Optimizing Parameters of CSM-CERES-Maize Model to Improve Simulation Performance of Maize Growth and Nitrogen Uptake in Northeast China

Crop models can be useful tools ibr optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer (DSSAT)-CERES-Maize were optimized using a new method to provide a better simulati...

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Published inJournal of Integrative Agriculture Vol. 11; no. 11; pp. 1898 - 1913
Main Authors LIU, Hai-long, YANG, Jing-yi, HE, Ping, BAI, You-lu, JIN, Ji-yun, Drury, Craig F, ZHU, Ye-ping, YANG, Xue-ming, LI, Wen-juan, XIE, Jia-gui, YANG, Jing-min, Hoogenboom, Gerrit
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.11.2012
Science Press
Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Agri-Information Service Technology,Ministry of Agriculture, Beijing 100081, P.R.China
Greenhouse and Processing Crops Research Centre, Agriculture & Agri-Food Canada, Ontario NOR IGO, Canada
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laborator%Greenhouse and Processing Crops Research Centre, Agriculture & Agri-Food Canada, Ontario NOR IGO, Canada%Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Nutrition and Fertilization, Ministry of Agriculture, Beijing 100081, P.R.China%Agricultural Information Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Agri-Information Service Technology,Ministry of Agriculture, Beijing 100081, P.R.China%Agricultural Environment and Resources Research Center, Jilin Academy of Agricultural Sciences, Changchun 130124, P.R.China%College of Resource & Environment Sciences, Jilin Agricultural University, Changchun 130118, P.R.China%AgWeatherNet, Washington State University, WA 99350-8694, USA
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Summary:Crop models can be useful tools ibr optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer (DSSAT)-CERES-Maize were optimized using a new method to provide a better simulation of maize (Zea mays L.) growth and N upfake in response to different nitrogen application rates. Field data were collected from a 5 yr field experiment (2006-2010) on a Black soil (Typic hapludoll) in Gongzhuling, Jilin Province, Northeast China. After cultivar calibration, the CERES-Maize model was able to simulate aboveground biomass and crop yield of in the evaluation data set (n-RMSE=5.0-14.6%), but the model still over-estimated aboveground N uptake (i.e., with E values from -4.4 to -21.3 kg N ha-~). By analyzing DSSAT equation, N stress coefficient for changes in concentration with growth stage (CTCNP2) is related to N uptake. Further sensitivity analysis of the CTCNP2 showed that the DSSAT model simulated maize nitrogen uptake more precisely after the CTCNP2 coefficient was adjusted to the field site condition. The results indicated that in addition to calibrating 6 coefficients of maize cultivars, radiation use efficiency (RUE), growing degree days for emergence (GDDE), N stress coefficient, CTCNP2, and soil fertility factor (SLPF) also need to be calibrated in order to simulate aboveground biomass, yield and N uptake correctly. Independent validation was conducted using 2008-2010 experiments and the good agreement between the simulated and the measured results indicates that the DSSAT CERES-Maize model could be a useful tool for predicting maize production in Northeast China.
Bibliography:10-1039/S
DSSAT, CERES-Maize model, maize growth simulation, model evaluation, fertilizer N experiment
Crop models can be useful tools ibr optimizing fertilizer management for a targeted crop yield while minimizing nutrient losses. In this paper, the parameters of the decision support system for agrotechnology transfer (DSSAT)-CERES-Maize were optimized using a new method to provide a better simulation of maize (Zea mays L.) growth and N upfake in response to different nitrogen application rates. Field data were collected from a 5 yr field experiment (2006-2010) on a Black soil (Typic hapludoll) in Gongzhuling, Jilin Province, Northeast China. After cultivar calibration, the CERES-Maize model was able to simulate aboveground biomass and crop yield of in the evaluation data set (n-RMSE=5.0-14.6%), but the model still over-estimated aboveground N uptake (i.e., with E values from -4.4 to -21.3 kg N ha-~). By analyzing DSSAT equation, N stress coefficient for changes in concentration with growth stage (CTCNP2) is related to N uptake. Further sensitivity analysis of the CTCNP2 showed that the DSSAT model simulated maize nitrogen uptake more precisely after the CTCNP2 coefficient was adjusted to the field site condition. The results indicated that in addition to calibrating 6 coefficients of maize cultivars, radiation use efficiency (RUE), growing degree days for emergence (GDDE), N stress coefficient, CTCNP2, and soil fertility factor (SLPF) also need to be calibrated in order to simulate aboveground biomass, yield and N uptake correctly. Independent validation was conducted using 2008-2010 experiments and the good agreement between the simulated and the measured results indicates that the DSSAT CERES-Maize model could be a useful tool for predicting maize production in Northeast China.
http://dx.doi.org/
http://www.chinaagrisci.com/Jwk_zgnykxen/fileup/PDF/2012,11(11)-1898.pdf
ISSN:2095-3119
2352-3425
DOI:10.1016/S2095-3119(12)60196-8