Predicting soybean development with a simple photothermal dynamic algorithm

ALVAREZ PRADO S.; ZUIL S.; ACRECHE, MARTÍN M.; MIRALLES D.J.; OTEGUI M.E.; KAVANOVA M.; SCHOLZ DRODOWSKI R.F.; SEVERINI A.D.; VEGA C.; CERETTA S.; SERRAGO R.A.

Rosario, Santa Fe

Congreso; 7° Congreso de la Soja Mercosur-Mercosoja 2019 y A Todo Soja; 2019

Asociación de la Cadena de la Soja Argentina

Predicting the occurrence of the critical period for soybean?s yield determination is important for farmers to decide on variety and sowing date with the objective to expose this period to the best environmental conditions. Simulation models like APSIM (Keating et al., 2003) and DSSAT (Jones et al., 2003) are extremely useful to predict yield under different environments but are difficult to calibrate. We created a simple, dynamic model based on photoperiod and temperature to predict flowering initiation (R1), start of grain filling (R5) and physiological maturity (R7, Fehr and Caviness (1977)) in a wide number of commercial soybean varieties ranging from maturity group (MG) II to VI used by farmers in Argentina, Uruguay, and Paraguay. Our aim was to build a model that is simple enough to be calibrated, yet able to predict soybean phenology with reasonable accuracy. The CRONOSOJA model outputs will be freely available in the near future on an interactive website (http://cronosoja.agro.uba.ar).