Volume 5, Issue 2 ((Autumn & Winter) 2019)                   Iranian J. Seed Res. 2019, 5(2): 1-13 | Back to browse issues page

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Porali F, Ghaderi-Far F, Soltani E, Palevani M H. Comparison of Different Models for Determining Time up to 50% Maximum Germination: A Case Study of Cottonseeds (Gossypium hirsutum). Iranian J. Seed Res.. 2019; 5 (2) :1-13
URL: http://yujs.yu.ac.ir/jisr/article-1-340-en.html
Gorgan University of Agricultural Science and Natural Resources , farshidghaderifar@yahoo.com
Abstract:   (4082 Views)
DOR: 98.1000/2383-1251.1397.5.

Extended abstract
Introduction: Germination speed is one of the most important germination indices, used in most studies to compare the effects of different treatments on seed germination. Researchers use the reverse time up to 50% maximum germination (1/D50) to calculate the germination rate. One of the methods used for calculating the D50 is the utilization of nonlinear regression models such as Logestic, Gompertz, Richard, Weibull and Hill. In addition, for the purpose of calculating this parameter, simple empirical models such as the model presented by Farooq et al. and Ellis and Roberts are used. The question which arises is which of these methods has more precision predicting D50. The purpose of this study was to calculate D50, using 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. Moreover, for the purpose of calculating D50, the models presented by Farooq et al. and Ellis and Roberts were used.
Results: The results showed that all nonlinear regression models exhibited suitable fit to germination data. However, logestic, Hill and Weibull showed better predictability of D50, compared with other models. Besides, D50 calculated by the Farooq model was similar to that estimated by nonlinear regression models, whereas D50 estimated by the Ellis and Roberts model was higher than that estimated by other models.
Conclusions: The results of this study showed that both non-linear regression models and the model developed 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 showed good fit for 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. Moreover, when researchers only seek to measure D50 and are not familiar with the statistical software, they can use the empirical formula presented in this research.
  1. Calculating D50 in cottonseeds, using different methods.
  2. Using nonlinear regression models to calculate D50 in cottonseeds.
  3. Developing a proper method which is more accurate, and better lends itself to calculating D50 of cottonseeds.
Full-Text [PDF 500 kb]   (586 Downloads)    
Type of Study: Research | Subject: General
Received: 2018/04/28 | Accepted: 2018/10/28

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