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Application of the thermal time model to assess the effects of priming treatments on seed germination of rice (Oryza sativa) cultivars in response to temperature
Ahmad Munir Amini, Farshid Ghaderi-Far, Dr Benjamin Torabi, Asieh Siahmargue, Hamid Reza Sadeghipour,
Volume 10, Issue 2 (3-2024)
Abstract
Extended abstract
Introduction: With regard to the ever-growing water deficit in the world, the adoption of the direct-seeded rice cultivation system has been suggested as an alternative to the transplanting method. One of the disadvantages of the direct-seeded method is low and non-uniform germination and emergence due to low seed vigor in rice. Priming is a technique which improves the rate and uniformity of seed germination under these conditions. Thus, this study aimed to investigate the effects of priming treatments on seed germination of different rice cultivars under different temperature conditions using the thermal time model.
Materials and methods: This study was conducted in 2019 at the seed research laboratory of Gorgan University of Agricultural Sciences and Natural Resources. In this experiment, germination of primed and non-primed seeds in three rice cultivars (Nada, Anam, and Tolo) was investigated under different temperatures (15, 20, 25, 30, and 35°C). The priming treatments which consisted of control, hydropriming, and osmopriming with different chemicals (potassium chloride 2%, potassium nitrate 1%, calcium chloride 4%, glycine betaine 10 ppm, salicylic acid 10 ppm, and ascorbic acid 10 ppm) were investigated under different temperatures.
Results: The results showed that priming treatments had no significant effect on the seed germination percentage of rice cultivars at different temperatures. The thermal time model based on binomial distribution fitted well to cumulative germination percentages in all priming treatments. Among the parameters of the thermal time model, the greatest priming effect was on the reduction of the thermal coefficient, followed by the reduction of the sigma coefficient, which resulted in the increased rate and uniformity of germination. Priming treatments had no significant effect on base temperature. Also, the responses of rice cultivars to seed priming treatments varied so that in Anam and Neda, priming with calcium chloride but in Tolo, hydropriming was more effective on the model parameters, especially thermal time to 50% of germination.
Conclusion: In general, priming treatments did not affect the base temperature of germination in rice cultivars, but they significantly affected the rate and uniformity of seed germination. As the latter issue is one of the main problems in the direct-seeded rice system, suitable priming treatments for each cultivar can be adopted to increase the rate and uniformity of seed germination and emergence in this system.

Highlights:
  1. The thermal time model can be used to select the appropriate priming treatment for improving seed germination components of rice cultivars.
  2. The responses of rice cultivars to different seed priming treatments were different.
  3. Priming treatments did not improve the base temperature of seed germination in rice cultivars, but they significantly affected seed germination rate and uniformity.

Quantifying and analysis of germination responses of invasive weed Western ragweed (Ambrosia psilostachya) to temperature and under different water potential conditions
Mahboubeh Shahbazi, Jafar Asghari, Behnam Kamkar, Edris Taghvaie Salimi,
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.

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