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

Abstract

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 (R

An adapted Weibull function for agricultural applications

“…Despite the above advantages, Weibull applications to agricultural processes appear limited to a relatively small number of studies using specialized (and restrictive) equation forms for characterizing crop yield and biomass production (e.g., Karadavut and Tozluca 2005;Karadavut et al 2010), seed germination (e.g., Brown and Mayer 1988;Gardarin et al 2011), and seedling emergence (e.g., Aboutalebian et al 2017;Izquierdo et al 2013;Navarro et al 2013;Gan et al 1996). The objectives of this study were consequently to (i) derive an adapted Weibull function that is applicable to a wide range of agricultural processes; (ii) describe Weibull function characteristics, parameters, and metrics that may be useful in agricultural applications; and (iii) present six illustrative Weibull characterizations of agricultural datasets.…”