# Daily output can be exported df <- wheatPhenology( sim, stages = c( 5.74, 6), stageNames = c( "head ", 'flow '), # Multiple stages can be calculated df <- wheatPhenology( sim, stages = c( 5.74, 6), stageNames = c( "head ", 'flow '), # Weather can be passed as a weaana object met_data <- weaana ::readWeatherRecords( met)ĭf <- wheatPhenology( sim, stages = 6, stageNames = 'flow ', model = 'APSIM ', # Models V1 or V2 can be used df <- wheatPhenology( sim, stages = 6, stageNames = 'flow ', model = 'V1 ', # Flowering time using parameter in the sim file df <- wheatPhenology( sim, stages = 6, stageNames = 'flow ', model = 'APSIM ', Sim <- system.file( "extdata/example.sim ", package = "APSIMWheatPhenology ") 48, 678-687.Met <- system.file( "extdata/t ", package = "APSIMWheatPhenology ") Simulation-based analysis of effects of Ppd and Vrn loci on flowering in wheat. Kluwer Academic Publ., Dordrecht, the Netherlands, pp. Understanding options for agricultural production. CERES-Wheat: A user oriented wheat yield model.
Photoperiod and vernalization effect on anthesis date in winter-sown spring wheat regions. Ottman, M.J., Anthony Hunt, L., White, J.W., 2013. Cropsim-Wheat: A model describing the growth and development of wheat. Uncertainty in simulating wheat yields under climate change. Characterizing local variability in crop phenology (Ottman et al., 2013)Īsseng, S., Ewert, F., Rosenzweig, C., Jones, J.W., Hatfield, J.L., Ruane, A.C., Boote, K.J., Thorburn, P.J., Rotter, R.P., Cammarano, D., Brisson, N., Basso, B., Martre, P., Aggarwal, P.K., Angulo, C., Bertuzzi, P., Biernath, C., Challinor, A.J., Doltra, J., Gayler, S., Goldberg, R., Grant, R., Heng, L., Hooker, J., Hunt, L.A., Ingwersen, J., Izaurralde, R.C., Kersebaum, K.C., Muller, C., Naresh Kumar, S., Nendel, C., O/’Leary, G., Olesen, J.E., Osborne, T.M., Palosuo, T., Priesack, E., Ripoche, D., Semenov, M.A., Shcherbak, I., Steduto, P., Stockle, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Travasso, M., Waha, K., Wallach, D., White, J.W., Williams, J.R., Wolf, J., 2013.Gene-based modeling (White et al., 2008).AgMIP wheat model intercomparisons (Asseng et al., 2013).Minor modifications were made to phenology routines to avoid unrealistic behavior under certain, extreme conditions.Įxamples of applications of CERES-Wheat include: Meinke (1996) stated that model Farmers typically apply low N to wheat crop in low rainfall simulation is dependent upon climate, soil and plant genetic cropping. Recent development work on CERES-Wheat has largely focused on ensuring that, so far as possible, model parameters of CERES-Wheat and CROPSIM-Wheat (Hunt and Pararajasingham, 1995) are defined in a comparable manner. The with APSIM-wheat module and concluded that the model low value of RMSE depicted that APSIM model simulated explained more than 90 variation in crop biomass. (1998) provides additional information on how growth, development and yield are simulated. The temperature effects includes a response to vernalizing temperatures, which allows distinguishing among the phenology of spring, facultative and winter wheats. Development is potentially affected both by temperature and daylength. Growth is modeled via a radiation use efficiency approach. Bread and durum wheat may be simulated using the CERES-Wheat model, whose origins trace back to modeling efforts of Joe Ritchie and colleagues in the 1970s (Ritchie et al., 1984).