عنوان مقاله [English]
نویسنده [English]چکیده [English]
Production potential of land for human food, especially wheat supply is limited and depends on environmental factors affecting production, such as climate, soil, landscape, and management. This paper examines these factors and provides guidelines for understanding the limitations of these factors and their role in the production were also investigated. The study area were in Aghili plain of Gotvand and Mianab plain of Shooshtar in Khuzestan. The result showed that land production potential for irrigated wheat in mian ab from 933 to 6023 kg/ha and for Gotvand is 2254 to 6687 kg/ha. The main soil limiting factors in both area were salinity, alkalinity, drainage and calcium carbonate limitations. predicted yield were compared with farmer wheat yield in both areas and showed coefficient factor equal 0.80 for Gotvand and 0.77 for Shoushtar. That means model can predict farmer yield with 80 percent in Gotvand and 77 percent of accuracy for Shoushtar.The reason of higher wheat yield in Gotvand to shoushtar is because of lower salinity limitations in Gotvand area.
4. Becker-Reshef A, E. Vermote A, M. Lindeman and B. C. Justice. 2010. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sensing of Environment 114: 1312–1323.
5. Budong Q, Reinder De J, and G. Samuel. 2009. Multivariate analysis of water-related agroclimatic factors limiting spring wheat yields on the Canadian prairies. Europ. Journal. Agronomy 30: 140–150
6. Charles, J., Godfray, J., Beddington, J.R., Crute, I.R., Haddad, L., Lawrence, D., Muir, J.F., Pretty, J., Robinson, S., Thomas, S.M., and C. Toulmin. 2010. Food security: The challenge of feeding 9 billion people. Science (Washington, DC) 327: 812–818.
7. Chen, Z. X., Ren, J. Q., Zhou, Q. B., and H. J, Tang. 2008. Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China. International Journal of Applied Earth Observation and Geoinformation, 10: 403−413.[u1]
8. Chipanshi, A. C., Ripley, E. A., and R. G. Lawford. 1999. Large-scale simulation of wheat yields in a semi-arid environment using a crop-growth model. Agricultural Systems, 59: 57−66.
9. Doorenbos, J. and A. H. Kassam. Yield response to water, irrigation and drainage paper 33. FAO, Rome.
10. Doraiswamy, P. C., Moulin, S., Cook, P. W., and V., Stern. 2003. Crop yield assessment from remote sensing. Photogrammetric Engineering and Remote Sensing, 69: 665−674.
11. Food and Agricultural Organization. 1979. Report on agro-ecological zones project. Vol. 1: Methodology and result for Africa. World soil resources report No. 48, FAO, Rome.
12. Keshavarzi, A; Sarmadian, F; Heidari, A and M. Omid. 2010. Land Suitability Evaluation Using Fuzzy Continuous Classification (A Case Study: Ziaran Region). Modern Applied Science. Vol. 4, No. 7.
13. Khiddir, S. M. 1986. A statistical approach in the use of parametric systems applied to the FAO framework for land evaluation. Ph. D. Thesis, State University of Ghent, Belgium.
14. Maselli, F., and F. Rembold. 2001. Analysis of GAC NDVI data for cropland identification and yield forecasting in Mediterranean African countries. Photogrammetric Engineering and Remote Sensing, 67: 593−602.
15. Padilla, F.L.M. ., Maas. S.J., Gonz M.P., lez-Dugo., F. Mansilla, N. Rajan, Gavil, P., and J. Donguez. 2012. Monitoring regional wheat yield in Southern Spain using the GRAMI model and satellite imagery. Field Crops Research 130: 145–154
16. Pinter, P. J., Jackson, R. D., Idso, S. B., and R. J. Reginato.1981. Multidate spectral reflectances as predictors of yield in water stressed wheat and barley. International Journal of Remote Sensing, 2: 43−48.
17. Shahbazi, F., Jafarzadeh, A.A., Sarmadian, F., Neyshaboury, M.R., Oustan, Sh., Anaya- Romero, M. and D. De la Rosa.2009. Suitability of Wheat, Maize, Sugar Beet and Potato Using MicroLEIS DSS Software in Ahar Area, North-West of Iran. American-Eurasian Journal of Agricultural and Environmental suence.5 (1): 45-52,
18. Storie, R. E. 1978. Storie index soil rating (revised). Spec. publ. Div. Agric. Sci. No. 3203. University of Calif. Berkley, USA.
19. Sys, C, E, Van Ranst., And J. Debaveye. 1991. Land evaluation, Part I and II. General Admhnstration for development cooperation, Brussels.
20. Sys, C, E, Van Ranst, and J. Debaveye.1993. Land evaluation, Part III. Crop requirements. General Administration for development cooperation, Brussels.
21. Toscano, P., Ranieri, R., Matese, A. ., Vaccari, F.P., Gioli , B. A. Zaldeia, M. Silvestri , C. Ronchi,P. La Cava, J.R. Porter and F. Miglietta. 2012. Durum wheat modeling: The Delphi system, 11 years of observations in Italy. Europ. Journal of. Agronomy 43:108–118
22. Wall, L., Larocque, D., and P. M., Leger. 2007. The early explanatory power of NDVI in crop yield modeling. International Journal of Remote Sensing, 29: 2211−2225.