Volume 8, Issue 2 ((Autumn & Winter) 2022)
Iranian J. Seed Res. 2022, 8(2): 113-130 |
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Miri M, Amerian M, Edalat M, Baradaran Firouzabadi M, Makarian H. (2022). Quantifying the Germination of Fagopyrum esculentum Moenc. Using Regression and Thermal-Time Models. Iranian J. Seed Res.. 8(2), : 8 doi:10.52547/yujs.8.2.113
URL: http://yujs.yu.ac.ir/jisr/article-1-500-en.html
URL: http://yujs.yu.ac.ir/jisr/article-1-500-en.html
Associate professor of Agronomy, Faculty of Agriculture, Shahroud University of Technology, Shahroud, Iran , Amerianuk@yahoo.co.uk
Abstract: (3034 Views)
Extended Abstract
Introduction: Germination is considered the first and most important stage of establishment and consequently, successful competition which is influenced by genetic and environmental factors. Among the environmental factors influencing the germination, temperature and light are the most important ones. Using different models, the germination response of seeds to temperature can be quantified; therefore, this study was performed to investigate the effect of temperature on germination and to quantify the germination response of Buckwheat seed (Fagopyrum esculentum Moenc) to temperature using nonlinear regression models and thermal-time model.
Materials and methods: The seeds were germinated in 4 replications of 25 seeds under 8 constant temperature treatments (5, 10, 15, 20, 25, 30, 35 and 40 ° C). Using a three-parameter logistic model, Buckwheat seed germination was quantified at different temperature levels and the percentage and time to reach 50% germination were obtained. Four nonlinear regression models and a thermal-time model were used to quantify the response of Buckwheat seed germination rate to temperature. To compare the models and determine the most appropriate model, the root mean square error index (RMSE), coefficient of determination (R2), coefficient of variation (CV) and standard error (SE) were used for the observed germination rate versus the predicted germination rate.
Results: The results indicated that temperature affected the seedling length, normal seedling percentage, seed vigor and the germination rate as well as germination percentage. Also, the results showed that germination characteristics increased with increasing temperature up to 20 and 25 °C. Comparison of the three models based on the root mean square error (RMSE) of germination time, the coefficient of determination (R2), CV and SE, the best model to determine the cardinal temperatures of Fagopyrum esculentum was the dent-like model. The results of thermal-time model showed that the base temperature of Fagopyrum esculentum seeds was 4.01 ° C and the thermal-time coefficient was 1242.6 h° C.
Conclusion: Utilization of non-linear regression models (segmented, dent-like and beta) and thermal-time model to quantify the germination response of Fagopyrum esculentum response to different temperatures led to acceptable results. Therefore, germination rate and percentage may be predicted using the outputs of these models at different temperatures.
Highlights:
Introduction: Germination is considered the first and most important stage of establishment and consequently, successful competition which is influenced by genetic and environmental factors. Among the environmental factors influencing the germination, temperature and light are the most important ones. Using different models, the germination response of seeds to temperature can be quantified; therefore, this study was performed to investigate the effect of temperature on germination and to quantify the germination response of Buckwheat seed (Fagopyrum esculentum Moenc) to temperature using nonlinear regression models and thermal-time model.
Materials and methods: The seeds were germinated in 4 replications of 25 seeds under 8 constant temperature treatments (5, 10, 15, 20, 25, 30, 35 and 40 ° C). Using a three-parameter logistic model, Buckwheat seed germination was quantified at different temperature levels and the percentage and time to reach 50% germination were obtained. Four nonlinear regression models and a thermal-time model were used to quantify the response of Buckwheat seed germination rate to temperature. To compare the models and determine the most appropriate model, the root mean square error index (RMSE), coefficient of determination (R2), coefficient of variation (CV) and standard error (SE) were used for the observed germination rate versus the predicted germination rate.
Results: The results indicated that temperature affected the seedling length, normal seedling percentage, seed vigor and the germination rate as well as germination percentage. Also, the results showed that germination characteristics increased with increasing temperature up to 20 and 25 °C. Comparison of the three models based on the root mean square error (RMSE) of germination time, the coefficient of determination (R2), CV and SE, the best model to determine the cardinal temperatures of Fagopyrum esculentum was the dent-like model. The results of thermal-time model showed that the base temperature of Fagopyrum esculentum seeds was 4.01 ° C and the thermal-time coefficient was 1242.6 h° C.
Conclusion: Utilization of non-linear regression models (segmented, dent-like and beta) and thermal-time model to quantify the germination response of Fagopyrum esculentum response to different temperatures led to acceptable results. Therefore, germination rate and percentage may be predicted using the outputs of these models at different temperatures.
Highlights:
- The best temperature for Fagopyrum esculentum Moenc. seed germination is 20-25 Celsius.
- The dent-like model was determined the most appropriate model for estimating the cardinal temperatures of Buckwheat.
Article number: 8
Type of Study: Research |
Subject:
Seed Physiology
Received: 2020/08/22 | Revised: 2024/02/20 | Accepted: 2021/01/25 | ePublished: 2022/05/21
Received: 2020/08/22 | Revised: 2024/02/20 | Accepted: 2021/01/25 | ePublished: 2022/05/21
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