JWSS - Journal of Water and Soil Science

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Canola (Brassica napus L.) in response to salinity represents various resistances with respect to its phonologic stages. Most plants such as Canola are resistant at germination stage. However, at seedling or earlier growth stages, plants become more sensitive to salinity but their tolerance increases with age. Salt tolerance of various plants has been extensively studied however, the results have either been qualitative or expressed as average values over root zone salinity for the whole growth season. Thus, developing appropriate models for quantitative characterization of plant response to salinity at different growth stages is essential. Canola which is considered as high economic value plant was selected for this study. Two productive stages for canola are recognized as flowering and ripening. To determine the effect of salinity on canola at vegetative growth stages, a greenhouse experiment was conducted on a natural saline loamy sand soil, using salinity treatment including one non-saline water (tap water) and 8 saline waters of 3 to 17 dS.m^-1. The canola plants were irrigated with tap water before the desired stage and then salinity treatments were imposed. The Maas and Hoffman (1977), van Genuchten and Hoffman (1984), Dirksen et al., (1993), and Homaee et al., (2002b) models were used to predict relative transpiration (T_a/T_p ) and relative yield ( Y/Y_m) as a function of soil salinity. The maximum error (ME), root mean square error (RMSE), coefficient of determination (CD), modeling efficiency (EF) and coefficient of residual mass (CRM) statistics were calculated to compare the models and their efficiencies. The results indicated that the van Genuchten and Hoffman (1984) model provides best prediction at flowering stage. However the Homaee et al. (2002b) model offers better prediction at ripening growth stage.

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Phytoremediation models are important to understand the processes governing phytoremediation and the management of contaminated soils. Little effort has been made for evaluating the potential of the phytoremediation of metals based on the mathematical models. Therefore, the purpose of this study was modeling the phytoremediation of the nickel-contaminated soils. For this purpose, a model was recommended for estimating the rate of the phytoremediation of nickel from the soil by means of relative transpiration reduction and concentration of nickel in the plant functions. To evaluate the model, soil was contaminated with different levels of nickel by nickel nitrate. Then, the pots were filled with contaminated soil and Basil (ocimum tenuiflirum L.) seeds were planted. To avoid the dry tension, the pots were weighed and irrigated to the point of field capacity (FC) at short time intervals (48 hours). The plants were harvested in four times. At each harvesting stage, the relative transpiration values and nickel concentration in the soil and plant samples were measured. The performance of the model was evaluated by statistical methods such as Maximum Error, Root Mean Square Error, Coefficient of Determination, Efficiency of Model and Coefficient of Residual Mass. Results demonstrated that in the case of nickel contamination in soil, changes in the relative transpiration of Basil can be measured by the two proposed models and the linear model (R2=0.94) has a better performance compared to the nonlinear one (R2=0.84). Also the model obtained from the combination of linear function and nickel's concentration in soil has a relatively good (R=0.7) fit with the measured values of the remediation rate of nickel in soil.