| چکیده انگلیسی مقاله |
Introduction Various studies have investigated the response of crops and pasture plants to water for non-saline waters and their reaction to salinity in full irrigation. A set of such studies can determine water-yield or salinity-yield relationships. However, quantitative research has been done to study the effects of salinity and drought stress. However, we are proposing perpendicular system as a new alternative to learn wheat yield under simultaneous water and salinity stresses. Materials and Methods Response of grain and straw of wheat, Back Cross Roshan 6611 cultivar, to combined effects of quantity and quality of water was traced under crossed sprinkler line source irrigation. The field area was 3232 m2 which was located in the west of Birjand city in southeast of Iran. The soil was sandy loam (=1.41 gr/cm3) and two different sources of water, normal (EC=1.5 dS/m) and saline (EC=5.5 dS/m) were adopted for two line sources, respectively. Crops located in the center of the field, were fully irrigated without any stress. While the other crops far beyond irrigation lines, were under water stress. Water salinity was differ among different points of the field and varied between 1.5 and 5.5 dS/m, based on the quantity of water received. After each irrigation procedure, the volume and salinity of water collected in 256 cans, which were placed in 2'2 square meters, were measured. At the end of the growing season, one square meter around the cans was taken to measure yield and yield components. General form of yield function for different salinities and irrigation water is Y=f (AW, EC) in which Y is the wheat yield in kg/hectare, AW is irrigation water depth during growth period in cm and EC is mean salinity of irrigation water in dS/m. Five types of production function (Linear, Cobb-Douglas, Quadratic, Laty-Dinar, and Transcendental) were evaluated using field data. Slide Write software was used for calculating R2, F-statistics, t-statistics and constant parameters of the equations. All statistics were tested at significant levels of 1% and 5%. The best function was selected based on goodness of fit and significance of factors. Results and Discussion The results showed that yield prediction of wheat and straw was better than other functions under the influence of combined conditions of drought and salinity with Cobb Douglas function. Datta et al. used second polynomial non-linear function among three linear, power and Second polynomial functions. Rosso and Baker concluded that Second polynomial function estimates the relationship between yield, salinity and water better than Maximum and Hoffman function. Kiani used transducer function for result analysis. The marginal rate of technical substitution indicated that each one of the factors can be substituted for the other one for a wide range in order to achieve equal amount of yield (grain/straw). These results are consistent with results of Rosso and Baker, Dota et al. and Letti and Dinar. Also, the results showed that in lower performances, the effect of water content on reduction of crop was higher than that of salinity. Conclusions 1-Regarding this research, reduction of grain and straw weight due to the reduction of irrigation water and increase in water salinity follows Cobb-Douglass function and outperforms other functions in predicting changes of grain and straw weight due to the effect of changes in two abovementioned factors. 2-Results showed that changes in grain and straw weights are more sensitive to changes of irrigation water than water salinity. 3-Using substitution rate curve, it is possible to substitute salinity and water content in order to achieve same yield. |