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Omid Ansari, Farshid Ghaderifar, Farzad Sharif Zadeh, Ali Moradi,
Volume 3, Issue 2 (2-2017)
Volume 3, Issue 2 (2-2017)
Abstract
The present study sought to evaluate the effect of different temperatures on germination and to determine cardinal temperatures (i.e., base, optimum and maximum) of Secale mountanum at temperatures of 3, 5, 10, 15, 20, 25, 30 and 35oC. Three nonlinear regression models (i.e., segmented, dent-like and beta) were used for quantifying the response of germination rate to temperature. The results showed that in addition to germination percentage, the temperature has a significant impact on germination rate. Given the root mean square of errors (RMSE) of germination time, the coefficient of determination (R2), the simple linear regression coefficients a and b, and the relationship between the observed and the predicted germination rates, the best models for determination of cardinal temperatures of Secale mountanum were dent-like and beta models. Base, optimum and maximum temperatures were estimated to be about 2.70 to 3.17, 21.27 to 30.00 and 35.00 to 35.05°C, respectively for the dent-like model. However, given the high value of SE for temperature base and a negative estimate of the base temperature of the beta model, one can report the dent-like model as the right model. Therefore, by using the dent-like model and the estimated parameters, it is possible to use this model for predicting germination.
Seyyed Mahdi Javadzadeh, Parviz Rezvani Moghaddam, Mohammad Banayan-Aval, Javad Asili,
Volume 3, Issue 2 (2-2017)
Volume 3, Issue 2 (2-2017)
Abstract
Roselle is an important medicinal and industrial plant of the family of Malvaceae, and is planted in vast areas of Sistan and Baluchestan. In a laboratory study, the effect of varying temperatures on seed germination of Hibiscus sabdariffa was investigated and minimum, optimum and maximum temperatures for its germination were determined in a completely randomized design with four replications. For this purpose, temperatures 5, 10, 15, 20, 25, 30, 35, 40, 45 and 50°C were considered in each treatment. Cardinal temperatures for germination were determined consistent with three models (i.e., Intersected-lines Model, Five-Parameters Beta Model and Quadratic Polynomial Model). The traits measured were germination percentage, the speed of germination and mean germination time. The temperature effect on all the measured traits was significant. The results of the regression analysis showed that the best model in terms of cardinal point of this plant is the Five-Parameters Beta Model. Given the results of this model, the minimum and the optimal temperatures for the germination of Roselle are 4.04°C, and 29.83° C, respectively.
Seyed Ali Tabatabaei, Omid Ansari,
Volume 5, Issue 2 (3-2019)
Volume 5, Issue 2 (3-2019)
Abstract
Extended abstract
Introduction: Heavy metal pollution is one of the most serious environmental problems. These metals which accumulate in food chain bring about a lot of hazards to both humans and animals. Among heavy metals, lead is considered to be the most dangerous heavy metal in the environment. It contaminates the environment through the lead-acid battery industry, paint and gasoline additives, insecticides, chemical fertilizers, car exhaust pipes and soldering. The objective of this study was to investigate the effect of Pb(NO3)2 on germination characteristics and biochemical changes of two wheat cultivars (Chamran and Kohdasht cultivars).
Materials and Methods: The objective of this research was to evaluate germination and biochemical changes of two wheat cultivars under Pb(NO3)2 stress, using three-parameter sigmoid model. The experimental design adopted was factorial with a completely randomized design, as the base design, with 3 replications. The first factor was 2 wheat cultivars (Kohdasht and Chamran), and the second factor was 6 levels of Pb(NO3)2 (0, 0.25, 0.5, 0.75, 1 and 1.5 mg.L).
Results: The results showed that with increases in levels of Pb(NO3)2 stress, germination percentage, germination rate, normal seedling percentage, seedling length, seedling weight and seed vigor index reduced for both wheat cultivars. The results of fitting three-parameter sigmoidal to characteristics indicated that the highest characteristics and X50 were obtained from the Chamran cultivar. The highest germination percentage (96%), germination rate (23 seeds per day), normal seedling percentage (93.33%), seedling length (13.07 cm), seedling weight (0.07) and seedling vigor index (12.18) were obtained from the Chamran cultivar under non-stress conditions. Pb(NO3)2 stress increased proline and catalase activity but reduced protein, proline and protein for the Chamran cultivar, as compared with the Kohdasht cultivar.
Conclusion: Generally speaking, the results showed that Pb(NO3)2 had a significant effect on germination characteristics and catalase, proline and protein of wheat. Finally, it could be said that in copper-accumulated areas, choosing proper cultivars can slightly mitigate the damages caused by copper. The Chamran cultivar seems to be a better candidate for these conditions.
Highlights:
- Evaluation of the effect of Pb(NO3)2 stress on germination characteristics of wheat.
- Using three-parameter sigmoid model for the evaluation of biochemical changes and germination of wheat under Pb(NO3)2 stress.
Farnaz Porali, Farshid Ghaderi-Far, Elias Soltani, Mohammad Hadi Palevani,
Volume 5, Issue 2 (3-2019)
Volume 5, Issue 2 (3-2019)
Abstract
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.
Highlights:
Hosein Sarani, Ebrahim Izadi, Ali Ghanbari, Ali Rahemi,
Volume 6, Issue 1 (9-2019)
Volume 6, Issue 1 (9-2019)
Abstract
Extended Abstract
Introduction: In recent years, Japanese morning glory has been recognized as a new weed in some soybean cultivation areas in the Province of Golestan. Japanese morning glory, an annual herbaceous plant, belongs to Convolvulaceae family. Germination is the first step in the competitiveness of a weed in an ecological niche. Among the factors influencing seed germination, temperature and light are the most important environmental factors. The relationship between temperature and germination rate is mainly determined by nonlinear regression, and various models such as dent-like, segmented, beta, and second-order major models are used for this purpose. In this study, we examined the aspects of germination biology of this weed under the influence of temperature and light.
Materials and Methods: In order to investigate the effect of temperature and light on germination of Japanese morning glory, two separate experiments were conducted. Treatments included constant temperature at 7 levels (10, 15, 20, 25, 30, 35, 40) in the first experiment and alternating temperature at 6 levels (30/25, 10/15, 30/20, 35/25, 40/30, 45/35) and light conditions (14 hours of brightness 250 μmoles/m-2-sec-1) and darkness in the second experiment based on a completely randomized design with four replications. The number of germinated seeds was taken up to 4 days after stopping germination every day. Percentage and speed of germination and time reaching 50% germination were calculated. Three models of dent-like, segmented lines and beta were used to determine the cardinal temperature between the temperature and germination rate.
Results: The results showed that temperature had a significant effect on percentage, speed and time taken to reach 50% (D50) of germination of Japanese morning glory. The highest percentage of germination (95%) and germination rate (19.80 seeds per day) were observed in the alternating temperature of 20/30 ° C treatment, respectively. The lowest percentage of germination (83.33%) was observed at alternating temperatures 25/35 °C, and the lowest germination rate (15.10 seeds per day) was observed at 10-20 °C. The segmented lines, dent-like and beta were best fit based on the highest R2adj 0.95, 0.96 and 0.95, respectively. Light had no significant effect on germination, so that germination occurred under both light and dark conditions. According to the results, Japanese morning glory is able to germinate at a wide range of constant and alternating temperatures, although germination is faster at warmer temperatures. On the other hand, the lack of light for germination is another advantage that increases germination, competition, and expansion in agronomic environments.
Conclusion: The findings of the present study suggest that the highest percentage of germination and rate of germination were observed in alternating temperatures of 20/30 °C respectively. Among the nonlinear regression models, the dent-like model represented the best model for describing the germination rate against the temperature in Japanese morning glory. It seems that this weed has better germination at warmer temperatures. Probably from mid-spring following warmer weather, and upon the availability of water, this weed is in a good situation to germinate and compete. It was also found that light had no significant effect on the germination of this weed.
Highlights:
- Non-photoblastic seeds
- Superiority of dent-like model for predicting germination of Japanese morning glory
Sepideh Nikoumaram, Naeimeh Bayatian, Omid Ansari,
Volume 6, Issue 2 (3-2020)
Volume 6, Issue 2 (3-2020)
Abstract
Extended abstract
Introduction: Temperature is one of the primary environmental regulators of seed germination. Seed priming technique has been known as a challenge to improving germination and seedling emergence under different environmental stresses. Quantification of germination response to temperature and priming is possible, using non-liner regression models. Therefore, the objective of this study was to evaluate the effect of temperature and priming on germination and determination of cardinal temperatures (base, optimum and maximum) of Brassica napus L.
Material and Methods: Treatments included priming levels (non-priming, priming with water, gibberellin 50 and 100 mg/l) and temperature (5, 10, 15, 20, 30, 35 and 40 °C). Germination percentage and time to 50% maximum seed germination of Brassica napus L. were calculated for different temperatures and priming by fitting 3-parameter logistic functions to cumulative germination data. For the purpose of quantifying the response of germination rate to temperature, use was made of 3 nonlinear regression models (segmented, dent-like and beta). The root mean square of errors (RMSE), coefficient of determination (R2), CV and SE for the relationship between the observed and the predicted germination percentage were used to compare the models and select the superior model from among the methods employed.
Results: The results indicated that temperature and priming were effective in both germination percentage and germination rate. In addition, the results showed that germination percentage and rate increase with increasing temperature to the optimum level and using priming. As for the comparison of the 3 models, according to the root mean square of errors (RMSE) of germination time, the coefficient of determination (R2), CV and SE, the best model for the determination of cardinal temperatures of Brassica napus L. for non-primed seeds was the segmented model. For hydro-priming and hormone-priming with 50 mg/l GA, the best models were segmented and dent-like models and for hormone-priming with 100 mg/l GA, the dent-like model was the best. The results showed that for non-priming, hydropriming with water, gibberellin 50 and 100 mg/l treatments, the segmented model estimated base temperature as 3.54, 2.57, 2.34 and 2.34 °C and dent-model estimated base temperature as 3.34, 2.45, 2.21 and 2.83 °C, respectively. The segmented model estimated optimum temperature as 24.62, 23.23, 23.69 and 24.38 °C. The dent-model estimated lower limit of optimum temperature and upper limit of optimum temperature as 20.01, 19.62, 16.25, 19.87 and 28.81, 27.38, 29.58 and 27.31 °C.
Conclusion: Utilizing non-liner models (segmented, dent-like and beta) for quantification of germination of Brassica napus L. response to different temperatures and priming produced desirable results. Therefore, utilizing the output of these models at different temperatures can be useful in the prediction of germination rate in different treatments.
Highlights:
1-The effect of priming on germination of Brassica napuswas investigated.
2-The temperature range of rapeseed germination of Brassica napus changes with the use of seed priming.
Fatemeh Lkhoshnoodashkarian, Marjan Diyanat, Gorban Noormohammadi,
Volume 7, Issue 1 (9-2020)
Volume 7, Issue 1 (9-2020)
Abstract
Extended abstract
Introduction: London rocket is an important winter annual weed of the mustard family (Brassicaceae), which is propagated by seed. Germination of a seed population in response to water potential reduction is modeled using the concept of hydro time. This model has outputs that are physiologically and ecologically meaningful. One of the presumptions of the Hydro time model is the normal distribution of the base water potential among the seed population.
Materials and methods: In order to quantify the germination characteristics and determine the cardinal temperature of germination of London rocket (Sisymbrium irio L.), an experiment was done in 2018 at Science Research Branch, Islamic Azad University, Tehran, Iran. The seeds were placed at constant temperatures (5, 10, 15, 20, 25, 30, 35, 40 and 45 °C). Germination percentage, germination rate, root length, shoot length, seedling length and seedling fresh weight were evaluated. Intersected-lines, dent-like and quadratic polynomial models were used to determine cardinal temperatures. London rocket seed germination was tested across a range of water potential (0, -0.2, -0.4, -0.6 and -0.8 MPa) at the optimal temperature of 22.80 °C. The hydro time model, based on the normal distributions was fitted to data.
Results: Results showed that seed of London rocket did not germinate at temperatures of 5, 35, 40 and 45° C, and 25° C was the best temperature for seed germination (48%). The longest root length (4.49 mm) was observed at 20°C, which did not have significant differences with temperatures of 15 and 25 °C. The longest shoot length (10.19 mm) was obtained at 25 °C and there were not any significant differences among this temperature and temperatures of 15 and 20 °C. Similar trend with the trait of root length was observed for the trait of seedling length. The best model for estimating the cardinal temperatures in London rocket was intersected-line model with respect to coefficient of determination and mean square error. According to the intersected-lines model in London rocket, the minimum, optimum and maximum temperatures were calculated 5.83, 22.80 and 37.91°C. According to the hydro-time model based on normal distribution, the hydro-time constant and the base-water potential (which is a threshold for germination beginning) of London rocket degree were 284.28 (MPa/h) and -1.18 (MPa) at 22.80 °C, respectively.
Conclusions: Knowledge of germination and emergence of weeds also helps to predict the potential distribution to new habitats. The obtained coefficient of determination (0.94) between observed germination and predicted germination showed that the hydro time model based on normal distribution fitted well to germination percentage of London rocket seed. Due to the low hydrotime coefficient of this weed and the drought problem that most provinces face, it is expected that this weed will become more problematic in most provinces of Iran in the future.
Highlights:
1- The best temperature for germination of London rocket seed is 25 °C.
2- The best model for estimating the cardinal temperatures in London rocket is intersected-line model
3- The hydro-time constant and the base-water potential of London rocket degree based on normal distribution are 284.28 (MPa/h) and -1.18 (MPa) at 22.80 °C, respectively.
Seyyed Hamidreza Ramazani, Fariba Armoon, Mohammad Ali Behdani,
Volume 7, Issue 2 (3-2021)
Volume 7, Issue 2 (3-2021)
Abstract
Extended Abstract
Introduction: Guar (Cyamopsis tetragonoloba L.) is a plant from the legumes family. Guar gum is obtained from endosperm in guar seeds. Guar gum is used in many industries such as pharmaceutical and food industries, paper, mining, oil and drilling, textiles, and explosives industries. Modeling is a method that is widely used in predicting plant growth stages and determining the required thermal units in each growing stage, especially germination.
Considering the important therapeutic and industrial uses of guar and the lack of sufficient information and reports to determine the cardinal temperatures of this plant, this study aimed to investigate the effect of temperature on germination traits and early seedling growth and predict the cardinal temperatures (minimum, optimal and maximum) of germination for this plant.
Materials and Methods: This research was carried out at the Seed Sciences and Technology Laboratory of Agricultural College of Sarayan, the University of Birjand in 2017. Experiments were carried out in a completely randomized design with 8 levels of temperature treatments (5, 10, 15, 20, 25, 30, 35, and 40°C), with 5 replications. Germination percentage, daily germination speed, mean daily germination, plumule length, root length, and seedling length were calculated. Cardinal temperatures of germination were calculated using regression analysis with the aid of the proposed models (logistic, two-way, quadratic, and third-order polynomials) using germination speed. The data were analyzed using SAS software and the comparison means were done by Duncan's test at a probability level of 5%. Sigma Plot software was used to plot the germination rate against temperature graphs (for fitting different models).
Results: The results showed that the effect of different temperature levels on the percentage, speed and mean seed germination was significant (P <0.05). According to the results, the lowest values for percentage, speed, and average germination were obtained at 5, 10, and 40°C, and the highest germination speed was observed at 15 °C and also the highest percentage of germination and average germination was observed at 35°C. The results of the effect of different temperature levels on seedling growth showed that the effect of temperature on the seedling length, stem, and root length was significant (P <0.01), so that the lowest values related to seedling length, plumule, and radicle was found at 5, 10 and 40°C, and the maximum seedling and plumule length were 30°C.
Conclusion: Quantification of the gauge seed germination reaction to different temperature levels was carried out using four dual-functions, logistic, quadratic and triple polynomials. The second-order multitasking regression model, based on the coefficient of explanation (R2) and the amount of deviation, had a suitable and significant fit with the data related to germination rate against the independent temperature variable. Based on the parameters of the model, the optimum temperature was obtained at 26.05°C and the minimum and maximum temperature of guar germination were calculated to be 6.09 and 40°C.
Highlights:
Introduction: Guar (Cyamopsis tetragonoloba L.) is a plant from the legumes family. Guar gum is obtained from endosperm in guar seeds. Guar gum is used in many industries such as pharmaceutical and food industries, paper, mining, oil and drilling, textiles, and explosives industries. Modeling is a method that is widely used in predicting plant growth stages and determining the required thermal units in each growing stage, especially germination.
Considering the important therapeutic and industrial uses of guar and the lack of sufficient information and reports to determine the cardinal temperatures of this plant, this study aimed to investigate the effect of temperature on germination traits and early seedling growth and predict the cardinal temperatures (minimum, optimal and maximum) of germination for this plant.
Materials and Methods: This research was carried out at the Seed Sciences and Technology Laboratory of Agricultural College of Sarayan, the University of Birjand in 2017. Experiments were carried out in a completely randomized design with 8 levels of temperature treatments (5, 10, 15, 20, 25, 30, 35, and 40°C), with 5 replications. Germination percentage, daily germination speed, mean daily germination, plumule length, root length, and seedling length were calculated. Cardinal temperatures of germination were calculated using regression analysis with the aid of the proposed models (logistic, two-way, quadratic, and third-order polynomials) using germination speed. The data were analyzed using SAS software and the comparison means were done by Duncan's test at a probability level of 5%. Sigma Plot software was used to plot the germination rate against temperature graphs (for fitting different models).
Results: The results showed that the effect of different temperature levels on the percentage, speed and mean seed germination was significant (P <0.05). According to the results, the lowest values for percentage, speed, and average germination were obtained at 5, 10, and 40°C, and the highest germination speed was observed at 15 °C and also the highest percentage of germination and average germination was observed at 35°C. The results of the effect of different temperature levels on seedling growth showed that the effect of temperature on the seedling length, stem, and root length was significant (P <0.01), so that the lowest values related to seedling length, plumule, and radicle was found at 5, 10 and 40°C, and the maximum seedling and plumule length were 30°C.
Conclusion: Quantification of the gauge seed germination reaction to different temperature levels was carried out using four dual-functions, logistic, quadratic and triple polynomials. The second-order multitasking regression model, based on the coefficient of explanation (R2) and the amount of deviation, had a suitable and significant fit with the data related to germination rate against the independent temperature variable. Based on the parameters of the model, the optimum temperature was obtained at 26.05°C and the minimum and maximum temperature of guar germination were calculated to be 6.09 and 40°C.
Highlights:
Azam Jamshidizadeh, Masoumeh Farzaneh, Afrasiab Rahnama Ghahfarokhi , Fatemeh Nasernakhaei,
Volume 7, Issue 2 (3-2021)
Volume 7, Issue 2 (3-2021)
Abstract
Extended Abstract
Introduction: It is obvious that all plants adopt mechanisms to control NaCl accumulation because sodium chloride is the most soluble and most abundant salt. Binweed (Convolvulus arvensis L.) is among the ten widespread noxious weeds in the world that it is reproduced by seed, horizontal lateral root, and rhizome. Because of the extensive underground root system of the bindweed with abundant buds and established root reserves, binweed competes more tolerant than crops under salinity and drought stress. More information on morphophysiological traits of binweed under salinity conditions and comparison of salinity tolerance index between germination and seedling can also be contributed to the most effective management. In order to investigate the germination and seedling growth characteristics of binweed two experiments were conducted separately under salinity stress.
Materials and Methods: Germination experiment was done in a completely randomized design with 9 levels of salinity stresses include 0 (control), 5, 10, 15, 20, 25, 30, 35, and 40 dS.m-1, with four replications in the lab. The seedling experiment was performed in a random complete block design consisted of five levels of salinity (tap water, 10, 20, 30, and 40 dS.m-1) with three replications as the pot in a non-shade greenhouse of Agricultural College of Shahid Chamran University of Ahvaz.
Results: The results showed that with raising salinity, percentage germination and vigure index of seed declined, but Radicle/ Plumule ratio rose. After two weeks, in response to salinity a decrease in root and shoot characteristics of the seedling was observed. Salinity stress data were fitted to a three-parameter logistic for seedling stage showed that the salinity levels higher than 7.86 dS.m-1 led to 50 percent reduction in tolerance index. It was found that 19.84 dS.m-1 caused 50% decrease in the tolerance index at germination stage. Sufficient tolerance index –growth stage variation in response to salinity was found which suggests that bindweed tolerance to salinity at germination stage is about 3 times more than that of seedling stage.
Conclusions: Radicle/ plumule ratio at germination stage and root lateral branches at seedling stage increased in concentrations of up to 25 and 20 dS.m-1, respectively. It seems the maintenance of root area and branches in response to increased salinity provide an acceptable mechanism of salinity tolerance for binweed. According to the three-parameter logistic model, the salinity tolerance of bindweed at germination and seedling stages was estimated at 20 and 8 dS.m-1, respectively.
Keywords: Logistic model, Root lateral branches, Relative water content, Salinity tolerance index
Highlights:
1 Salinity tolerance of bindweed was investigated in germination and seedling growth.
2- Salinity tolerance index was compared between germination and seedling of bindweed and was introduced a proper trait which is more effective to pointing salinity tolerance.
3- The best sigmoidal model based on salinity criterion was introduced for salt tolerance index of bindweed.
Introduction: It is obvious that all plants adopt mechanisms to control NaCl accumulation because sodium chloride is the most soluble and most abundant salt. Binweed (Convolvulus arvensis L.) is among the ten widespread noxious weeds in the world that it is reproduced by seed, horizontal lateral root, and rhizome. Because of the extensive underground root system of the bindweed with abundant buds and established root reserves, binweed competes more tolerant than crops under salinity and drought stress. More information on morphophysiological traits of binweed under salinity conditions and comparison of salinity tolerance index between germination and seedling can also be contributed to the most effective management. In order to investigate the germination and seedling growth characteristics of binweed two experiments were conducted separately under salinity stress.
Materials and Methods: Germination experiment was done in a completely randomized design with 9 levels of salinity stresses include 0 (control), 5, 10, 15, 20, 25, 30, 35, and 40 dS.m-1, with four replications in the lab. The seedling experiment was performed in a random complete block design consisted of five levels of salinity (tap water, 10, 20, 30, and 40 dS.m-1) with three replications as the pot in a non-shade greenhouse of Agricultural College of Shahid Chamran University of Ahvaz.
Results: The results showed that with raising salinity, percentage germination and vigure index of seed declined, but Radicle/ Plumule ratio rose. After two weeks, in response to salinity a decrease in root and shoot characteristics of the seedling was observed. Salinity stress data were fitted to a three-parameter logistic for seedling stage showed that the salinity levels higher than 7.86 dS.m-1 led to 50 percent reduction in tolerance index. It was found that 19.84 dS.m-1 caused 50% decrease in the tolerance index at germination stage. Sufficient tolerance index –growth stage variation in response to salinity was found which suggests that bindweed tolerance to salinity at germination stage is about 3 times more than that of seedling stage.
Conclusions: Radicle/ plumule ratio at germination stage and root lateral branches at seedling stage increased in concentrations of up to 25 and 20 dS.m-1, respectively. It seems the maintenance of root area and branches in response to increased salinity provide an acceptable mechanism of salinity tolerance for binweed. According to the three-parameter logistic model, the salinity tolerance of bindweed at germination and seedling stages was estimated at 20 and 8 dS.m-1, respectively.
Keywords: Logistic model, Root lateral branches, Relative water content, Salinity tolerance index
Highlights:
1 Salinity tolerance of bindweed was investigated in germination and seedling growth.
2- Salinity tolerance index was compared between germination and seedling of bindweed and was introduced a proper trait which is more effective to pointing salinity tolerance.
3- The best sigmoidal model based on salinity criterion was introduced for salt tolerance index of bindweed.
Sajad Mijani, Mehdi Rastgoo, Ali Ghanbari, Mehdi Nassiri Mahallati,
Volume 7, Issue 2 (3-2021)
Volume 7, Issue 2 (3-2021)
Abstract
Extended Abstract
Introduction: Tubers are considered as the most important vegetative organs in reproduction of purple nutsedge, as one of the most troublesome weeds worldwide. Therefore, it is great of importance to investigate the properties of the tuber response to the surrounding environment such as absorption and loss of water. Water uptake is the first step in the sprouting process, though the pattern of water uptake by purple nutsedge tubers has not been documented. Loss of water in tubers is one of the potent factors in reducing their ability to sprouting. Three separate experiments were carried out to investigate the absorption and loss of water content of purple nutsedge tubers.
Material and Methods: In the first experiment, the tubers were placed in a water bath at temperatures of 10, 20, 30, and 40 ° C. Then, the weight of the tubers was measured at different times (24 till 3600 minutes). The water uptake percentage of tubers at different temperatures was studied by fitting the Peleg model. In the second experiment, the initiation day of sprouting was investigated at constant temperatures of 10, 20, 30, and 40 ° C. In the third experiment, water loss and sprouting percentage of tubers were evaluated in two conditions refrigerator (4° C) and room (22 to 25 ° C).
Results: The results showed that the initial water content of tubers was 42% and absorbed 10% extra water after being immersed in water. The water uptake behavior was based on the Peleg model at two stages: (1) rapid uptake (less than 420 minutes (7 hours), and (2) a low uptake with a gentle slope afterward. In the Peleg model, the parameters K1 (minutes *.%weight -1) and K2 (%-1) are water absorption rate and water absorption capacity, respectively. The K1 parameter was negatively against temperature. The highest and lowest values were 49.56 and 28.55 at 10 and 40 ° C, respectively. On the other hand, the trend of the K2 was constant (0.1) at 10-30 °C but was 0.08 at 40 °C. The two-parameter Hyperbola model was superior to the Peleg and predicts the highest water absorption and time to 50 percent water absorption parameters. The results showed that sprouting of purple nutsedge tubers at 10, 20, 30, and 40 °C occurred after 14.44, 6.57, 3.24, and 3.12 days, respectively. Keeping the tubers in the room (22-25 °C) and refrigerator (4 °C), sprouting stopped after 3 and 9 months, respectively. The time required for 50% reduction of sprouting in the room and refrigerator was estimated to be 1.3 months (39 days) and 5.12 months (154 days), respectively. The time required for 50% loss weight of tubers in the room and refrigerator was 1.981 months (59 days) and about 6 months (180 days), respectively. Overall, weight loss (water loss) up 11.85%, resulted in 50% reduction in tuber sprouting.
Conclusion: Maximum water uptake in tubers occurred in less than 420 minutes (seven hours) at all temperatures. Slow sprouting in tubers at low temperatures is not associated with an obstacle in water absorption. Tubers lost half of their sprouting ability by losing water about 12%. On the other hand, the results show that the tubers at cool temperatures (4 °C) lose their water and sprouting capacity less than the ambient temperature (22 to 25 °C).
Highlights:
1- Determination of water absorption pattern on purple nutsedge tubers.
2- Effect of storage location in reducing water and sprouting ability of purple nutsedge tubers.
Introduction: Tubers are considered as the most important vegetative organs in reproduction of purple nutsedge, as one of the most troublesome weeds worldwide. Therefore, it is great of importance to investigate the properties of the tuber response to the surrounding environment such as absorption and loss of water. Water uptake is the first step in the sprouting process, though the pattern of water uptake by purple nutsedge tubers has not been documented. Loss of water in tubers is one of the potent factors in reducing their ability to sprouting. Three separate experiments were carried out to investigate the absorption and loss of water content of purple nutsedge tubers.
Material and Methods: In the first experiment, the tubers were placed in a water bath at temperatures of 10, 20, 30, and 40 ° C. Then, the weight of the tubers was measured at different times (24 till 3600 minutes). The water uptake percentage of tubers at different temperatures was studied by fitting the Peleg model. In the second experiment, the initiation day of sprouting was investigated at constant temperatures of 10, 20, 30, and 40 ° C. In the third experiment, water loss and sprouting percentage of tubers were evaluated in two conditions refrigerator (4° C) and room (22 to 25 ° C).
Results: The results showed that the initial water content of tubers was 42% and absorbed 10% extra water after being immersed in water. The water uptake behavior was based on the Peleg model at two stages: (1) rapid uptake (less than 420 minutes (7 hours), and (2) a low uptake with a gentle slope afterward. In the Peleg model, the parameters K1 (minutes *.%weight -1) and K2 (%-1) are water absorption rate and water absorption capacity, respectively. The K1 parameter was negatively against temperature. The highest and lowest values were 49.56 and 28.55 at 10 and 40 ° C, respectively. On the other hand, the trend of the K2 was constant (0.1) at 10-30 °C but was 0.08 at 40 °C. The two-parameter Hyperbola model was superior to the Peleg and predicts the highest water absorption and time to 50 percent water absorption parameters. The results showed that sprouting of purple nutsedge tubers at 10, 20, 30, and 40 °C occurred after 14.44, 6.57, 3.24, and 3.12 days, respectively. Keeping the tubers in the room (22-25 °C) and refrigerator (4 °C), sprouting stopped after 3 and 9 months, respectively. The time required for 50% reduction of sprouting in the room and refrigerator was estimated to be 1.3 months (39 days) and 5.12 months (154 days), respectively. The time required for 50% loss weight of tubers in the room and refrigerator was 1.981 months (59 days) and about 6 months (180 days), respectively. Overall, weight loss (water loss) up 11.85%, resulted in 50% reduction in tuber sprouting.
Conclusion: Maximum water uptake in tubers occurred in less than 420 minutes (seven hours) at all temperatures. Slow sprouting in tubers at low temperatures is not associated with an obstacle in water absorption. Tubers lost half of their sprouting ability by losing water about 12%. On the other hand, the results show that the tubers at cool temperatures (4 °C) lose their water and sprouting capacity less than the ambient temperature (22 to 25 °C).
Highlights:
1- Determination of water absorption pattern on purple nutsedge tubers.
2- Effect of storage location in reducing water and sprouting ability of purple nutsedge tubers.
Amin Haghighi, Yazdan Izady, Miad Haji Mahmoudi, Seyed Amir Moosavi,
Volume 7, Issue 2 (3-2021)
Volume 7, Issue 2 (3-2021)
Abstract
Extended Abstract
Introduction: Seed germination and seedling emergence depend on the genetics of plant species and are also influenced by environmental factors. Genetics and nutritional status of the maternal plant, maturity stage at a time of harvest, and environmental factors such as temperature, salinity, drought, and soil fertility influence seed germination. Seed vigor as the main parameter of seed quality decreases due to accelerated aging and storage. The objective of this study was to evaluate the response of accelerated aged Chia seed to different levels of salinity stress.
Material and Methods: Two-way factorial experiment with experimental factors, including five levels of seed accelerated aging durations (0, 24, 48, 72, 96 h) and six levels of salinity stress (0, 50, 100, 150, 200, and 250 mM) was arranged based on a complete randomized block design with three replications. The experiment was conducted at seed technology laboratory Khuzestan Agricultural Sciences and Natural Resources, University of Khuzestan, in 2019.
Results: Results of analysis of variance revealed that the effect of seed accelerating aging, salinity stress, and interaction effects of both factors on all measured germination traits were significant (p<0.01). The best pattern of seed germination was evaluated using three-parameter sigmoid models (logistic, Gompertz, and sigmoidal) and two polynomial models (quadratic and cubic), then the performance of all models was compared using (R2adj), root square of the mean (RMSE) and corrected Akaike index (AICc). Results showed that at accelerated aging duration, models' performance to describe Chia seed germination response varied at different levels of salinity stress. At no aging and 72h of accelerated aging treatments, the sigmoidal model exhibited the best fit on final seed germination, whereas for the other levels of accelerated aging, Gompertz exhibited the best fit. Based on the output of the sigmoidal model, for no aging and 72 hours of accelerated aging, 50% of seed germination was declined at 171.7 and 76.9 mM, respectively, and based on the results of the Gompertz model, after 24 and 48 h of accelerated aging, seed germination declined to 50% at 163.8 and 129.6 mM. Results obtained from fitting polynomial models on seed germination showed that the cubic model provides reasonable descriptions for studied traits such as seed vigor.
Conclusion: Chia seed germination was sensitive to salinity and accelerated aging treatments. At no aging condition, Chia seeds tolerate salinity stress up to 200 mM and were able to germinate. By increasing aging durations, seed germination declined dramatically at all salinity levels and after 96 hours of aging, there was no seed germination at 150 mM.
Highlights:
1- The best nonlinear model to study accelerated Chia seed response to salinity stress was selected using the model selection criterion.
2- Chia seed germination threshold to salinity stress was determined for not- aged and aged seeds.
Introduction: Seed germination and seedling emergence depend on the genetics of plant species and are also influenced by environmental factors. Genetics and nutritional status of the maternal plant, maturity stage at a time of harvest, and environmental factors such as temperature, salinity, drought, and soil fertility influence seed germination. Seed vigor as the main parameter of seed quality decreases due to accelerated aging and storage. The objective of this study was to evaluate the response of accelerated aged Chia seed to different levels of salinity stress.
Material and Methods: Two-way factorial experiment with experimental factors, including five levels of seed accelerated aging durations (0, 24, 48, 72, 96 h) and six levels of salinity stress (0, 50, 100, 150, 200, and 250 mM) was arranged based on a complete randomized block design with three replications. The experiment was conducted at seed technology laboratory Khuzestan Agricultural Sciences and Natural Resources, University of Khuzestan, in 2019.
Results: Results of analysis of variance revealed that the effect of seed accelerating aging, salinity stress, and interaction effects of both factors on all measured germination traits were significant (p<0.01). The best pattern of seed germination was evaluated using three-parameter sigmoid models (logistic, Gompertz, and sigmoidal) and two polynomial models (quadratic and cubic), then the performance of all models was compared using (R2adj), root square of the mean (RMSE) and corrected Akaike index (AICc). Results showed that at accelerated aging duration, models' performance to describe Chia seed germination response varied at different levels of salinity stress. At no aging and 72h of accelerated aging treatments, the sigmoidal model exhibited the best fit on final seed germination, whereas for the other levels of accelerated aging, Gompertz exhibited the best fit. Based on the output of the sigmoidal model, for no aging and 72 hours of accelerated aging, 50% of seed germination was declined at 171.7 and 76.9 mM, respectively, and based on the results of the Gompertz model, after 24 and 48 h of accelerated aging, seed germination declined to 50% at 163.8 and 129.6 mM. Results obtained from fitting polynomial models on seed germination showed that the cubic model provides reasonable descriptions for studied traits such as seed vigor.
Conclusion: Chia seed germination was sensitive to salinity and accelerated aging treatments. At no aging condition, Chia seeds tolerate salinity stress up to 200 mM and were able to germinate. By increasing aging durations, seed germination declined dramatically at all salinity levels and after 96 hours of aging, there was no seed germination at 150 mM.
Highlights:
1- The best nonlinear model to study accelerated Chia seed response to salinity stress was selected using the model selection criterion.
2- Chia seed germination threshold to salinity stress was determined for not- aged and aged seeds.
Sajad Mijani, Mehdi Rastgoo, Ali Ghanbari, Mehdi Nassiri Mahallati,
Volume 8, Issue 1 (9-2021)
Volume 8, Issue 1 (9-2021)
Abstract
Extended abstract
Introduction: Purple nutsedge (Cyperus rotundus L.) is one of the problematic weeds worldwide prevalent in tropical and subtropical regions. Tubers are major tools through which purple nutsedge is propagated, whereas its seeds have a low ability to germinate. Therefore, evaluation of the response of tubers against environmental agents is great of importance to know the germination and emergence time. Germination, in turn, is mostly affected by temperature, among other environmental factors. Various models that are recognized as the Thermal Time model have been introduced to describe the seed germination pattern against temperature. Since predicting the emergence of reproductive organs through the modeling is great of importance for improving the control strategies; the present study was carried out to investigate the response of tuber sprouting of purple nutsedge (Cyperus rotundus) against temperature using thermal time models.
Material and methods: The experiment was carried out as a randomized complete block design with three replications in a germinator. Each replicate was placed on a separate shelf. For each replicate, 15 tubers were placed inside a 20 cm Petri dish on a filter paper and then 100 ml of water was added. The experiment was performed separately for constant temperatures of 10, 15, 20, 25, 30, 35, and 40 °C in absolute darkness. To analyze the data as modeling, five thermal time models were evaluated based on the statistical distributions of normal, Weibull, Gumble, logistic and log logistic. Indices such as R2, RMSE, RMSE%, and AICc were used to evaluate the models.
Results: The results showed that all models predicted the germination response of purple nutsedge tuber with high accuracy (R2 = 0.95). A comparison of models based on AICc values showed significant superiority of the Gumble model over other models. According to this index, there was no difference between logistic and log logistic models with normal. Among the models, Weibull was identified as the most inappropriate model. Different models estimated the final germination (Gmax) between 0.93 to 0.94 (93 to 94%). The base temperature was estimated through different models from 7.10 to 7.47 °C. Among the models, the model based on the Gumble distribution proved the skew to the right of the thermal time and Tm. According to the Gumble model, the thermal time parameters required to reach 50% germination (θT (50)) equals 123.8 ° C day and the maximum temperature for germination at 50% probability (Tc (50)) was estimated to be 46.10 ° C.
Conclusion: the thermal time model based on the Gumble probability distribution was most plausible among the models. Also, a distributed right skewness related to the thermal time and Tm was proved through the Gumble model. The parameters obtained from the Gumble model can be used to predict the sprouting of purple nutsedge tubers.
Highlights:
Introduction: Purple nutsedge (Cyperus rotundus L.) is one of the problematic weeds worldwide prevalent in tropical and subtropical regions. Tubers are major tools through which purple nutsedge is propagated, whereas its seeds have a low ability to germinate. Therefore, evaluation of the response of tubers against environmental agents is great of importance to know the germination and emergence time. Germination, in turn, is mostly affected by temperature, among other environmental factors. Various models that are recognized as the Thermal Time model have been introduced to describe the seed germination pattern against temperature. Since predicting the emergence of reproductive organs through the modeling is great of importance for improving the control strategies; the present study was carried out to investigate the response of tuber sprouting of purple nutsedge (Cyperus rotundus) against temperature using thermal time models.
Material and methods: The experiment was carried out as a randomized complete block design with three replications in a germinator. Each replicate was placed on a separate shelf. For each replicate, 15 tubers were placed inside a 20 cm Petri dish on a filter paper and then 100 ml of water was added. The experiment was performed separately for constant temperatures of 10, 15, 20, 25, 30, 35, and 40 °C in absolute darkness. To analyze the data as modeling, five thermal time models were evaluated based on the statistical distributions of normal, Weibull, Gumble, logistic and log logistic. Indices such as R2, RMSE, RMSE%, and AICc were used to evaluate the models.
Results: The results showed that all models predicted the germination response of purple nutsedge tuber with high accuracy (R2 = 0.95). A comparison of models based on AICc values showed significant superiority of the Gumble model over other models. According to this index, there was no difference between logistic and log logistic models with normal. Among the models, Weibull was identified as the most inappropriate model. Different models estimated the final germination (Gmax) between 0.93 to 0.94 (93 to 94%). The base temperature was estimated through different models from 7.10 to 7.47 °C. Among the models, the model based on the Gumble distribution proved the skew to the right of the thermal time and Tm. According to the Gumble model, the thermal time parameters required to reach 50% germination (θT (50)) equals 123.8 ° C day and the maximum temperature for germination at 50% probability (Tc (50)) was estimated to be 46.10 ° C.
Conclusion: the thermal time model based on the Gumble probability distribution was most plausible among the models. Also, a distributed right skewness related to the thermal time and Tm was proved through the Gumble model. The parameters obtained from the Gumble model can be used to predict the sprouting of purple nutsedge tubers.
Highlights:
- Thermal time models were evaluated for prediction of tuber sprouting of purple nutsedge.
- The thermal time model based on the Gumble distribution was superior over the normal distribution.
- Thermal time and Tm for tuber sprouting of purple nutsedge were distributed as right skewness.
Mohammad Hossein Banakar, Hamzeh Amiri, Gholam Hassan Ranjbar, Mohammad Raza Sarafraz Ardakani,
Volume 8, Issue 2 (3-2022)
Volume 8, Issue 2 (3-2022)
Abstract
Extended Abstract
Introduction: Fenugreek, is a medicinal plant that has been considered as a salt tolerant crop. This research was conducted to investigate the effects of salt stress on seedling emergence characteristics and determination of the salt tolerance threshold, declivity of emergence and salt tolerance index of some fenugreek ecotypes.
Material and Methods: Seeds of five ecotypes (Ardestani, Isfahani, hendi, Mashhadi, Neyrizi) were subjected to seven levels of salinity (0.5, 3, 6, 9, 12, 15 and 18 dS/m) in a factorial experiment based on a completely randomized design with three replications. In this research, experimental models (linear, sigmoidal, exponential and multi-component) were used.
Results: Results showed that increasing levels of salinity decreased seedling emergence percentage and rate. In Ardestani and Isfahani ecotypes, increase of salinity up to 3 dS/m had no effect on seedling emergence percentage and thereafter, decreased it, significantly. The maximum seedling emergence percentage (94.62%) belonged to Hendi in control treatment. Hendi ecotype had also the highest emergence percentage (25.81%) at 18 dS/m. Although the highest seedling emergence rate (5.93 per day) belonged to Mashhadi ecotype in control treatment, it didn’t show any significant difference to Hendi, Neyrizi and Isfahani ecotypes. In Ardestani, Mashhadi and Neyrizi ecotypes, seedling length decreased significantly with increasing salinity, but this decrease was not significant in Isfahani ecotype between salinities of 3 and 6 dS/m and also 12 and 15 dS/m. In Hendi ecotype, seedling length at 3 dS/m was similar to control, but higher salinities caused a significant reduction. The maximum value of seedling vigor index (20.44) belonged to Mashhadi and Neyrizi ecotypes in control treatment and Ardestani ecotype had the lowest one (0.39) at 18 dS/m. Results showed that seedling dry weight was first unchanged up to salinity level of 3 dS/m and then gradually decreased with increasing salinity. In Hendi and Neyrizi ecotypes, applying salinities higher than 6 dS/m, gradually decreased seedling dry weight. The salt tolerance threshold of fenugreek for Ardestani, Isfahani, Hindi, Mashhadi and Neyrizi ecotypes was 4.69, 4.90, 7.83, 1.69 and 1.57 dS/m, respectively. Thus, the highest salt tolerance threshold (7.83 dS/m) and the declivity of emergence percentage (7.55%) was obtained from Hendi ecotype and the lowest one from Neyrizi ecotype (1.57 and 4.63 dS/m, respectively). Results of nonlinear models showed that the highest salinity in which 50 percent of seedlings emerged was obtained in Hendi ecotype (14.24 dS/m).
Conclusion: Based on the results, comparing the salt tolerance index of fenugreek ecotypes and also evaluating of some experimental models showed that Hendi ecotype may be introduced as the most tolerant ecotype to salinity stress at the emergence stage to exploit saline soil and water resources.
Highlights:
- Different fenugreek ecotypes in terms of salinity tolerance at seedling emergence stage were compared using some experimental models.
- The salt tolerance threshold, declivity of emergence and also salt tolerance index was reported for some fenugreek ecotypes.
Meysam Miri, Mohammdreza Amerian, Mohsen Edalat, Mehdi Baradaran Firouzabadi, Hasan Makarian,
Volume 8, Issue 2 (3-2022)
Volume 8, Issue 2 (3-2022)
Abstract
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.
Fatemeh Lajorak Shirpour, Yazdan Izadi, Dr. Seyed Amir Moosavi,
Volume 8, Issue 2 (3-2022)
Volume 8, Issue 2 (3-2022)
Abstract
Extended Abstract
Introduction: Seed germination is one of the most important factors which determine the success of failure of crop establishment. In the absence of other environmental limiting factors such as moisture, temperature would determine the rate and overall seed germination. This research was conducted to investigate the effect of temperature regimes on seed germination, quantify the response of germination rate to temperature and determine the cardinal temperatures for different germination percentiles in Solanum lycopersicom.
Materials and Methods: Two-way factorial experiment including seven constant temperatures (5, 10, 15, 20, 25, 30 and 35 oC) and two tomato varieties (Red cherry: var. Cerasiformi and Yellow pearl: var. Yellow Pear) was conducted based on a completely randomized design arranged with thee replications at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan in 2019. Beta, segmented and dent-like functions were used to determine the relationship between germination rate and temperature. Logistic model was used to describe the suitable pattern for the germination of these two cultivars in response to each temperature level.
Results: Results of analysis of variance showed that the interaction effect of temperature and cultivar was significant on all studied traits. Results showed that respectively at temperatures of 15, 20, 25 and 30 oC, total seed germination for yellow pearl tomato was 93%, 96%, 95% and 86% and for red cherry tomato was 95, 98, 93 and 98 percent. There was no seed germination for both tomato varieties at 5, 10 and 35 oC. Based on the results of the fitted models, it was revealed that among the tested non-linear regression models, segmented model described the germination rate of the studied tomato cultivars against the temperature the best (AICc≤70, R2=0.93). Three parameters logistic functions exhibited a reasonable fit (R2=0.96) for germination time course under temperature range of 15 to 30 oC in both cultivars. Based on the segmented model, base, optimum and ceiling temperatures of Yellow pearl and Cherry tomato were estimated 11.25, 28.72, 35.00 oC and 10.97, 28.361 and 35 oC, respectively.
Conclusion: Both tomato cultivars exhibited sensitivity to changes in temperature. Seed germination rate and number of the germinated seeds increased at temperatures higher than base. This increase continued until the optimum temperature and then started to decline as the temperature exceeded from optimum range. Also, results obtained from the logistic function showed that Yellow pearl cultivar is more sensitive to supra-optimal temperatures compared with Cherry tomato, and germination percentage of the 97.79 to 85.09 percent as temperature reached from 25 to 30 oC.
Highlights:
1- The pattern of seed germination in two new tomato cultivars was investigated under temperatures regimes
2- Cardinal temperatures of two new tomato varieties was estimated using nonlinear regression models
Introduction: Seed germination is one of the most important factors which determine the success of failure of crop establishment. In the absence of other environmental limiting factors such as moisture, temperature would determine the rate and overall seed germination. This research was conducted to investigate the effect of temperature regimes on seed germination, quantify the response of germination rate to temperature and determine the cardinal temperatures for different germination percentiles in Solanum lycopersicom.
Materials and Methods: Two-way factorial experiment including seven constant temperatures (5, 10, 15, 20, 25, 30 and 35 oC) and two tomato varieties (Red cherry: var. Cerasiformi and Yellow pearl: var. Yellow Pear) was conducted based on a completely randomized design arranged with thee replications at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan in 2019. Beta, segmented and dent-like functions were used to determine the relationship between germination rate and temperature. Logistic model was used to describe the suitable pattern for the germination of these two cultivars in response to each temperature level.
Results: Results of analysis of variance showed that the interaction effect of temperature and cultivar was significant on all studied traits. Results showed that respectively at temperatures of 15, 20, 25 and 30 oC, total seed germination for yellow pearl tomato was 93%, 96%, 95% and 86% and for red cherry tomato was 95, 98, 93 and 98 percent. There was no seed germination for both tomato varieties at 5, 10 and 35 oC. Based on the results of the fitted models, it was revealed that among the tested non-linear regression models, segmented model described the germination rate of the studied tomato cultivars against the temperature the best (AICc≤70, R2=0.93). Three parameters logistic functions exhibited a reasonable fit (R2=0.96) for germination time course under temperature range of 15 to 30 oC in both cultivars. Based on the segmented model, base, optimum and ceiling temperatures of Yellow pearl and Cherry tomato were estimated 11.25, 28.72, 35.00 oC and 10.97, 28.361 and 35 oC, respectively.
Conclusion: Both tomato cultivars exhibited sensitivity to changes in temperature. Seed germination rate and number of the germinated seeds increased at temperatures higher than base. This increase continued until the optimum temperature and then started to decline as the temperature exceeded from optimum range. Also, results obtained from the logistic function showed that Yellow pearl cultivar is more sensitive to supra-optimal temperatures compared with Cherry tomato, and germination percentage of the 97.79 to 85.09 percent as temperature reached from 25 to 30 oC.
Highlights:
1- The pattern of seed germination in two new tomato cultivars was investigated under temperatures regimes
2- Cardinal temperatures of two new tomato varieties was estimated using nonlinear regression models
Majid Azimmohseni, Farshid Ghaderi-Far, Mahnaz Khalafi, Hamid Reza Sadeghipour, Marzieh Ghezel,
Volume 9, Issue 1 (9-2022)
Volume 9, Issue 1 (9-2022)
Abstract
Extended abstract
Introduction: Numerous studies are being carried out to reveal the effects of different treatments on the germination of seeds from various plants. The most commonly used method of analysis is the nonlinear regression which estimates germination parameters. Although the nonlinear regression has been performed based on different models, some serious problems in its structure and results motivated researchers to investigate alternative approaches with higher accuracy and precision. The main purpose of the present research is to introduce the alternative parametric time to event model and comparing its reliability to the nonlinear regression in experiments carried out under different conditions.
Materials and Methods: The results of four different experiments were used here including the effect of Potassium cyanide on walnut seed germination, the effect of salinity on wheat seed germination, the effect of water potential on corn seed germination and the effect of temperature on cotton seed germination. The nonlinear regression and time to event methods were applied based on the Gompertz model. The obtained standard errors from the two models were further assessed using the Monte-Carlo method.
Results: Both methods provided well-fitting models according to the MSE and R2 criteria. Although the germination parameters were approximately identical in both models, the standard error of parameters in nonlinear regression was significantly less than those of time to event method except for the experiments in which all tested seeds germinated within the time frame of study so that in the latter case the estimated standard errors in both models were identical. The Monte-Carlo method confirmed the results of the time to event model and reveals the underestimation of the nonlinear regression method in estimating the standard error of parameters.
Conclusions: Generally, the results of this research showed that the time to event model can be trustfully utilized in seed germination studies under different conditions and treatments. This model, not only provides precise estimates of the germination parameters but also provides the precise standard error of parameters that have important roles in making inferences for parameters. The drc package in R software enables researchers to fit the different time to event models.
Highlights:
- Using the time to the event model in estimation of seed germination parameters.
- Comparing the time to event and nonlinear regression methods in different seed germination experiments.
- Using the Monte-Carlo method for investigating the accuracy of results of the used methods.
Fatemeh Ghorbannezhad, Mohsen Zavareh, Farzad Sharifzadeh,
Volume 10, Issue 1 (9-2023)
Volume 10, Issue 1 (9-2023)
Abstract
Extended abstract
Introduction: Linseed (Linum usitatissimum L.) is a multipurpose crop and is cultivated to obtain oil, fiber, and seeds. Under optimal moisture conditions, the temperature is considered an environmental factor affecting the germination of this crop. Hence, knowing the cardinal temperatures can help farmers to predict the successful germination, emergence, and even yield of linseed and help scientists to develop new cultivars that are more tolerant to high temperatures. Therefore, this study was performed to determine the temperature range and the cardinal temperatures of germination in two linseed genotypes.
Material and methods: The germination response of two linseed genotypes (Golchin genotype and Line 286) to nine temperatures (3, 5, 10, 15, 20, 25, 30, 35, and 40 Celsius degrees) was quantified in a CRD based split-plot experiment with four replications. For this purpose, three nonlinear regression models (beta, segmented, and dent-like) were used to fit to the data and select the superior model. The superior model was selected using the Akaike information index (AIC), the modified Akaike index (AICc), and ∆i.
Results: Findings showed that the beta model had the best performance in estimating the line 286 cardinal temperatures according to its lower AIC (-3.96), AICc (-89.61), and ∆i (0). Accordingly, the base, optimum, and maximum temperature as well as the number of biological hours estimated by this model for Line 286 were 7.18, 24.22, 40.16 Celsius degrees, and 19.25 hours, respectively. In the Golchin genotype, the beta model with the lowest AIC=-3.89 and AICc= -89.083 fitted better compared with the other models. Nonetheless, considering ∆i for beta which was respectively 0, 1.61, and 4.49 for beta, segmented, and dent-like models, Beta and segmented models had a similar accuracy in estimation of cardinal temperatures for Golchin genotype. These findings represent that the suitable temperature range for germination of the Golchin genotype is 3.8- 23.85 Celsius degrees and the range of biological hours to 50% of germination varied from 16.42 to 19.77 hours.
Conclusion: Overall, according to the results of this study, it is possible to predict the time to germination under optimal moisture conditions using the beta model for Line 286 and one of the two beta and segmented models for the Golchin genotype.
Highlights:
1. A suitable model was developed for a suitable prediction of the seed germination percentage of two linseed genotypes (Golchin genotype and Line 286).
2. The cardinal temperatures for two linseed genotypes (Golchin genotype and Line 286) were determined.
Introduction: Linseed (Linum usitatissimum L.) is a multipurpose crop and is cultivated to obtain oil, fiber, and seeds. Under optimal moisture conditions, the temperature is considered an environmental factor affecting the germination of this crop. Hence, knowing the cardinal temperatures can help farmers to predict the successful germination, emergence, and even yield of linseed and help scientists to develop new cultivars that are more tolerant to high temperatures. Therefore, this study was performed to determine the temperature range and the cardinal temperatures of germination in two linseed genotypes.
Material and methods: The germination response of two linseed genotypes (Golchin genotype and Line 286) to nine temperatures (3, 5, 10, 15, 20, 25, 30, 35, and 40 Celsius degrees) was quantified in a CRD based split-plot experiment with four replications. For this purpose, three nonlinear regression models (beta, segmented, and dent-like) were used to fit to the data and select the superior model. The superior model was selected using the Akaike information index (AIC), the modified Akaike index (AICc), and ∆i.
Results: Findings showed that the beta model had the best performance in estimating the line 286 cardinal temperatures according to its lower AIC (-3.96), AICc (-89.61), and ∆i (0). Accordingly, the base, optimum, and maximum temperature as well as the number of biological hours estimated by this model for Line 286 were 7.18, 24.22, 40.16 Celsius degrees, and 19.25 hours, respectively. In the Golchin genotype, the beta model with the lowest AIC=-3.89 and AICc= -89.083 fitted better compared with the other models. Nonetheless, considering ∆i for beta which was respectively 0, 1.61, and 4.49 for beta, segmented, and dent-like models, Beta and segmented models had a similar accuracy in estimation of cardinal temperatures for Golchin genotype. These findings represent that the suitable temperature range for germination of the Golchin genotype is 3.8- 23.85 Celsius degrees and the range of biological hours to 50% of germination varied from 16.42 to 19.77 hours.
Conclusion: Overall, according to the results of this study, it is possible to predict the time to germination under optimal moisture conditions using the beta model for Line 286 and one of the two beta and segmented models for the Golchin genotype.
Highlights:
1. A suitable model was developed for a suitable prediction of the seed germination percentage of two linseed genotypes (Golchin genotype and Line 286).
2. The cardinal temperatures for two linseed genotypes (Golchin genotype and Line 286) were determined.
Mahboubeh Shahbazi, Jafar Asghari, Behnam Kamkar, Edris Taghvaie Salimi,
Volume 10, Issue 2 (3-2023)
Volume 10, Issue 2 (3-2023)
Abstract
Extended abstract
Introduction: The germination process is one of the most critical stages of a plant's growth and determines the success of the emergence of a weed in an agroecosystem because it is the first stage in which the weed competes for a niche. Various environmental factors, including temperature and moisture, affect the germination of weed seeds. Modeling techniques are capable of predicting germination, seedling emergence, and establishment of weed species. The ability to predict weed germination in response to environmental conditions is very effective for the development of control programs. The experiment was conducted to determine the cardinal temperature and evaluate the best model for quantifying the response of the germination rate of Western ragweed weed seeds under different water stress conditions.
Materials and Methods: A factorial experiment was conducted in the form of a completely randomized design in three replications. The investigated factors include temperature with eight levels (5, 10, 15, 20, 25, 30, 35, and 40 C˚) and water potential with six levels (0, -0.3, -0.6, -0.9, -1.2, and -1.5 MPa) on the germination of Western ragweed. In order to quantify the response of Western ragweed germination rate to temperature, three non-linear Dent-like, Beta, and Segmented regression models were used.
Results: The results showed that the effect of temperature, water potential, and their interactions on maximum germination, germination rate, and time required to reach 10, 50, and 90 percent germination were significant. Also, the results showed that by increasing the temperature from 10 to 25 C˚, the percentage and rate of germination increased whereas by increasing water potential, the percentage and rate of germination decreased. In comparing the models, based on RMSE, R2, CV, and coefficients a and b parameters, the Beta model was the most suitable for estimating the temperatures of cardinal Western ragweed. The base, optimum, and ceiling temperatures using the Beta model were 3.88, 25, and 40 C˚, respectively.
Conclusions: The use of the Beta model to quantify the germination response of Western ragweed seeds to different levels of water potential at different temperatures had acceptable results. Therefore, by using the output of these models at different temperatures, it is possible to predict the germination rate at different potentials.
Highlights:
1- Germination cardinal temperatures and the effect of water potential on western ragweed weed were investigated.
2- Estimation of different models to quantify the response of germination rate to temperature and different water potentials.
Introduction: The germination process is one of the most critical stages of a plant's growth and determines the success of the emergence of a weed in an agroecosystem because it is the first stage in which the weed competes for a niche. Various environmental factors, including temperature and moisture, affect the germination of weed seeds. Modeling techniques are capable of predicting germination, seedling emergence, and establishment of weed species. The ability to predict weed germination in response to environmental conditions is very effective for the development of control programs. The experiment was conducted to determine the cardinal temperature and evaluate the best model for quantifying the response of the germination rate of Western ragweed weed seeds under different water stress conditions.
Materials and Methods: A factorial experiment was conducted in the form of a completely randomized design in three replications. The investigated factors include temperature with eight levels (5, 10, 15, 20, 25, 30, 35, and 40 C˚) and water potential with six levels (0, -0.3, -0.6, -0.9, -1.2, and -1.5 MPa) on the germination of Western ragweed. In order to quantify the response of Western ragweed germination rate to temperature, three non-linear Dent-like, Beta, and Segmented regression models were used.
Results: The results showed that the effect of temperature, water potential, and their interactions on maximum germination, germination rate, and time required to reach 10, 50, and 90 percent germination were significant. Also, the results showed that by increasing the temperature from 10 to 25 C˚, the percentage and rate of germination increased whereas by increasing water potential, the percentage and rate of germination decreased. In comparing the models, based on RMSE, R2, CV, and coefficients a and b parameters, the Beta model was the most suitable for estimating the temperatures of cardinal Western ragweed. The base, optimum, and ceiling temperatures using the Beta model were 3.88, 25, and 40 C˚, respectively.
Conclusions: The use of the Beta model to quantify the germination response of Western ragweed seeds to different levels of water potential at different temperatures had acceptable results. Therefore, by using the output of these models at different temperatures, it is possible to predict the germination rate at different potentials.
Highlights:
1- Germination cardinal temperatures and the effect of water potential on western ragweed weed were investigated.
2- Estimation of different models to quantify the response of germination rate to temperature and different water potentials.
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Seed Science and Technology, Seed Physiology, Seed Ecology, Modeling, Seed Health, Germination Characteristics, Seed Dormancy, Seed Ageing, Seed Storage, Seed PrimingVote
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