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Showing 11 results for Cardinal Temperature
Jalal Jalilian, Nabi Khaliliaqdam,
Volume 2, Issue 1 (9-2015)
Volume 2, Issue 1 (9-2015)
Abstract
Rocket (Eruca sativa) is an important medicinal plant which not be done any experiment about its germination quantification response to temperature. Thus, an experiment base on CRD performed in seed research laboratory of Urmia University with four replications with ten levels of temperatures includes 1, 3, 5, 10, 15, 20, 25, 30, 35 and 40 0C. Results revealed that the temperature had significant effects on the rate and germination percent and Dent-like model estimated greatly cardinal temperature (base, upper and bottom optimum and ceiling temperatures). Germination rate stopped at equal and less than 0.79 and equal and higher than 47.6 0C and Rmax were 0.066 in 16.9-32.6 0C. Also, results emphasized that Rocket seed needs low temperature for germination but, germination rate and percent of Rocket increased by temperature increment. Therefore, the Rocket can germinate and emerge in dispersal spans of an environmental thermal from 0.79 to 47.6 0C and thus recognized as a crop with allowable production for various seasons and climate.
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.
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.
Keyvan Maleki, Elias Soltani, Iraj Alahdadi, Majid Ghorbani Javid,
Volume 6, Issue 2 (3-2020)
Volume 6, Issue 2 (3-2020)
Abstract
Extended abstract
Introduction: Conditional dormancy (CD) is a dynamic state between dormancy (D) and nondormancy (ND). Seeds at the conditional dormancy stage germinate over a narrower range of temporal conditions. Conditional dormancy is usually observed in seeds with physiological dormancy. However, primary conditional dormancy has also been seen in some freshly harvested seeds. The purpose of the present study was to investigate whether freshly harvested oilseeds have non-dormancy or conditional dormancy.
Materials and Methods: A factorial experiment was conducted based on a completely randomized design with four replications at Seed Technology Laboratory of Aburaihan Campus, University of Tehran, Iran, in 2018. In this experiment, seeds of rapeseed were collected from 20 different locations in Golestan and Mazandaran provinces. Following that, a germination test was carried out at different temperatures (5, 15, 20, 30, 35°C), and the germination percentage and seed germination rate were recorded. In order to break seed dormancy, two treatments were used: gibberellic acid and after-ripening. For after-ripening treatment, seeds were stored in a paper bag in a dry and dark environment for 6 months. For gibberellic acid treatment, a solution of 100 parts per million (PPM) of gibberellic acid was prepared and added to the Petri dishes. Subsequently, the percentage and rate of germination were recorded.
Results: The results showed that freshly harvested seeds had primary conditional dormancy and germinated in a narrow range of temporal conditions. In addition, cardinal temperatures for freshly harvested seeds were 4.45 and 27.8 for bases and ceilings, respectively. Following gibberellic acid and after-ripening treatments, seeds germinated in a wider range of temperatures and base and ceiling temperatures reached 1.74 and about 40°C, respectively. Thus, germination percentage of seeds treated with gibberellic acid and after-ripening increased at both high and low temperatures. However, the increase in germination percentage was higher at high temperatures than low temperatures. In addition, the effect of gibberellic acid treatment was more than that of after-ripening treatment on the release of dormancy, and after-ripening treatment had an intermediate effect between the gibberellic acid and freshly harvested seeds.
Conclusion: Based on the results of this experiment, the application of gibberellic acid and after-ripening treatments resulted in breaking the dormancy of freshly harvested seeds and increased germination temperature range at high and low temperatures. Of the two treatments, gibberellic acid had the greatest effect on breaking dormancy and increasing temperature range. Among the cultivars, these changes were maximum in the germination capacity of Hyola 50 and Trapar cultivars and Trapar cultivar had minimum changes.
Highlights:
1-Conditional dormancy of oilseed cultivars was investigated under different environmental conditions.
2-Application of gibberellic acid and after-ripening treatments resulted in breaking primary conditional dormancy in oilseed cultivars.
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.
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:
Morteza Gorzin, Farshid Ghaderi-Far, Hamid Reza Sadeghipour, Ebrahim Zeinali,
Volume 8, Issue 1 (9-2021)
Volume 8, Issue 1 (9-2021)
Abstract
Extended abstract
Introduction: Since the maximum percentage and rate of germination of rapeseed occur at a certain temperature, finding these temperatures can play an important role in determining the appropriate time and place for the cultivation of different cultivars. Also, light can affect the germination percentage of rapeseed at different temperatures, but the response of rapeseed to light, especially at lower and higher temperatures, has not been studied. Therefore, this study aimed to investigate the changes in the germination of rapeseed cultivars at different temperatures and determine cardinal germination temperatures based on germination percentage and rate under both the presence and absence of light conditions.
Materials and methods: In this study, germination tests were carried out at 5, 10, 15, 20, 25, 30, 35, 37, and 40°C temperatures in two light conditions (12 h light / 12 h dark) and darkness on nine spring cultivars (Traper, Agamax, Hayola-50, Hayola-420, RGS, Mahtab, Hayola-61, Zafar, and Zarfam) and one winter cultivar (Garo). The four-parameter Hill model was used to describe germination changes over time and the dent model was used to calculate cardinal temperatures. Seed viability at lower and higher temperatures was evaluated by the tetrazolium test.
Results: The evaluation of the trend of cumulative germination percentage over time in different cultivars showed that maximum germination percentage of all cultivars happened in the temperature range between 15-30 °C, some in the temperature range of 10-30 °C (Hyola-61) and others even in the temperature range of 5-30 °C (RGS, Mahtab, Garo, Zafar, and Zarfam) had the highest germination percentage. The highest germination rate in all cultivars was observed at the temperature range of 22-35 °C. Light only had an effect on the germination percentage of the seeds at sub and super optimal temperatures. At these temperatures, light increased the germination percentage. The remaining seed of 5, 10, 35, 37, and 40 °C temperature after transfer to 20 °C did not germinate, whereas most of them were viable based on the tetrazolium test.
Conclusion: The difference in the optimum temperature range for germination percentage and rate showed that to optimize seed performance, the optimal temperature range between the germination percentage and germination rate should be considered as the optimum temperature for germination. At sub and supra optimal temperatures, light leads to improved germination in some cultivars. The effect of light on germination at supra optimal temperatures was far higher than that of sub-optimal ones. Survival of the remaining seeds at the sub and supra optimal temperatures in some cultivars provided evidence of thermo-dormancy in these cultivars, this issue needs further investigation in the future.
Highlights:
1- The cardinal temperatures were studied based on both the percentage and rate of germination and the effect of light on them.
2- Some new varieties such as Traper and Agamax that little information about their characteristics is available were examined.
3- In this study, the reason for the lack of germination of rapeseed at the sub and supra optimal temperatures especially in the darkness has been mentioned.
Introduction: Since the maximum percentage and rate of germination of rapeseed occur at a certain temperature, finding these temperatures can play an important role in determining the appropriate time and place for the cultivation of different cultivars. Also, light can affect the germination percentage of rapeseed at different temperatures, but the response of rapeseed to light, especially at lower and higher temperatures, has not been studied. Therefore, this study aimed to investigate the changes in the germination of rapeseed cultivars at different temperatures and determine cardinal germination temperatures based on germination percentage and rate under both the presence and absence of light conditions.
Materials and methods: In this study, germination tests were carried out at 5, 10, 15, 20, 25, 30, 35, 37, and 40°C temperatures in two light conditions (12 h light / 12 h dark) and darkness on nine spring cultivars (Traper, Agamax, Hayola-50, Hayola-420, RGS, Mahtab, Hayola-61, Zafar, and Zarfam) and one winter cultivar (Garo). The four-parameter Hill model was used to describe germination changes over time and the dent model was used to calculate cardinal temperatures. Seed viability at lower and higher temperatures was evaluated by the tetrazolium test.
Results: The evaluation of the trend of cumulative germination percentage over time in different cultivars showed that maximum germination percentage of all cultivars happened in the temperature range between 15-30 °C, some in the temperature range of 10-30 °C (Hyola-61) and others even in the temperature range of 5-30 °C (RGS, Mahtab, Garo, Zafar, and Zarfam) had the highest germination percentage. The highest germination rate in all cultivars was observed at the temperature range of 22-35 °C. Light only had an effect on the germination percentage of the seeds at sub and super optimal temperatures. At these temperatures, light increased the germination percentage. The remaining seed of 5, 10, 35, 37, and 40 °C temperature after transfer to 20 °C did not germinate, whereas most of them were viable based on the tetrazolium test.
Conclusion: The difference in the optimum temperature range for germination percentage and rate showed that to optimize seed performance, the optimal temperature range between the germination percentage and germination rate should be considered as the optimum temperature for germination. At sub and supra optimal temperatures, light leads to improved germination in some cultivars. The effect of light on germination at supra optimal temperatures was far higher than that of sub-optimal ones. Survival of the remaining seeds at the sub and supra optimal temperatures in some cultivars provided evidence of thermo-dormancy in these cultivars, this issue needs further investigation in the future.
Highlights:
1- The cardinal temperatures were studied based on both the percentage and rate of germination and the effect of light on them.
2- Some new varieties such as Traper and Agamax that little information about their characteristics is available were examined.
3- In this study, the reason for the lack of germination of rapeseed at the sub and supra optimal temperatures especially in the darkness has been mentioned.
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.
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 (2-2024)
Volume 10, Issue 2 (2-2024)
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.
Ramin Piri, Farzad Sharifzadeh, Naser Majnounhosseini,
Volume 11, Issue 1 (9-2024)
Volume 11, Issue 1 (9-2024)
Abstract
Extended abstract
Introduction: Currently, temperature and salinity stresses are spreading globally, which have a detrimental impact on the performance of various plants, particularly during seed germination and seedling growth stages. Therefore, the objective of this laboratory study was to examine the influence of temperature treatments and salinity levels on germination characteristics and initial seedling growth of kochia.
Materials and Methods: In the first experiment, temperature at nine levels (1, 5, 10, 15, 20, 25, 30, 35, and 40°C), and in the second experiment, salinity (osmotic potential at six levels (no stress, -0.4, -0.8, -1.2, -1.6, and -1.8 MPa) were considered as experimental treatments. In order to determine the cardinal temperatures (base, optimal, and ceiling) of germination in kochia seeds, non-linear regression models including the segmented, dent-like, and modified beta models were used.
Results: In the first experiment, the response of kochia germination rate was predicted by a segmented function with R2, RMSE, and AIC (Akaike) values of 0.92, 1.32, and 65.69, respectively, which indicates the high accuracy and precision of this model in predicting the cardinal temperatures of kochia seed germination compared with the other two models. In this model, the estimated base temperature for germination was 0.7°C, the optimal temperature was 20°C, and the ceiling temperature was 44.3°C. In the second experiment, salinity stress negatively affected the characteristics of seed germination in kochia, including germination percentage, germination rate, percentage of normal seedlings, seedling length, and seedling vigor index. The highest germination percentage of kochia seeds was observed under salt-free conditions with 88.66%, which decreased to 13% under -1.8 MPa salinity conditions.
Conclusions: In general, the results showed that the segmented model is more efficient and accurate than the other two models in predicting germination of kochia seeds under different temperature treatments. Also, increasing levels of salinity stress significantly reduced germination potential and seedling growth of kochia seeds, so that at a stress level of -1.8 MPa, germination rate decreased by 75% compared with stress-free condition.
Highlights:
Introduction: Currently, temperature and salinity stresses are spreading globally, which have a detrimental impact on the performance of various plants, particularly during seed germination and seedling growth stages. Therefore, the objective of this laboratory study was to examine the influence of temperature treatments and salinity levels on germination characteristics and initial seedling growth of kochia.
Materials and Methods: In the first experiment, temperature at nine levels (1, 5, 10, 15, 20, 25, 30, 35, and 40°C), and in the second experiment, salinity (osmotic potential at six levels (no stress, -0.4, -0.8, -1.2, -1.6, and -1.8 MPa) were considered as experimental treatments. In order to determine the cardinal temperatures (base, optimal, and ceiling) of germination in kochia seeds, non-linear regression models including the segmented, dent-like, and modified beta models were used.
Results: In the first experiment, the response of kochia germination rate was predicted by a segmented function with R2, RMSE, and AIC (Akaike) values of 0.92, 1.32, and 65.69, respectively, which indicates the high accuracy and precision of this model in predicting the cardinal temperatures of kochia seed germination compared with the other two models. In this model, the estimated base temperature for germination was 0.7°C, the optimal temperature was 20°C, and the ceiling temperature was 44.3°C. In the second experiment, salinity stress negatively affected the characteristics of seed germination in kochia, including germination percentage, germination rate, percentage of normal seedlings, seedling length, and seedling vigor index. The highest germination percentage of kochia seeds was observed under salt-free conditions with 88.66%, which decreased to 13% under -1.8 MPa salinity conditions.
Conclusions: In general, the results showed that the segmented model is more efficient and accurate than the other two models in predicting germination of kochia seeds under different temperature treatments. Also, increasing levels of salinity stress significantly reduced germination potential and seedling growth of kochia seeds, so that at a stress level of -1.8 MPa, germination rate decreased by 75% compared with stress-free condition.
Highlights:
- The cardinal temperatures (base, optimum, and ceiling temperatures) of kochia seed germination were determined.
- This research introduced 1°C temperature and -1.8 MPa of salinity level as low temperature stress and critical salinity, respectively.
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