Field Scale Adaptation of the CROPGRO Model for Spring Safflower.

Safflower (Carthamus tinctorius L.) is gaining importance as an oilseed crop since the interest of producing biofuels has increased. Cropping system models can be used to predict the feasibility of safflower production under different environments. In this study, we adapted the CROPGRO model to simulate growth and yield of spring safflower. Species and cultivar parameters for safflower were updated based on literature in the existing CROPGRO-soybean (Glycine max L.) model. The model was parameterized and calibrated based on phenological and agronomic data obtained from field experiments conducted at Clovis, NM, USA, during 2013 and 2014 summers. The crop life cycle (anthesis and harvest maturity date) was accurately predicted by the model with root mean square error (RMSE) of 5.4 days. Leaf area index across all the irrigation treatments and seasons was estimated to 1.51 and was very close to the observed value of 1.31 with RMSE of 0.61. Average plant biomass, head mass, head number and seed number were satisfactorily simulated when compared to observed values. Seed yield, averaged over irrigation treatments and years, was predicted at 1963 kg ha^-1 and was very consistent with observed value of 1902 kg ha^-1 with RMSE of 236 kg ha^-1. Reasonable prediction of phenology, growth and yield by the model adapted for safflower suggested that the CROPGRO-safflower model is promising to simulate safflower production in semi-arid climates. However, further evaluation of the CROPGRO-safflower model under different agroclimatic conditions is needed.