方法的华北冬小麦区域生长模型初步研究Ⅰ.潜在生产水平. 作物学报, 2005, 31: 697-705



Ma Y P, Wang S L, Zhang L, Zhuang L W. A preliminary study on a regional growth simulation model of winter wheat in North China based on scaling-up approach. Acta Agron Sin, 2005, 31: 697–705 (in Chinese with English abstract)



[22]莫志鸿, 冯利平, 邹海平, 王靖, 黄晚华, 杨晓光. 水稻模型ORYZA2000在湖南双季稻区的验证与适应性评价. 生态学报, 2011, 31: 4628–4637



Mo Z H, Feng L P, Zou H P, Wang J, Huang W H, Yang X G. Validation and adaptability evaluation of rice growth model ORYZA2000 in double cropping rice area of Hunan Province. Acta Ecol Sin, 2011, 31: 4628–4637 (in Chinese with English abstract)



[23]杨沈斌, 申双和, 赵小艳, 赵艳霞, 许吟隆, 王主玉, 刘娟, 张玮玮. 气候变化对长江中下游稻区水稻产量的影响. 作物学报, 2010, 36: 1519–1528



Yang S B, Shen S H, Zhao X Y, Zhao Y X, Xu Y L, Wang Z Y, Liu J, Zhang W W. Impacts of climate changes on rice production in the middle and lower reaches of the Yangtze River. Acta Agron Sin, 2010, 36: 1519–1528 (in Chinese with English abstract)



[24]孙林丽, 景元书, 马玉平, 俄有浩, 邹艳东, 邢开俞, 吴玮. 基于Downhill-Simplex算法的观测数据与作物生长模型同化方法研究. 中国农业气象, 2012, 33: 555–566



Sun L L, Jing Y S, Ma Y P, E Y H, Zou Y D, Xing K Y, Wu W. Assimilation scheme of observation data and crop growth model based on Downhill-Simplex glgorithm. Chin J Agrometeorol, 2012, 33: 555–566 (in Chinese with English abstract)



[25]Van Diepen C A, Wolf J, Van Keulen H, Rappoldt C. WOFOST: a simulation model of crop production. Soil Use Manage, 1989, 5: 16–24



[26]叶宏宝, 孟亚利, 汤亮, 朱艳, 曹卫星. 水稻叶龄与叶面积指数动态的模拟研究. 中国水稻科学, 2008, 22: 625–630



Ye H B, Meng Y L, Tang L, Zhu Y, Cao W X. A simulation study on leaf age and leaf area index in rice. Chin Rice Sci, 2008, 22: 625–630 (in Chinese with English abstract)



[27]王希群, 马履一, 贾忠奎, 徐程扬. 叶面积指数的研究和应用进展. 生态学杂志, 2005, 24: 537–541



Wang X Q, Ma L Y, Jia Z K, Xu C Y. Research and application advances in leaf area index (LAI). Chin J Ecol, 2005, 24: 537–541 (in Chinese with English abstract)

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