Comparison of Land Suitability Methods for Estimating Quantity of Maize Yield in Calcareous Soils

References

• Al-Taani, A., A.-H. Y, and I. Farhan. 2021. Land suitability evaluation for agricultural use using GIS and remote sensing techniques: The case study of Ma’an governorate, Jordan. Egyptian Journal of Remote Sensing and Space Science 24 (1):109–17. doi:10.1016/j.ejrs.2020.01.001.
   Web of Science ®Google Scholar
• Amirian Chekan, A., F. Sarmadiyan, A. Heydari, M. Omid, J. Mohammadi, and I. Odeh. 2012. Performance Assessment of Fuzzy Integrals as Aggregation Operators for Soil Suitability Analysis (case study: Silakhor plain of Lorestan Province. Journal of Range and Watershed Management 65 (3):301–14. doi:10.22059/jrwm.2012.30019.
   Google Scholar
• Azadi, A., J. Baninemeh, and S. A. Seyed Jalali. 2021. Land suitability assessment for wheat in some saline lands in the south of Khuzestan Province. Iranian Journal of Soil Research 35 (3):217–34. doi:10.22092/IJSR.2021.355514.623.
   Google Scholar
• Azadi, A., S. A. SeyedJalali, and M. N. Navidi. 2023. Assessment of land suitability for sugarcane cultivation using TOPSIS and Parametric Methods in Southwestern Iran. Eurasian Soil Science 12:1–2. doi:10.1134/S1064229322602268.
   Google Scholar
• Bagheri Bodaghabadi, M. 2020. Assessment of corrected land index in land suitability evaluation and adjusting its functions. Journal of Water and Soil 34 (6):961–72. doi:10.22067/JSW.V34I6.86309.
   Google Scholar
• Bagherzadeh, A., and A. Gholizadeh. 2016. Modeling land suitability evaluation for wheat production by parametric and TOPSIS approaches using GIS, northeast of Iran. Modeling Earth Systems and Environment 2 (126). doi:10.1007/s40808-016-0177-8.
   PubMedGoogle Scholar
• Bagherzadeh, A., and A. Gholizadeh. 2017. Parametric-based neural networks and TOPSIS modeling in land suitability evaluation for alfalfa production using GIS. Modeling Earth Systems and Environment 3 (2):1–11. doi:10.1007/s40808-016-0263-y.
   Google Scholar
• Boyer, J. S., R. A. James, R. Munns, T. A. Condon, and J. B. Passioura. 2008. Osmotic adjustment leads to anomalously low estimates of relative water content in wheat and barley. Functional Plant Biology 35 (11):1172–82. doi:10.1071/FP08157.
   PubMed Web of Science ®Google Scholar
• Charles, J., J. Godfray, J. R. Beddington, I. R. Crute, L. Haddad, D. Lawrence, J. F. Muir, J. Pretty, S. Robinson, S. M. Thomas, et al. 2010. Food security: The challenge of feeding 9 billion people. Science (Washington, DC) 327 (5967):812–18. doi:10.1126/science.1185383.
   PubMed Web of Science ®Google Scholar
• Diallo, M. D., S. A. Wood, A. Diallo, M. Mahatma-Saleh, O. Ndiaye, A. K. Tine, T. Ngamb, M. Guisse, S. Seck, A. Diop, et al. 2016. Soil suitability for the production of rice, groundnut, and cassava in the peri-urban Niayes zone, Senegal. Soil and Tillage Research 155:412–20. doi:10.1016/j.still.2015.09.009.
   Web of Science ®Google Scholar
• Di Paola, A., L. Caporaso, F. Di Paola, A. Bombelli, I. Vasenev, O. V. Nesterova, S. Castaldi, and R. Valentini. 2018. The expansion of wheat thermal suitability of Russia in response to climate change. Land Use Policy 78:70–77. doi:10.1016/j.landusepol.2018.06.035.
   Web of Science ®Google Scholar
• El Baroudy, A. A. 2016. Mapping and evaluating land suitability using a GIS-based model. Catena 140:96–104. doi:10.1016/j.catena.2015.12.010.
   Web of Science ®Google Scholar
• Eskandari, M., A. Zeinadini, J. Seyed mohammadi, and M. N. Navidi. 2023. Estimating quantity of date yield using soil properties by regression and artificial neural network. Communications in Soil Science and Plant Analysis 54 (1):36–47. doi:10.1080/00103624.2022.2109661.
   Web of Science ®Google Scholar
• FAO. 1976. A framework for land evaluation. In FAO soils bulletin no, Vol. 32, 94P. Rome: FAO.
   Google Scholar
• Fathi, F., A. Sheikhzeinoddin, and R. Talebnejad. 2020. Environmental and economic risk management of seed maize production in Iran. Journal of Cleaner Production 258:120772. doi:10.1016/j.jclepro.2020.120772.
   Web of Science ®Google Scholar
• Gao, Y., A. Zhang, Y. Yue, J. Wang, and P. Su. 2021. Predicting shifts in land suitability for maize cultivation worldwide due to climate change: A modeling approach. The Land 10 (3):295. doi:10.3390/land10030295.
   Web of Science ®Google Scholar
• Habibie, M. I., R. Noguchi, M. Shusuke, and T. Ahamed. 2019. Land suitability analysis for maize production in Indonesia using satellite remote sensing and GIS-based multi criteria decision support system. Geo Journal 86:777–807. doi:10.1007/s10708-019-10091-5.
   Google Scholar
• Homaee, M., C. Dirksen, 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. doi:10.1016/S0378-3774(02)00072-0.
   Web of Science ®Google Scholar
• Jafarzadeh, A. A., and G. Abbasi. 2006. Qualitative land suitability evaluation for the growth of onion, potato, maize and alfalfa on soils of the Khalatpushan research station. Biologia,Bratislava 61 (S19):349–52. doi:10.2478/s11756-006-0187-5.
   Google Scholar
• Khiddir, S. M. 1986. A statistical approach in the use of parametric systems applied to the FAO framework for land evaluation (Doctoral dissertation, Ph.D. Thesis. State University Ghent).
   Google Scholar
• Mandal, D. K., N. C. Kandare, C. Mandal, and O. Challa. 2002. Assessment of quantitative land evaluation methods and suitability mapping for cotton growing soils of Nagpur district. Journal of the Indian Society of Soil Science 50 (1):74–80.
   Google Scholar
• McKenzie, N., M. Grundy, R. Webster, and A. Ringrose-Voase. 2008. Guideline for surveying soil and land resources, 557. CSIRO Publishing.
   Google Scholar
• Mehrjardi, R. T., K. Nabiollahi, L. Rasoli, R. Kerry, and T. H. Scholten. 2020. Land suitability assessment and agricultural production sustainability using machine learning models. Agronomy 10 (4):573. doi:10.3390/agronomy10040573.
   Google Scholar
• Mendas, A., and A. Delali. 2012. Integration of Multi Criteria Decision Analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria. Computers and Electronics in Agriculture 83:117–26. doi:10.1016/j.compag.2012.02.003.
   Web of Science ®Google Scholar
• Mohammadi, S., and M. Maysami. 2021. Energy consumption pattern for corn production in Iran. Agricultural Mechanization 6 (1):49–55. doi:10.22034/JAM.2021.13121.
   Google Scholar
• Pakpour Rabati, A. P., A. A. Jafarzadeh, F. Shahbazi, S. Rezapour, and H. R. Momtaz. 2012. Qualitative and quantitative land suitability evaluation for sunflower and maize in the northwest of Iran.Arch. Archives of Agronomy and Soil Science 58 (11):1229–42. doi:10.1080/03650340.2011.579597.
   Web of Science ®Google Scholar
• Pilevar, A. R., H. R. Matinfar, A. Sohrabi, and F. Sarmadian. 2020. Integrated fuzzy, AHP and GIS techniques for land suitability assessment in semi-arid regions for wheat and maize farming. Ecological Indicators 110:105887. doi:10.1016/j.ecolind.2019.105887.
   Web of Science ®Google Scholar
• Schmidhuber, J., and F. N. Tubiello. 2007. Global food security under climate change. Proceedings of the National Academy. Sciences USA 104 (50):19703–08. doi:10.1073/pnas.0701976104.
   PubMed Web of Science ®Google Scholar
• Servati, M., H. Momtaz, B. Zali Vargahan, and H. Mohammadi. 2016. Performance evaluation of corrected land indices to determine the potential of maize production using FAO Method.Applied soil research. 3 (1):65–77.
   Google Scholar
• Seyed Jalali, S., M. Eskandari, A. Zeinadini Meymand, M. Z. Navidi, G. Azadi, and A. Khosravi Nejad. 2023. Investigating the effect of soil properties on yield and modifying the crop requirements table of maize. Water and Soil Science 33 (2):151–65. doi:10.22034/WS.2021.46940.2422.
   Google Scholar
• Seyed Jalali, S., F. Sarmadian, and M. Shorafa. 2014. Comparison of corrected and uncorrected land indices in Parametric method of land suitability Evaluation. Iranian. Journal of Soil Research 28 (1):127–41. doi:10.22092/IJSR.2014.120157.
   Google Scholar
• Seyed Jalali, S., A. Zeinadini, M. N. Navidi, and Z. Mohammad Esmail. 2019. Field crops Requirements. In Soil and Water Research Institute. Karaj. IRAN.
   Google Scholar
• Seyed mohammadi, J., F. Sarmadian, A. Jafarzadeh, M. A. Ghorbani, and F. Shahbazi. 2018. Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma 310:178–90. doi:10.1016/j.geoderma.2017.09.012.
   Web of Science ®Google Scholar
• Sheikhzeinoddin, A., and F. Fathi. 2021. Management of maize sustainable production in Iran: A social benefits approach. Agricultural Economics Research 13 (1):63–87.
   Google Scholar
• Soil Survey Staff. 2014a. Kellogg Soil survey laboratory methods manual. Soil Survey Investigations Report No. 42, Version 5. R. Burt and Soil Survey Staff (ed.). United States Department of Agriculture, Natural Resources Conservation Service.
   Google Scholar
• Soil Survey Staff. 2014b. Keys to Soil, Taxonomy. 12th ed., United States Department of Agriculture, National Soil Survey Center, Natural Resources Conservation Service.
   Google Scholar
• Sposito, C. 2016. The chemistry of. Soils. 3rd ed. 272. Oxford University Press.
   Google Scholar
• Storie, R. E. 1978. Rating soils for agricultural, forest and grazing use. International congress of soil science 1:336–39.
   Google Scholar
• Sys, C., T. E. VanRans, J. Debaveye, and F. Beernaert. 1993. Land evaluation, part III, crop requirements. Brussels, Belgium: General Administration for Development Cooperation Place.
   Google Scholar
• Sys, C., E. Van Ranset, and J. Debaveye. 1991a. Land evaluation, part I, principle in land evaluation and crop production calculation. Ghent, Belgium: international Training Center for Post Graduate Soil Scientists, Ghent Univercity.
   Google Scholar
• Sys, C., E. Van Ranst, and J. Debaveye. 1991b. Land evaluation, part II. Methods in land Evaluation.International Training center for post graduate soil scientists, 247. Ghent: Ghent University.
   Google Scholar
• Taghizadeh, Z., A. Jafarzadeh, and F. Shahbazi. 2011. Comparison of qualitative land evaluation for wheat, sunflower and corn with FAO and microlysis systems at Kirkj Research Station. In Proceedings of the 12th Iranian Congress of Soil Science on September 12-4, 51–55. Tabriz: Tabriz University.
   Google Scholar
• Taghizadeh-Mehrjardi, R., K. Nabiollahi, L. Rasoli, R. Kerry, and T. Scholten. 2020. Land suitability assessment and agricultural production sustainability using machine learning models. Agronomy 10 (4):573. doi:10.3390/agronomy10040573.
   Google Scholar
• Tercan, E., and M. A. Dereli. 2020. Development of a land suitability model for citrus cultivation using GIS and multi-criteria assessment techniques in Antalya province of Turkey. Ecological Indicators 117:106549. doi:10.1016/j.ecolind.2020.106549.
   Web of Science ®Google Scholar
• Van Niekerk, A. 2010. A comparison of land unit delineation techniques for land evaluation in the Western Cape, South Africa. Land Use Policy 27 (3):937–45. doi:10.1016/j.landusepol.2009.12.007.
   Web of Science ®Google Scholar
• Vasu, D., R. Srivastava, N. G. Patil, P. Tiwary, P. Chandran, and S. Kumar Singh. 2018. A comparative assessment of land suitability evaluation methods for agricultural land use planning at village level. Land Use Policy 79:146–63. doi:10.1016/j.landusepol.2018.08.007.
   Web of Science ®Google Scholar
• Zarei, G., M. Homaee, and A. Liaghat. 2009. Modeling transient evaporation from descending shallow groundwater table based on Brooks–Corey retention function. Water Resources Management 23 (14):2867–2876.‏ doi:10.1007/s11269-009-9413-6.
   Web of Science ®Google Scholar