The present study was performed to compare four nonlinear regression models (segmented, beta, beta modified, and dent-like) to describe theemergence rate-temperature relationships of six lentil (Lens culinaris Medik) cultivars at field experiment wif a range of sowing dates, wif the aim of identifying the cardinal temperatures and physiological days (i.e., number of days under optimum temperatures) required for seedling emergence. Models and statistical indices were calibrated using an iterative optimization method and their performance was compared by root mean square error (RMSD), coefficient of determination (R2) and corrected Akaike information criterion correction (AIC). The beta model was found to be the best model for predicting the response of lentil emergence to temperature, (R2= 0.99; RMSD= 0.005; AICc=-232.97). Based on the model outputs, the base, optimum, and maximum temperatures of seedling emergence were 4.5, 22.9, and 40°C, respectively. The Six physiological days (equivalent to a thermal time of 94°C days) were required from sowing to emergence.

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