title: Within-season yield prediction with different nitrogen inputs under rain-fed condition using CERES-Wheat model in the northwest of China.
abstract: BACKGROUND
  Yield prediction within season is of great use to improve agricultural risk management and decision making. The objectives of this study were to access the yield forecast performance with increasing nitrogen inputs and to determine when the acceptable predicted yield can be achieved using the CERES-Wheat model.
  
  
  RESULTS
  the calibrated model simulated wheat yield very well under various water and nitrogen conditions. Long-term simulation demonstrated that nitrogen input enlarged the annual variability of wheat yield generally. Within-season yield prediction showed that, regardless of nitrogen inputs, yield forecasts in the later growing season improved the accuracy and reduced the uncertainty of yield prediction. In a low-yielding year (2011-2012) and a high-yielding year (1991-1992), the date of acceptable predicted yield was achieved 62 and 65 days prior to wheat maturity, respectively. In a normal-yielding year (1983-1984), inadequate precipitation after the jointing stage in most historical years led to the underestimation of wheat yield and the date of accurate yield prediction was delayed to 235-250 days after simulation (7-22 days prior to maturity) for different N inputs.
  
  
  CONCLUSIONS
  Yield prediction was highly influenced by the distribution of meteorological elements during the growing season and may show great improvement if future weather can be reliably forecast early. © 2015 Society of Chemical Industry.
authors.affiliation: Institute of Soil and Water Conservation, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, 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.
authors.forename: Zhengpeng
authors.initials: Z
authors.lastname: Li
authors.affiliation: Institute of Soil and Water Conservation, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, 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.
authors.forename: Mingdan
authors.initials: M
authors.lastname: Song
authors.affiliation: Institute of Soil and Water Conservation, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, 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.|Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Shaanxi, 712100, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Feng
authors.affiliation: Institute of Water Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling, Shaanxi, 712100, China.|College of Natural Resources and Environment, Northwest A&F University, Yangling, Shaanxi, 712100, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhao
mesh_terms: D057914:Agricultural Irrigation; D002681:China; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000502:physiology; D008954:Models, Biological; D009584:Nitrogen; D011891:Rain; D012621:Seasons; D014908:Triticum / Q000254:growth & development*
chemical_list: D009584:Nitrogen
keywords: CERES-Wheat model; forecast accuracy; nitrogen; precipitation distribution; yield forecast