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Showing 12 results for Regression
Zeinab Alipoor, Sohrab Mahmodi,
Volume 2, Issue 2 (2-2016)
Volume 2, Issue 2 (2-2016)
Abstract
In order to determinate the cardinal temperatures and investigate the effect of temperature on seed germination and seedling growth of Securigera securidaca, a study was conducted in a completely randomized design with 8 temperature treatments (5, 10, 15, 20, 25, 30, 35 and 40oC) and four replications in research laboratory of faculty of agriculture at the Birjand University in 2013. A two-segmented linear regression model was fitted between germination rate and temperatures to determine cardinal temperatures for germination. Cardinal (minimum, optimum and maximum) temperatures of germination were determined as -1, 22.5 and 40.2oC respectively. Maximum rate and percentage of germination obtained in the range of 20-25oC. Maximum of radicle length and dry weight, maximum of caulicle length and dry weight and maximum of vigor seedling were obtained in 20oC,10-20oC and 5-30oC respectively. Maximum and minimum germination uniformity (GU) was obtained in 25 and 5oC.
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.
Gholamhassan Ranjbar, Hossein Ghadiri,
Volume 3, Issue 2 (2-2017)
Volume 3, Issue 2 (2-2017)
Abstract
A controlled experiment was run to quantify emergence of Kochia indica under different temperature, salinity and seeding depth levels at Yazd National Salinity Research Center in 2013. Treatments were five day/night temperature regimes: 20/10, 25/15, 30/20, 35/25 and 40/30 °C, five salinity levels: 2, 6, 10, 14 and 18 dS m-1, and seeding depth on the surface (0 mm), 5, 10 and 15 mm. Final emergence percentage, emergence rate index and elapsed time (days) to reach 50% of the maximum emergence were measured. The results showed that the highest and lowest final emergence percentages were observed at 25/15°C and 40/30°C day/night, respectively. Final emergence percentages at salinity levels of 6, 10, 14 and 18 dS m-1were, respectively, 9, 22, 36 and 57% lower than 2 dS m-1. Final emergence percentages for 5, 10 and 15 mm seeding depths were, respectively, 30, 44 and 72% lower, as compared with the placement of seeds on the soil surface. Regression analysis showed that final emergence percentage linearly decreased with increase in salinity and seeding depth levels. However, elapsed time (days) to reach 50% of the maximum emergence (T50), increased as salinity and seeding depth increased, so that the highest T50 was obtained for 18 dS m-1 and seeding depth of 15 mm. Increase in salinity and seeding depth was associated with a significant decrease in emergence rate index. In addition, using a logistic regression equation, emergence rate of K. indica was quantified on each day after sowing for each temperature-salinity combination to predict the distribution range of the plant in these situations.
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:
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.
Asgar Ganje, Ali Ebadie, Ghasem Parmoon, Soodabeh Jahanbaksh,
Volume 7, Issue 2 (3-2021)
Volume 7, Issue 2 (3-2021)
Abstract
Extended Abstract
Introduction: Water deficit stress is one of the important factors affecting seed germination. This stress decrease germination rate and affects germination percentage under high levels as well. Seed priming improves germination by changing metabolic activities before radicle emergence. This investigation was conducted to evaluate the effect of seed priming by salicylic acid on the emergence index and grain weight of spring wheat under water deficit stress.
Material and Method: These experiments were conducted as factorial based on the completely randomized design with three replicates in the greenhouse of the Faculty of the Agriculture Sciences University of Mohaghegh Ardabili. Experiment treatments included different salicylic acid concentrations (0, 1, 2 mM) and water deficit stresses (25%, 45%, 65% and 85% Field capacity).
Result: According to results, emergence index (emergence percentage and emergence rate, uniformity emergence, and times to 10, 50, and 90% emergence) was influenced at 1% by water deficit stress. The effect of salicylic acid was significant on the emergence index. The interactions of water deficit stress and salicylic acid were effective at 1% on emergence uniformity and time to 90% emergence. Changes in plant height and heading rate were lower under water deficit stress. Also, both slope (b) and maximum content (a) decreased by water stress (22% and 7%). Priming by salicylic acid at 2 mM had the highest effect on both traits and resulted in a decrease in their slopes (17% and 13%) and an increase in their maximum content (34 and 10%). Plant dry weight was influenced by the interactions of water deficit stress and salicylic acid at 5% level. The plant's final height and grain weight was influenced by water deficit stress and salicylic acid. The highest grain weight was obtained at 80% and 60% field capacity with means of 0.79 and 0.75 g, which had no significant differences with eachother. The heights grain weight (0.72 g) was obtained by application of 2 mM salicylic acid which led to an increase of 250% compared to control.
Conclusions: Overall, we showed that water deficit stress resulted in decreased emergence rate and emergence percentage of wheat and finally declined plant growth and grain weight. Application of salicylic acid in seed priming resulted in improvement in the emergence index, growth, and grain weight of wheat. Also, the highest grain weight was observed at 2 mM concentration and it can be considered as the enhancing treatment.
Highlights:
1- Response of plant growth stage to stress was quantified using nonlinear regression
2- Relationship between emergence and grain weight was investigated under stress and priming by salicylic acid.
Introduction: Water deficit stress is one of the important factors affecting seed germination. This stress decrease germination rate and affects germination percentage under high levels as well. Seed priming improves germination by changing metabolic activities before radicle emergence. This investigation was conducted to evaluate the effect of seed priming by salicylic acid on the emergence index and grain weight of spring wheat under water deficit stress.
Material and Method: These experiments were conducted as factorial based on the completely randomized design with three replicates in the greenhouse of the Faculty of the Agriculture Sciences University of Mohaghegh Ardabili. Experiment treatments included different salicylic acid concentrations (0, 1, 2 mM) and water deficit stresses (25%, 45%, 65% and 85% Field capacity).
Result: According to results, emergence index (emergence percentage and emergence rate, uniformity emergence, and times to 10, 50, and 90% emergence) was influenced at 1% by water deficit stress. The effect of salicylic acid was significant on the emergence index. The interactions of water deficit stress and salicylic acid were effective at 1% on emergence uniformity and time to 90% emergence. Changes in plant height and heading rate were lower under water deficit stress. Also, both slope (b) and maximum content (a) decreased by water stress (22% and 7%). Priming by salicylic acid at 2 mM had the highest effect on both traits and resulted in a decrease in their slopes (17% and 13%) and an increase in their maximum content (34 and 10%). Plant dry weight was influenced by the interactions of water deficit stress and salicylic acid at 5% level. The plant's final height and grain weight was influenced by water deficit stress and salicylic acid. The highest grain weight was obtained at 80% and 60% field capacity with means of 0.79 and 0.75 g, which had no significant differences with eachother. The heights grain weight (0.72 g) was obtained by application of 2 mM salicylic acid which led to an increase of 250% compared to control.
Conclusions: Overall, we showed that water deficit stress resulted in decreased emergence rate and emergence percentage of wheat and finally declined plant growth and grain weight. Application of salicylic acid in seed priming resulted in improvement in the emergence index, growth, and grain weight of wheat. Also, the highest grain weight was observed at 2 mM concentration and it can be considered as the enhancing treatment.
Highlights:
1- Response of plant growth stage to stress was quantified using nonlinear regression
2- Relationship between emergence and grain weight was investigated under stress and priming by salicylic acid.
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.
Farshid Yousefi, Abdolreza Sihampoosh, Abdolmahdi Bakhshandeh, Seyyed Amir Mousavi,
Volume 8, Issue 1 (9-2021)
Volume 8, Issue 1 (9-2021)
Abstract
Extended Abstract
Introduction: Coneflower herbal medicinal plant is from the Asteraceae family, native to North America. Because of its immune-boosting properties, it is used to treat a variety of pathogens. The seed germination stage is one of the crucial and crucial stages in the growth cycle of plant species that can play an important role in the production process by optimal establishment of seedlings. Seed of Coneflower germinates and grows very slowly and weakly. Therefore, the use of some plant growth regulators, such as the gibberellin hormone, can play an important role in improving seed germination. The aim of this study was investigate the effect of hormone seed priming using gibberellin on seed germination quality of Coneflower.
Material and Methods: A factorial experiment was conducted based on the complete randomized design arranged with three replications. The experiment was conducted at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan, 2018. Experimental treatments were different concentrations of gibberellin (0, 50, 100, 200, 400, and 800 mg/l) as the first factor and the durations of seed priming (12, 24, and 48 hour) as the second factor.
Results: Results of in vitro studies showed that the interaction of gibberellin in priming time on percentage, rate and mean germination time, root and shoot length, seed vigor index, peroxidase activity at 1% and Seed soluble protein content was significant at 5% level. Seed germination quality and protein content increased by the application of 200 mg/l gibberellin for the 24 hours, whereas at the concentrations of 400 and 800 mg/l, gibberellin reduced germination quality and antioxidant enzymes activities. Results of stepwise regression models of antioxidant enzymes activity and protein content with germination indices showed that these traits were significantly entered into the prediction model. It was observed that in all traits except for the rate and the mean germination time, the amount of protein entered the prediction equation. In general, stepwise regression models predicted stem length and power index better than other traits and showed the highest coefficients in these traits with values of 0.85 and 0.83. Also, catalase and peroxidase activities were significantly correlated with rate and mean germination time only. The amount of soluble protein had a positive and significant correlation with all studied traits except germination rate and mean germination time. The highest correlation coefficients for protein content were obtained from longitudinal power index with correlation coefficient (r = 0.856).
Conclusion: Based on the obtained results, the best hormone priming treatment was 200 mg/l gibberellin for the durations of 24 hour.
Highlights:
1- The role of gibberellin hormone on seed germination traits Coneflower was evaluated
2- The effect of gibberellin hormone on the activity of antioxidant enzymes and soluble proteins during seed germination was investigated.
Introduction: Coneflower herbal medicinal plant is from the Asteraceae family, native to North America. Because of its immune-boosting properties, it is used to treat a variety of pathogens. The seed germination stage is one of the crucial and crucial stages in the growth cycle of plant species that can play an important role in the production process by optimal establishment of seedlings. Seed of Coneflower germinates and grows very slowly and weakly. Therefore, the use of some plant growth regulators, such as the gibberellin hormone, can play an important role in improving seed germination. The aim of this study was investigate the effect of hormone seed priming using gibberellin on seed germination quality of Coneflower.
Material and Methods: A factorial experiment was conducted based on the complete randomized design arranged with three replications. The experiment was conducted at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan, 2018. Experimental treatments were different concentrations of gibberellin (0, 50, 100, 200, 400, and 800 mg/l) as the first factor and the durations of seed priming (12, 24, and 48 hour) as the second factor.
Results: Results of in vitro studies showed that the interaction of gibberellin in priming time on percentage, rate and mean germination time, root and shoot length, seed vigor index, peroxidase activity at 1% and Seed soluble protein content was significant at 5% level. Seed germination quality and protein content increased by the application of 200 mg/l gibberellin for the 24 hours, whereas at the concentrations of 400 and 800 mg/l, gibberellin reduced germination quality and antioxidant enzymes activities. Results of stepwise regression models of antioxidant enzymes activity and protein content with germination indices showed that these traits were significantly entered into the prediction model. It was observed that in all traits except for the rate and the mean germination time, the amount of protein entered the prediction equation. In general, stepwise regression models predicted stem length and power index better than other traits and showed the highest coefficients in these traits with values of 0.85 and 0.83. Also, catalase and peroxidase activities were significantly correlated with rate and mean germination time only. The amount of soluble protein had a positive and significant correlation with all studied traits except germination rate and mean germination time. The highest correlation coefficients for protein content were obtained from longitudinal power index with correlation coefficient (r = 0.856).
Conclusion: Based on the obtained results, the best hormone priming treatment was 200 mg/l gibberellin for the durations of 24 hour.
Highlights:
1- The role of gibberellin hormone on seed germination traits Coneflower was evaluated
2- The effect of gibberellin hormone on the activity of antioxidant enzymes and soluble proteins during seed germination was investigated.
Habib Nejadgharebaghi, Esfandiar Fateh, Amir Aynehband,
Volume 8, Issue 1 (9-2021)
Volume 8, Issue 1 (9-2021)
Abstract
Extended Abstract
Introduction: In Iran, the majority of research has been done on the depth of burial on crops and the effect of these factors on weeds resulted from seeds and rhziomes of seedlings has been less studied. Strangle Wort weed is one of the most problematic weeds in sugarcane fields, orchards, especially pistachio orchards, barren lands, and roads. Thus, this study aimed to find out the effect of different levels of burial depth and flood stress on the extent and quality of seedlings resulted from its rhizomes.
Material and Methods: Two separate greenhouse experiments based on completely randomized design with four replications were conducted in the experimental farm of Sugarcane Research Institute of Khuzestan province at 2014-2015 growing season. Flooding stress treatment included 7 levels of flooding stress (4, 8, 16, 24, 48, 72, and 96 flooding hours) and 6 levels of seed burial (1, 3, 5, 7, 10, and 15 cm) and rhizome burial depth treatment included 7 levels (1, 3, 5, 7, 10, and cm 15).
Results: With increasing levels of flood stress, all studied traits including root length, stem height, total dry matter biomass, shoot dry weight and root dry weight of strangle wort rhizomes decreased at 96 hours of waterlogged stress compared to the control by 63, 70, 59, 98 and 74 percent, respectively. Also, in second experiment, buried rhizomes of this weed with a length of 5 cm at a depth of 15 cm were not able to produce new seedlings.
Conclusion: According to these results, for proper management of this weed, highly contaminated areas in the field should be identified (especially in sugarcane fallow fields because at this time there is no weed control limitation). Then, the weed should be turned it into pieces smaller than 5 cm with plowing tools. Also, if possible, with suitable tools, transfer rhizomes should be transferred to a depth of more than 15 cm and integrated weed control management with drought and flooding stress and burial depth with at least two times of plowing could be implemented to control weed and prevent its expansion.
Highlights:
1-Germination characteristics of strangle wort seedlings under burial depths and flooding stress were evaluated.
2-The effect of burial depth and flooding stress on control and management of strangle wort was examined.
3-Precise determination of weed biology and weed germination behavior will lead to proper execution of weed control program.
Introduction: In Iran, the majority of research has been done on the depth of burial on crops and the effect of these factors on weeds resulted from seeds and rhziomes of seedlings has been less studied. Strangle Wort weed is one of the most problematic weeds in sugarcane fields, orchards, especially pistachio orchards, barren lands, and roads. Thus, this study aimed to find out the effect of different levels of burial depth and flood stress on the extent and quality of seedlings resulted from its rhizomes.
Material and Methods: Two separate greenhouse experiments based on completely randomized design with four replications were conducted in the experimental farm of Sugarcane Research Institute of Khuzestan province at 2014-2015 growing season. Flooding stress treatment included 7 levels of flooding stress (4, 8, 16, 24, 48, 72, and 96 flooding hours) and 6 levels of seed burial (1, 3, 5, 7, 10, and 15 cm) and rhizome burial depth treatment included 7 levels (1, 3, 5, 7, 10, and cm 15).
Results: With increasing levels of flood stress, all studied traits including root length, stem height, total dry matter biomass, shoot dry weight and root dry weight of strangle wort rhizomes decreased at 96 hours of waterlogged stress compared to the control by 63, 70, 59, 98 and 74 percent, respectively. Also, in second experiment, buried rhizomes of this weed with a length of 5 cm at a depth of 15 cm were not able to produce new seedlings.
Conclusion: According to these results, for proper management of this weed, highly contaminated areas in the field should be identified (especially in sugarcane fallow fields because at this time there is no weed control limitation). Then, the weed should be turned it into pieces smaller than 5 cm with plowing tools. Also, if possible, with suitable tools, transfer rhizomes should be transferred to a depth of more than 15 cm and integrated weed control management with drought and flooding stress and burial depth with at least two times of plowing could be implemented to control weed and prevent its expansion.
Highlights:
1-Germination characteristics of strangle wort seedlings under burial depths and flooding stress were evaluated.
2-The effect of burial depth and flooding stress on control and management of strangle wort was examined.
3-Precise determination of weed biology and weed germination behavior will lead to proper execution of weed control program.
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 (3-2024)
Volume 10, Issue 2 (3-2024)
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.
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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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