Evaluating Water Uptake Functions under Simultaneous Salinity and Water Stress Conditions in Cherry Tomato (Solanum lycopersicum ) | ||
| پژوهش آب در کشاورزی | ||
| Article 8, Volume 32, Issue 2, August 2018, Pages 247-265 PDF (1.82 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/jwra.2018.116969 | ||
| Authors | ||
| yaser hossini* 1; Javad Ramezani Moghaddam2; Mohammad Reza Nikpour3; Attieh Abdoli4 | ||
| 1Associate Professor, Moghan College of Agriculture & Natural Resources - University of Mohaghegh Ardabili. | ||
| 2Assistant Professor of Faculty of Agriculture and Natural Resources - University of Mohaghegh Ardabili - Ardabil – Iran | ||
| 3Assistant Professor of College of Agriculture and Natural Resources - University of Mohaghegh Ardabili - Ardabil – Iran | ||
| 4MSc Student of Irrigation & Drainage, University of Mohaghegh Ardabili | ||
| Abstract | ||
| Various mathematical models are available for predicting the response of plants to combined water and salinity stress and their share in water uptake. The reduction functions are classified as additive, multiplicative, and conceptual models. In this study, 6 macroscopic reduction functions, namely, Van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, Homaee and Skaggs were evaluated in a greenhouse experiment on cherry tomato, var. cherry tomato cluster. This experiment was performed based on a completely randomized design with 3 replicates and 2 levels of salinity (4 and 7 dSm-1). Water stress levels were imposed as matric potential decline during the study at 3 levels of available water depletion (40%, 50%, and 65%). The result of the study indicated that the crop response to water stress and salinity stress was incremental at 4 and 7 dSm-1 salinity levels. Among the multiplicative models, reduction functions of Dirksen model had better fit than others at 4 dSm-1 salinity level (RMSE=0.15 and ME=0.14).However, at 7 dSm-1, Van Dam (RMSE=0.017, ME=0.09) and Skaggs (RMSE=0.018, ME=0.14) had better fit to the measured data. | ||
| Keywords | ||
| Root water uptake; Soil dryness; Water salinity; Moisture stress | ||
| References | ||
11. Chaali, N., Commegna, A., Dragonetti, G., Todorovic, M., Albrizio, R., Hijazeen, D., Lamaddalena, N., and A. Coppola. 2013. Monitoring and Modeling Root-uptake Salinity Reduction Factors of a Tomato Crop under Non-Uniform Soil Salinity Distribution. Procedia Environmental Sciences. 19: 643-653. 12. Dirksen, C., and D.C. Augustijn. 1988. Root water uptake function for no uniform pressure and osmotic potentials. Agric. Abstracts. pp.188. 13. Gokceoglu, C. 2002. A fuzzy triangular chart to predict the uniaxial compressive strength of the Ankara agglomerates from their petrographic composition. Engineering Geology. 66: 39–51. 14. Finol, J., Guo, Y.K., and X.D. Jing. 2001. A rule based fuzzy model for the prediction of petrophysical rock parameters. Journal of Petroleum Science and Engineering. 29: 97–113. 15. Feddes, R.A., Kowalik, P.J., and H. Zaradny. 1978. Simulation of field water use and crop yield. Prudoc. Wageningen. 189 pp. 16. Homaee, M., Dirksen, C., and R.A. Feddes. 2002. Simulation of root water uptake. I. Non – uniform transient salinity using different macroscopic reduction functions. Agricultural Water Management. 57: 89-109. 17. Homaee, M. 1999. Root water uptake under non-uniform transient salinity and water tress.Ph.D. Thesis, Wageningen Agricultural University. 173 pp 18. Maas, E.V., and G.J. Hoffman. 1977. Crop salt tolerance Current assessment. J. Irrig. Drain. Div. Am. Soc.Civ. Eng, 103:115–134. 19. Mualem, Y. 1976. A new model predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12:513–522. 20. Karakus, M. and Tutmez. B. 2006. Fuzzy and multiple regression modeling for evaluation of intact rock strength based on point load, Schmidt hammer and sonic velocity, Rock Mech. Rock Eng. 39 (1) ,45–57. 21. Rahman, M.A., Smith, J.G., Stringer, P., and A.R. Ennos. 2011. Effect of rooting conditions on the growth and cooling ability of Pyrus calleryana. Urban Forestry & Urban Greening 10:185–192. 22. Rameshwaran, P., Tepe, A., Yazar, A., and R. Ragab. 2016. Effects of Drip-Irrigation Regimes with Saline Water on Pepper Productivity and Soil Salinity under Greenhouse Conditions. Scientia Horticulturae 199: 114-123. 23. Sepaskhah, A. R., and N. Yarami. 2010. Evaluation of macroscopic water extraction model for salinity and water stress in saffron yield production. International Journal of Plant Production.4 (3):175-186. 24. Skaggs, T.H., Van Genuchten, M.Th., Shouse, P.J., and J.A. Poss. 2006. Root uptake and transpiration: From measurements and models to sustainable irrigations. Agric. Water Manage. 86: 140–179. 25. U.S. Salinity Laboratory Staff. 1954. Diagnosis and improvement of saline and alkali soils. U.S. Dep. Agric. Handb. 26. Van Dam, J.C., Huygen, J., Wesseling, J.G., Feddes, R.A., Kabat, P., Van Walsum, P.E.V., Groenendijk, P., and C.A. Van Diepen. 1997.Theory of SWAP, version 2. Simulation of water flow, solute transport plant growth in the soil-water-atmosphere-plant environment. Report No.71. Dept. of Water Resources. Wageningen Agricultural Univ. 167 pp. 27. Van genuchten, M. Th., and S.K. Gupta. 1993. A Reassessment of the Crop Tolerance Response Function. Journal of the Indian Society of Soil Science. 41(4): 730-737. 28. Van Genuchten, M. Th. 1987. A numerical model for water and solute movement in and below the root zone. Research Report, U. S. Salinity Lab. Riverside CA. 29. Yanagawa, A., and H. Fujimaki. 2013. Tolerance of canola to drought and salinity stresses in terms of root water uptake model parameters. J. Hydrol. Hydromech. 61(1): 73–80. | ||
|
Statistics Article View: 952 PDF Download: 941 |
||
Journal management system. designed by sinaweb