Evaluation of Linear and Nonlinear Regression Models to Describe Response of Germination to Temperature in Lentil (Lens culinaris Medik. )
Subject Areas : Journal of Crop Ecophysiologyسمانه Rahban 1 , Gh. Rassam 2 , B. Torabi 3 , A. Khoshnood Yazdi 4
1 - M.Sc. Student, Faculty of Agriculture of Shirvan, Ferdowsi University of Mashhad, Mashhad, Iran
2 - Staff member, Faculty of Agriculture of Shirvan, Ferdowsi University of Mashhad, Mashhad, Iran
3 - Staff member, Faculty of Agriculture, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
4 - Staff member, Faculty of Agriculture of Shirvan, Ferdowsi University of Mashhad, Mashhad, Iran
Keywords: simulation, germination, temperature, Lentil,
Abstract :
This study was carried out to determine the requirements of cardinal temperatures and biological hours for germination of lentil by using different linear and nonlinear regression models. To do this, a split plot experiment based on randomized completely design with four replications was conducted in germinator. Experimental treatments were three lentil cultivars (Gacgsaran, Kimia and Bilehsovar) under seven fixed temperature regimes (5, 10, 15, 20, 25, 30 and 35°C). Beta, Dent-like and Segmented models were applied to evaluate the relationship between germination rate and temperature. Root mean square deviation (RMSD), coefficient of determination (R2), coefficients of variation (CV (and linear regression coefficients (a, b) were used to detect the perfect model. Results of fitting the models indicated that the response of lentil germination to temperature is best described by a segmented function. Cardinal temperatures estimated by this model were 0.89 to 1.23°C for base temperature, 23.41 to 26.94°C for optimum temperature and 35.15 to 45°C for ceiling temperature. Significant difference in base temperature among cultivars was not observed, but cultivars had significant difference in optimum and ceiling temperatures. Biological hour's requirement for germination ranged between 25.43 to 31.37 hours. The quantitative information provided by this research can be used in prediction of germination of lentil cultivars.
