中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > A Method for Upscaling Genetic Parameters of CERES-Rice in Regional Applications 水稻科学(英文版) 2009,16 (4)
Position: Home > Articles > A Method for Upscaling Genetic Parameters of CERES-Rice in Regional Applications Rice Science 2009,16 (4)

A Method for Upscaling Genetic Parameters of CERES-Rice in Regional Applications

作  者：
Jiyoung Min;Zhiqing Ji
单  位：
Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, Chin;College of Crop Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China; Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
关键词：
simulation model;regional application;genetic parameter;upscaling;rice;crop mode
摘  要：
To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data (Method 1). The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety (Method 2), using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology (Method 3), and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels (Method 4). The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error (RMSE) values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.

相似文章

导出引用
计量
文章访问数: 11
HTML全文浏览量: 0
PDF下载量: 0

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46