Evaluation of a model for predicting Avena fatua and Descurainia sophia seed emergence in winter rapeseed

Avena fatua and Descurainia sophia are two important annual weeds throughout winter rapeseed (Brassica napus L.) production systems in the semiarid region of Iran. Timely and more accurate control of both species may be developed if there is a better understanding of its emergence patterns. Non-linear regression techniques are usually unable to accurately predict field emergence under such environmental conditions. The objectives of this research were to evaluate the emergence patterns of A. fatua and D. sophia and determine if emergence could be predicted using cumulative soil thermal time in degree days (CTT). In the present work, cumulative seedling emergence from a winter rapeseed field during 3 years data set was fitted to cumulative soil CTT using Weibull and Gompertz functions. The Weibull model provided a better fit, based on coefficient of determination (R2sqr), root mean square of error (RMSE) and Akaike index (AICd), compared to the Gompertz model between 2013 and 2016 seasons for both species. Maximum emergence of A. fatua occured 70-119 days after sowing or after equals 329-426 °Cd, while in D. sophia it occurred 119-134 days after sowing rapeseed equals 373-470 °Cd. Both models can aid in the future study of A. fatua and D. sophia emergence and assist growers and agricultural professionals with planning timely and more accurate A. fatua and D. sophia control.Peer reviewe