evaluation of least limiting water range by vegetative and physiological parameters of pistachio, cv. sarakhsi, seedlings

continuous availability of soil water is an important factor for plant growth. both lack of adequate access to water in soils, or adequate oxygen in saturated soils, may reduce or even stop plant growth. to study the behavior of pistachio seedling at various moisture levels and to determine non-limiting water range for its growth, a greenhouse experiment with a completely randomized design was conducted at two levels of bulk density (bd) i.e. 1.5 and 1.8 g cm-3, six moisture levels for bd 1.5 g cm-3 (33-43%, 25-33%, 19-25%, 14-19%, 11-14%, and 7-11% on volume basis) and bd level of 1.8 g cm-3 (27-33%, 23-27%, 19-23%, 15-19%, 13-15%, and 8-13% v/v), with three replications. after transferring the pistachio cv. sarakhsi seedlings (pistachio vera l.) into soil cylinders and their establishment, six different volumetric water contents for each bd level were applied. stomatal conductance of the third mature leaf, proline content, leaf relative water content (rwc) and leaf area were determined. the effect of moisture levels on all growth parameters were significant (p<0.01). with bulk density of 1.5 g cm-3, the seedlings experienced vegetative and physiological limitations in the range of 7 to 14 percent volumetric water content, thus, non-limiting water range for pistachio seedling at this bd level ranged from 14 to 43 percent v/v. in the compacted treatment (bd of 1.8 g cm-3), the vegetative growth and physiological activities suffered limitations within the range of 8-19 percent water content due to moisture deficit, and, in the range of 23-32, were retarded due to soil poor aeration. also, non-limiting water range at this bd ranged from 19-23 percent water content. the least limiting water range predicted from dasilva et al. model at the two bdof 1.5 and 1.8 g cm-3 were 11- 25% and 20- 22 percent, respectively. the differences between the predicted range and the range obtained based on the seedling response implies the need for the calibration of the predicting model for each particular soil and plant.