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《Research of Agricultural Modernization》 2006-01
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Validation of Digital Maize Planting System in Hebei Province

LI Shi-juan,ZHU Ye-ping,WANG Qi-xian(Institute of Agricultural Information, China Agricultural Academy of Science,Beijing 100081,China)  
Data on maize grown under 0,90,180,270,360 kg N/hm 2 in Hebei province for two continuous seasons were used for testing the digital maize planting system,especially its nitrogen module.The results indi-cated that①phenology prediction were close,with most prediction errorsof 5%;②as concerning the yield and biomass,there were greater deviation in model predictions, yet the relative errors also were reasonable within 10%;③ears per ha predictions were all lower than observations, with most prediction errors of 5%.Grains per ear and grain weight showed higher or lower simulations compared with observations, respectively, and their maximal relative errors were all beyond 10%;④the total N uptake prediction wasn'tgood,but there was a sig-nificant positive correlation relationship between predictions and observations of grain N uptake.This showed that digital maize planting system l can predict phenology,yield and biomass perfectly, and certain parameters within yield component and nitrogen simulation module should be adjusted and revised according to local experiment data.
【Fund】: 国家863计划(玉米系统模型及玉米—小麦周年数字化种植系统2003AA209032);; 北京市自然基金项目(基于小麦玉米生长及其虫害模型的决策支持系统4042026)
【CateGory Index】: S513
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【Citations】
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【Co-citations】
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1 FENG Qing he,ZHANG Jian ping,WANG Xiang dong,MA Hai lian (College of Agronomy, Agricultural University of Hebei, Baoding 071001, China);Progresses and perspectives in crop growth simulation research[J];Journal of Agricultural University of Hebei;2002-S1
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3 CHEN Xue-wen1,2,ZHANG Xing-yi1,SUI Yue-yu1,2 (1.Northeast Institute of Geography and Agricultural Ecology,Chinese Academy of Sciences,Harbin 150081,China;2.Graduate University of Chinese Academy of Sciences,Beijing 100049,China);Modeling the Maize Growth Processes in Black Farmland[J];System Sciences and Comprehensive Studies in Agriculture;2009-02
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