水氮管理影响冬小麦品质的CERES-Wheat模型模拟  

Effect of Irrigation and Nitrogen Fertilizer Managements on Winter Wheat Quality Based on CERES-Wheat Model

作　　者：刘建超 何建强[1,2] 武文杰 李正鹏[2] 马海姣[1,2] 冯浩 LIU Jianchao;HE Jianqiang;WU Wenjie;LI Zhengpeng;MA Haijiao;FENG Hao(Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A ＆ F University, Yangling , Shaanxi 712100, China;Institute of Water-saving Agriculture in Arid Areas of China, Northwest A ＆ F University, Yangling, Shaanxi 712100, China;Water and Soil Conservation Research Institute, Chinese Academy of Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, China)

机构地区：[1]西北农林科技大学旱区农业水土工程教育部重点实验室,陕西杨凌712100 [2]西北农林科技大学中国旱区节水农业研究院,陕西杨凌712100 [3]中国科学院水利部水土保持研究所,陕西杨凌712100

出　　处：《农业机械学报》2018年第7期271-278,共8页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家高技术研究发展计划(863计划)项目(2013AA102904);中央高校基本科研业务费专项资金项目(QN2009087);高等学校学科创新引智计划项目(B12007)

摘　　要：评估CERES-Wheat对不同水氮管理的响应,模拟不同水氮管理对冬小麦品质和产量的影响,筛选优质高产的水氮管理,优化冬小麦农田管理措施。首先利用关中地区2014—2016年2季冬小麦试验数据,对CERES-Wheat进行校准和验证,并评估其模拟籽粒蛋白质浓度和产量的精度。应用CERES-Wheat模拟51 a(1966—2016)历史气象数据下不同水氮管理的冬小麦生长情况,以籽粒蛋白质浓度和产量为主要筛选目标优化水氮管理。结果表明,CERES-Wheat能够较为精确地模拟冬小麦的生长过程,但籽粒和地上部生物量在严重氮胁迫条件下被低估,籽粒蛋白质浓度在低氮胁迫条件下被高估。籽粒蛋白质浓度和产量对不同的水氮处理具有不同的响应,但可以通过调整灌溉定额、灌溉次数、灌溉时期和施氮量之间的耦合作用达到小麦提质增效的目的。越冬期灌溉120 mm,施氮量262.5 kg/hm^2的水氮管理最适合关中地区的气候条件,可以同时实现优质、高产、稳产。Market shortage of high-quality wheat and lack of market competitiveness both exist in wheat production in China. The objective was to evaluate response of CERES-Wheat to different irrigation and nitrogen fertilization managements. Field experiments were conducted in the Guanzhong Plain of Shaanxi Provice during 2014—2016 for two wheat growing seasons. And its relevant outputs were used to estimate grain protein concentration （GPC）. The CERES-Wheat was calibrated and evaluated with the experimental data. CERES-Wheat was run with 51 years （1966—2016） historical weather data to simulate the GPC and yield, and the optimal irrigation and nitrogen fertilization managements were selected. The CERES-Wheat model could accurately simulate winter wheat growth and GPC under different irrigation and nitrogen fertilization managements. While the aboveground and grain biomass were underestimated with severe nitrogen stress, and the relative root mean square error （RRMSE） values between simulated and measured were 10%-30%, which meant that the simulation results were good or medium. And GPC were overestimated with slight nitrogen stress. The RRMSE of GPC was 3.77%, and the simulation results were still excellent. The CERES-Wheat model was able to be used to simulate winter wheat quality and yield. GPC and yield had different responses to irrigation and nitrogen fertilization. But the coupling effects of irrigation depth and nitrogen fertilization, irrigation depth and irrigation frequency, and irrigation depth and irrigation times could improve GPC and yield at the same time. The selected final optimal management, with a basal dressing of 262.5kg/hm^2 and 120mm irrigation depth at wintering stages, showed strong reliability under different climatic conditions in the Guanzhong Plain. The management could simultaneously meet the multiple requirements of high grain quality and yield, and would be more practical.

关 键 词：冬小麦 籽粒蛋白质浓度 产量 CERES-Wheat 水氮管理 

分 类 号：S274.1[农业科学—农业水土工程] S512.11[农业科学—农业工程]