مقایسه مدلهای مختلف جهت تعیین زمان تا 50 درصد حداکثر جوانه زنی: مطالعه موردی روی بذرهای پنبه (Gossypium hirsutum)

Extended abstract Introduction: Germination speed is one of the most important germination indices, which is used in the most studies to compare the effects of different treatments on germination of seeds. Researchers use the reverse time to 50% maximum germination (1/D50) to calculate the germination rate. One of the methods for calculating the D50 is the use of nonlinear regression models such as Logestic, Gompertz, Richard, Weibull and Hill. Also, for calculating this parameter, simple empirical models such as the model presented by Farooq et al and Ellis and Roberts are used. The question now is which of these methods has a precise prediction of  D50. The purpose of this study was to calculate D50 with different methods in seed germination of cotton. Material and Methods: In this experiment, cottonseeds were placed at three temperatures of 15, 25 and 40°C with three replications, and germinated seeds were counted daily several times. To calculate D50, several nonlinear regression models including Gompertze, Logestic, Hill (the four-parameter), Richard and Weibull models were used. Also, for calculating D50, the models presented by Farooq et al and Ellis and Roberts were used. Results: The results showed that all nonlinear regression models had suitable fit to germination data, but logestic, Hill and Weibull had better prediction of D50 than other model. Also, D50 calculated by Farooq model was similar to that estimated by nonlinear regression models, but D50 estimated by Ellis and Roberts model was higher than estimated from other models. Conclusions: Finally, the results of this study showed that both non-linear regression models and the model presented by Farooq could be used to calculate D50 of cottonseed. In general, the results of this study showed that nonlinear regression models could be used to calculate D50. In this research, Logestic, Hill, and Weibull fit well to cumulative seed germination data of cotton seeds versus time at different temperatures. These models have coefficients that have a biological concept that includes maximum germination percentage, time to 50% maximum germination and time to start germination. Also, when the researcher only seeks to measure the D50 and is not familiar with the statistical software, it can use the empirical formula presented in this research.   Highlights: Calculate D50 with different methods in cottonseeds. Use of nonlinear regression models to calculate D50 in cottonseeds. Introducing of a suitable method as a more accurate and better method for calculating D50 of cottonseeds.