Iranian Journal of Seed Research

Extended Abstract
Introduction: It is obvious that all plants adopt mechanisms to control NaCl accumulation because sodium chloride is the most soluble and most abundant salt. Binweed (Convolvulus arvensis L.) is among the ten widespread noxious weeds in the world that it is reproduced by seed, horizontal lateral root, and rhizome. Because of the extensive underground root system of the bindweed with abundant buds and established root reserves, binweed competes more tolerant than crops under salinity and drought stress. More information on morphophysiological traits of binweed under salinity conditions and comparison of salinity tolerance index between germination and seedling can also be contributed to the most effective management. In order to investigate the germination and seedling growth characteristics of binweed two experiments were conducted separately under salinity stress.
Materials and Methods: Germination experiment was done in a completely randomized design with 9 levels of salinity stresses include 0 (control), 5, 10, 15, 20, 25, 30, 35, and 40 dS.m^-1, with four replications in the lab. The seedling experiment was performed in a random complete block design consisted of five levels of salinity (tap water, 10, 20, 30, and 40 dS.m^-1) with three replications as the pot in a non-shade greenhouse of Agricultural College of Shahid Chamran University of Ahvaz.
Results: The results showed that with raising salinity, percentage germination and vigure index of seed declined, but Radicle/ Plumule ratio rose. After two weeks, in response to salinity a decrease in root and shoot characteristics of the seedling was observed. Salinity stress data were fitted to a three-parameter logistic for seedling stage showed that the salinity levels higher than 7.86 dS.m^-1 led to 50 percent reduction in tolerance index. It was found that 19.84 dS.m^-1 caused 50% decrease in the tolerance index at germination stage. Sufficient tolerance index –growth stage variation in response to salinity was found which suggests that bindweed tolerance to salinity at germination stage is about 3 times more than that of seedling stage.
Conclusions: Radicle/ plumule ratio at germination stage and root lateral branches at seedling stage increased in concentrations of up to 25  and 20 dS.m^-1, respectively. It seems the maintenance of root area and branches in response to increased salinity provide an acceptable mechanism of salinity tolerance for binweed. According to the three-parameter logistic model, the salinity tolerance of bindweed at germination and seedling stages was estimated at 20 and 8 dS.m^-1, respectively.
Keywords: Logistic model, Root lateral branches, Relative water content, Salinity tolerance index
Highlights:
1 Salinity tolerance of bindweed was investigated in germination and seedling growth.
2- Salinity tolerance index was compared between germination and seedling of bindweed and was introduced a proper trait which is more effective to pointing salinity tolerance.
3- The best sigmoidal model based on salinity criterion was introduced for salt tolerance index of bindweed.

Extended Abstract
Introduction: Seed germination is one of the most important factors which determine the success of failure of crop establishment. In the absence of other environmental limiting factors such as moisture, temperature would determine the rate and overall seed germination. This research was conducted to investigate the effect of temperature regimes on seed germination, quantify the response of germination rate to temperature and determine the cardinal temperatures for different germination percentiles in Solanum lycopersicom.
Materials and Methods: Two-way factorial experiment including seven constant temperatures (5, 10, 15, 20, 25, 30 and 35 ^oC) and two tomato varieties (Red cherry: var. Cerasiformi and Yellow pearl: var. Yellow Pear) was conducted based on a completely randomized design arranged with thee replications at the seed technology laboratory of Agricultural Sciences and Natural Resources University of Khuzestan in 2019. Beta, segmented and dent-like functions were used to determine the relationship between germination rate and temperature. Logistic model was used to describe the suitable pattern for the germination of these two cultivars in response to each temperature level.
Results: Results of analysis of variance showed that the interaction effect of temperature and cultivar was significant on all studied traits. Results showed that respectively at temperatures of 15, 20, 25 and 30 ^oC, total seed germination for yellow pearl tomato was 93%, 96%, 95% and 86% and for red cherry tomato was 95, 98, 93 and 98 percent. There was no seed germination for both tomato varieties at 5, 10 and 35 ^oC. Based on the results of the fitted models, it was revealed that among the tested non-linear regression models, segmented model described the germination rate of the studied tomato cultivars against the temperature the best (AICc≤70, R²=0.93). Three parameters logistic functions exhibited a reasonable fit (R²=0.96) for germination time course under temperature range of 15 to 30 ^oC in both cultivars. Based on the segmented model, base, optimum and ceiling temperatures of Yellow pearl and Cherry tomato were estimated 11.25, 28.72, 35.00 ^oC and 10.97, 28.361 and 35 ^oC, respectively.
Conclusion: Both tomato cultivars exhibited sensitivity to changes in temperature. Seed germination rate and number of the germinated seeds increased at temperatures higher than base. This increase continued until the optimum temperature and then started to decline as the temperature exceeded from optimum range. Also, results obtained from the logistic function showed that Yellow pearl cultivar is more sensitive to supra-optimal temperatures compared with Cherry tomato, and germination percentage of the 97.79 to 85.09 percent as temperature reached from 25 to 30 ^oC.

Highlights:
1- The pattern of seed germination in two new tomato cultivars was investigated under temperatures regimes
2- Cardinal temperatures of two new tomato varieties was estimated using nonlinear regression models