Iranian Journal of Seed Research

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:

1. Calculating D50 in cottonseeds, using different methods.
2. Using nonlinear regression models to calculate D50 in cottonseeds.
3. Developing a proper method which is more accurate, and better lends itself to calculating D50 of cottonseeds.

Extended Abstract
Introduction: Priming is one of the most commonly used seed enhancement techniques. Events such as increased synthesis of nucleic acids, activation of repair processes, increased respiratory activity, and improved antioxidant capacity during priming lead to advanced metabolism in seeds. The most important effects of priming include increased percentage, speed and uniformity of germination and emergence. However, the longevity of primed seeds in storage is the major concern for researchers as it restricts widespread use of this technique. Some researchers believe that priming reduces the storage capacity of seeds, while others have reported increased seed shelf life after using priming treatments. Therefore, this study sought to investigate the effects of priming on the storage capacity of the seeds of canola cultivars under different storage conditions.
Material and Methods: In this study, the effects of priming on the shelf life of seeds of three canola cultivars including Dk-xpower, Traper and Hayola50 were investigated. For this purpose, the seeds were first treated with hydropriming and osmopriming methods. Then primed and control seeds with 6, 9, 12 and 15% moisture content were stored for 8 months at 15, 25, 35 and 45 °C. Sampling from different seed treatments was carried out at intervals of 1 to 30 days to assess germination. Finally, by fitting a three-parameter logistic model to cumulative germination data versus the day after storage, the time to germination loss to 50% was calculated and used to compare seed storage behavior between the treatments.
Results: The results showed that the storage behavior of canola seed varies greatly depending on the cultivar, and each cultivar showed a distinct behavior. Priming effects on the shelf life of seeds were different depending on the storage conditions, cultivars and also the priming methods. Comparison of the effects of priming on the seeds’ shelf life under different storage conditions showed that priming treatments were more efficient under higher seed moisture content and storage temperatures than those with lower seed moisture content and storage temperatures. In addition, priming treatments in Dk-xpower cultivar often increased the seeds’ shelf life. However, in the Traper and Hayola 50 cultivars, hydropriming often improved the seeds’ shelf life, and in contrast to osmopriming, it led to a decrease in the shelf life of the seeds.
Conclusion: Based on the results of this study, it was shown that priming effects on canola seed viability can be a function of various factors such as cultivar, storage conditions, and also the type of priming treatment. Moreover, in this study, hydropriming often increased seed longevity whereas osmopriming often increased the deterioration rate and reduced seed longevity.
 
 
Highlights:

1. Seed storage behavior of canola cultivars was compared under natural storage conditions.
2. Priming effects on seed longevity of canola cultivars was investigated under different storage conditions.

Extended Abstract
Introduction: Seeds, like other materials, are hygroscopic and exchange moisture with their surroundings. The changes in the moisture of seeds during storage depend on their hygroscopic nature and this feature plays an important role in determining the seed quality and longevity. Furthermore, studying the hygroscopic characteristics if seeds can be useful in seed storage studies as well as in commercial applications such as drying and seeds processing. Therefore, in this study, the relationship between seed moisture content and relative humidity in seed of rapeseed cultivars was studied.
Material and Methods: In this study, the relationship between the ambient relative humidity and seed moisture content of three rapeseed cultivars at 10, 20 and 30 °C was investigated using hygroscopic equilibrium curves. Therefore, water desorption and absorption curves were studied separately. Water absorption and desorption curves were obtained by drying the seeds at 1% relative humidity and seed hydration at 100% relative humidity, respectively, followed by transferring the seeds to different relative humidities at different temperatures and finally determining the equilibrium moisture content of the seeds. It should be noted that glycerol and sulfuric acid solutions were used to creation different relative humidity. Finally, the relationship between seeds moisture content against the relative humidity was quantified by fitting the D’Arcy-Watt equation.
Results: The results indicated that the seeds moisture content varied in cultivars and temperatures at different relative humidities. Also, there was a difference between water desorption and absorption curves in all cultivars and temperatures; desorption curves were generally higher than water absorption curves. The greatest difference among the cultivars regarding seed moisture content was observed at 100% relative humidity, and this difference was less severe at lower relative humidities. Also, the highest seed moisture content of rapeseed cultivars was observed at 20 °C and 100% relative humidity, and the lowest seed moisture content was recorded at 30 °C and 1% relative humidity.
Conclusions: According to the results, it was found that the relationship between seed moisture content and relative humidity followed a sigmoidal function, and this relationship would also vary depending on cultivar and temperature. There was also a difference between the adsorption and desorption curves, which is called "hysteresis", and showed that the seed moisture content at a constant relative humidity was generally higher in the state of dehydration compared with that in the state of hydration. Due to this event, desorption curve is situated higher than the absorption curve.

Highlights:

1. Response to hygroscopic equilibrium curves in seeds of different rapeseed cultivars was compared.
2. Sulfuric acid and glycerol solutions were used to create different relative humidity.

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.

Extended Abstract
Introduction: Seeds need successful germination at the optimal time and conditions to survive. Sometimes, even in the best environmental and genetic conditions of the seed, they do not germinate or germinate with a delay, which are called dormant seeds. Seed dormancy can have positive effects on avoiding adverse conditions and ensuring survival in the environment. However, dormancy in crop plants reduces emergence and yield by preventing germination. A combination of environmental and seed genetic factors are involved in seed dormancy formation. In general, seed dormancy includes: physical dormancy, physiological dormancy, morphological dormancy, morphophysiological dormancy and combinational dormancy, and physical / chemical scarification treatments, hot and cold stratification, leaching, hormonal treatments, after-ripening, light and combination treatments can be used to eliminate dormancy depending on its type. Therefore, in this study, using domestic studies conducted in the field of seed dormancy in different plant species, identification of dormancy in different plant species and its types have been discussed, and general and practical information in this regard has been provided.
Materials and Methods: In this study, 168 reports published on 250 plant species in the last 20 years, which were published in the seed dormancy of medicinal plants, weeds, rangelands, ornamentals and crops were investigated. Then, the percentage of plants studied and their families, as well as the share of different types of seed dormancy and appropriate treatments to for its eliminate were determined.
Results: Among the plant species studied, the most freuqent type of dormancy was related to physiological dormancy (50%), followed by physical dormancy, combinational dormancy, morphophysiological dormancy and the lowest share of dormancy in the studied plant species was related to morphological dormancy (1.61%). The most effective treatments to eliminate physiological dormancy were the use of cold stratification, gibberellic acid, and potassium nitrate. Also, the most effective treatments for the removal of physical dormancy were the use of physical / mechanical scarification treatments, chemical scarification and potassium nitrate treatment. According to the results, temperature treatments and then gibberellic acid and potassium nitrate treatments are recommendedt eliminate morphological dormancy. To eliminate morphophysiological dormancy, it is recommended to use treatments to maturate differentiated small or undifferentiated seeds (removal of morphological dormancy) as well as treatments to counteract the germination inhibitory factors or to compensate the were applied the most to eliminate morphophysiological dormancy.
Conclusion: By identifying the type of dormancy and applying the appropriate treatments, the germination of economical and valuable plants can be improved.

Highlights:
1- Dormancy types in native plant species of Iran through the information of domestic studies was investigated and a comprehensive report on seed dormancy was presented for the first time.
2- General and practical information about seed dormancy, effective factors and methods of dormancy elimination was reviewed in a practical way.

Extended Abstract
Introduction: The different species of Amaranthus species are among the most important damaging weeds in the world. Due to the importance of studying the effect of management factors on seed dynamics of different weed species, this experiment aimed to investigate the effect of burial depth and high temperatures on the seed dynamic of different species of Amaranthus in Golestan province including white pigweed (A. albus), prostrate pigweed (A. belitoides), hybrid Amaranthus (A. chlorostachys), redroot pigweed (A. retrofelexus) and green Amaranthus (A. viridis) were performed.
Materials and Methods: This research was conducted on five amaranthus species of white pigweed, prostrate pigweed, hybrid Amaranthus, redroot pigweed, and green Amaranthus at the seed laboratory and greenhouse of Gorgan University of Agricultural Sciences and Natural Resources. In the first experiment, seed emergence of different species of Amaranthus was studied in eight burial depths including 0, 1, 2, 3, 4, 5, 7, and 10 cm. In the second experiment, seeds were exposed to 50, 60, 70, 80, 90, 100, and 110 °C temperatures for 5, 10, and 15 minutes
Results: All seeds of A. blitoides and A. viridis germinated in the topsoil (zero depth); But, in A. albus, A. retroflexus, A. chlorostachys, 93%, 83%, and 3% of the seeds were emergence at the soil surface, respectively. By increasing the burial depth to one centimeter, the percentage of seeds emergence in different species of Amaranthus decreased significantly and was negligible at ≥ 2 cm depth. Germination test performed on retrieved seeds showed that zero to 16% of the seeds were able to germinate in petri dish, and most of the non-germinated seeds were viable. In all species except for A. chlorostachys high temperatures reduced the germination percentage.
Conclusion: Due to the reduction of seed germination percentage of different species of Amaranthus from a depth of more than one centimeter of soil, it seems that the use of conservation and conventional tillage methods has a good potential to reduce infestation of fields by these weeds. Also, although high temperatures reduce weed infestation in fields, they do not have a significant effect on depleting the seed bank of these species.

Highlights:
1- Seed dynamics of different species of Amaranthus were affected by burial depth and high temperature
2- Deep burial of seeds of different species of Amaranthus causes the stability of their seeds in the soil seed bank.

Extended abstract
Introduction: In seed research, germination percentage data is the result of counting and has a binomial distribution, and therefore, seed researchers use data transformation, especially square root transformation, to stabilize the variance and normalize the data before performing analysis of variance and comparison of treatments. Despite the use of data transformation, this method has fundamental issues in the structure that misleads the test results. Therefore, it is important to introduce and replace a method that preserves the research assumptions and provides acceptable results for a researcher without using data transformation. The use of generalized linear model is an alternative method for analyzing germination data with binomial distribution. In this research, the generalized linear model will be introduced first, and then by using simulated and real germination data, the efficiency of this method will be illustrated.
Materials and Methods: In this research, first, the simulated data was generated by the Monte Carlo method. Based on the simulated data, the significance level and the power of test of generalized linear model were computed. Then the data related to three experiments including the effect of acidity on the germination of wheat varieties, the effect of water stress and salinity on the germination of yellow sweet clover seeds, and the effect of alternating temperature on the germination of three Lavender populations were used and the results of the generalized linear model were compared with the square root transformation method based on the data of three experiments.
Results: The simulation results showed that the generalized linear model has a high efficiency to preserve the predetermined significance level and a high power in detecting significant differences in germination of treatments. Moreover, the results of the comparison of the generalized linear model with the square root transformation method illustrated that the generalized linear model had a higher capability to detect significant differences between various treatments, especially in the treatments with unequal seeds in the Petri dish, and in the treatments in which the square root transformation method resulted no significant difference among treatments, the generalized linear method showed a significant difference.
Conclusions: Generally, the results of this research demonstrated that the generalized linear model can be used as an alternative method of square root transformation in studies on the germination percentage of seeds with binomial distribution, without encountering the problems of square root transformation method. Moreover, comparing to the square root transformation, this model outperforms to detect significant differences in germination of treatments with fixed and different seeds.

Highlights: