Evaluating TOPSIS Method in Prioritizing Lands for Saffron Cultivation

Document Type : Research Article

Authors

• M. Eskandari ¹
• A. Zeinadini ¹
• M.N. Navidi ¹
• A. Salmanpour ²

¹ Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

² Soil and Water Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorram Abad, Iran

https://doi.org/10.22067/jsw.2022.74195.1125

Abstract

Introduction
Saffron, which its cultivation is compatible with the arid and semi-arid climate of Iran, is one of the most valuable agricultural products in the world. Therefore, the cultivation of this crop in different parts of the country has been enormously developed in recent years. More than 95% of the world production of this precious product is allocated to Iran, which is mainly located in the two provinces of Khorasan Razavi and Southern Khorasan. The objective of this study was to determine the priority of lands for saffron cultivation by using TOPSIS method. Furthermore, in this study, TOPSIS, which is the second most widely used approach among multi-criteria decision making methods, was compared with the conventional parametric one to assess the land suitability for saffron production.
Materials and Methods
To achieve the objective of this study, 135 saffron farms in Khorasan Razavi, Southern Khorasan, Fars, Markazi and Kerman provinces were selected. In each farm, one pedon was dug and studied in detail. Soil samples were collected from different horizons of the pedons and taken to the laboratory for the designated physicochemical analyses. The average quantity of saffron yield in the last three years was recorded for each study point. The selected areas did not have climatic restrictions for saffron cultivation. For this purpose, in addition to local experience, the climate suitability index was calculated using the saffron climatic requirement table by its phenological period in each region. The effective soil criteria conditioned on the saffron yield were obtained using statistical analyses. By constructing a decision matrix and normalizing it, weighting the criteria by ranking order method and constructing a weighted matrix, determining the positive and negative ideal and then calculating the relative proximity of each alternative to the positive ideal, the preference of each alternative by TOPSIS method for saffron cultivation was determined. Then, the prioritization of alternatives was compared with the actual yield of saffron. Soil suitability index was also calculated using the table of soil and landscape requirements for saffron, and then compared with actual yield. Finally, the two schemes were validated and compared with each other.
Results and Discussion
The climate suitability index for saffron cultivation in the five studied areas indicated that the climate conditions in all areas were relatively similar. Consequently, soil properties can be considered as the only factors affecting the priority of lands for saffron cultivation in the studied areas. The results further revealed that three variables of lime content, salinity and exchangeable sodium percentage of soils under saffron cultivation in the country were higher than the critical level for saffron production. Therefore, these three variables are considered as the most important soil properties affecting the saffron yield. The order of weights assigned to the variables included salinity, exchangeable sodium percentage, lime, gravel, gypsum, organic carbon and soil reaction. Comparison of the order of priority of 135 options by TOPSIS with the actual yield of saffron showed an acceptable accuracy (R² = 0.92) for this method. The soil index calculated by the parametric square root method for 135 soil profiles was also compared with the actual yield. The coefficient of determination obtained in this case was about 0.9, showing that TOPSIS was able to determine the suitability of lands for saffron cultivation better than the parametric method. Due to the ability of TOPSIS to evaluate a large number of evaluation criteria, this method is superior to the parametric method, which can consider a maximum of eight criteria in estimating the index.
Conclusion
The outcome of this study showed a high accuracy of TOPSIS method in determining land suitability for development of saffron cultivation. This method is well able to use a large number of criteria that have negative or positive effects on the priority of alternatives. Furthermore, depending on the conditions of the decision making problem, one of the methods of weighting the criteria can be employed and combined with the TOPSIS method. The high accuracy of this method can be attributed to the use of mathematical relationships and matrices, data standardization by Euclidean soft method, and the nature of comparing both distances from the positive and negative ideals.

Keywords

• Crop development
• Land suitability
• Multi-criteria decision making
• Yield

20.1001.1.20084757.1401.36.2.6.0

Main Subjects

• Soil science

References

1. Asadi Kangarshahi, AkhlaghiAmiriN., and Samar M. 2015. Possibility of Using Chlorosis Degree and Active Iron (Fe²⁺) to Assess the Tolerance of Some Citrus Rootstocks to Calcareous Soils. Iranian Journal of Soil Research 29(3): 296-284. (In Persian with English abstract). https://dx.doi.org/10.22092/ijsr.2015.103433.
2. Bagherzadeh A., and Gholizadeh A. 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). https://doi.org/10.1007/s40808-016-0177-8.
3. Bagherzadeh A., and Gholizadeh A. 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. https://doi.org/10.1007/s40808-016-0263-y.
4. Celikbilek Y., and Tuysuz F. 2020. An in-depth review of theory of the TOPSIS method: An experimental analysis. Journal of Management Analytics 7(2): 281-300. https://doi.org/10.1080/23270012.2020.1748528.
5. Eskandari M., Homaee M., Mahmodi S., and Pazira E. 2013. A New Landfill Siting Method Based on Land Classification Maps and GIS. Environmental Sciences 11(2): 121-132. (In Persian with English abstract). https://envs.sbu.ac.ir/article_95068.html.
6. Eskandari M., Homaeei M., and Mahmoodi S. 2013. Optimized Approach for MSW Landfill Siting Using MCDA and GIS. Environmental Sciences 11(3): 41-54. (In Persian with English abstract). https://envs.sbu.ac.ir/article_97284.html.
7. 1976. A Framework for Land Evaluation. FAO Soils Bulletin No. 32. Rome.
8. Fattahi M., Mahdavi R., Rezaei M., and Esmaeilpour Y. 2021. Determination of optimal cultivation pattern of medicinal plants using AHP-TOPSIS hybrid model (Case study: Qom province). Iranian Journal of Medicinal and Aromatic Plants Research 36(6): 885-897. (In Persian with English abstract). https://doi.org/10.22092/ijmapr.2021.342346.2749.
9. Ghiasvand A. 2016. Application of statistics and SPSS software in data analysis. 4th Ed. Motefakkeran Publications. (In Persian)
10. Kazemi , and Akinci H. 2018. A land use suitability model for rainfed farming by Multi-criteria Decision-making Analysis (MCDA) and Geographic Information System (GIS). Ecological Engineering 116: 1-6. https://doi.org/10.1016/j.ecoleng.2018.02.021.
11. Mohammadi 2006. Pedometry: Classical Statistics. Volume One, Pelk Publications, Tehran. (In Persian)
12. Navidi M.N. Design and preparation of land suitability evaluation software for field and orchard crops of the country.Soil and Water Research Institute. (In Persian with English abstract). https://nlss.ir/Home/AboutUs.
13. Pilevar A.R., Matinfar H.R., Sohrabi A., and Sarmadian F. 2020. Integrated fuzzy, AHP and GIS techniques for land suitability assessment in semi-arid regions for wheat and maize farming, Ecological Indicators (110): 105887. https://doi.org/10.1016/j.ecolind.2019.105887.
14. Rooshanali M. 2012. Land suitability evaluation model based on the elements of the climate for the cultivation of rapeseed TOPSIS: A Case Study of Mazandaran province. Journal of Urban Ecology Researches 3(6): 67-80. (In Persian with English abstract). https://grup.journals.pnu.ac.ir/article_1119.html?lang=en.
15. Sarmadian F., and Ghavami M. 2020. Land Suitability Evaluation Using TOPSIS Method and Its Comparison with Parametric Methods for Maize Production in Part of Qazvin. Iranian Journal of Soil and Water Research 50(9): 2275-2287. (In Persian with English abstract). https://doi.org/10.22059/ijswr.2019.273788.668095.
16. SeyedJalali S.A., Dehghan R., Azadi A., Zaeinaldini Mimand A., Navidi M.N., and Mohammad Esmaeil Z. 2020. Investigation of the effect of soil factors on sugarcane growth in sugarcane cultivated lands in khuzestan and mazandaran provinces. Soil Research 34(3): 343-357. (In Persian with English abstract). https://dx.doi.org/10.22092/ijsr.2020.343172.532.
17. Seyedjalali S.A., Eskandari M., Roshani G., Navidi M., Zareian G., Zeinadini Meymand A., and Ghasemzadeh Ganjehie M. 2021. Determining Soil and Landscape Requirements of cotton for Using in Land Suitability Evaluation. Iranian Journal of Cotton Researches 9(1): 69-88. (In Persian with English abstract). https://doi.org/10.22092/ijcr.2021.352985.1162.
18. Seyedmohammadi J., Jafarzadeh A.A., Sarmadian F., Shahbazi F., and Ghorbani M.A. 2017. Comparing the Efficiency of TOPSIS, AHP and Square Root Methods in Cultivation Priority Determination for Wheat, Barley and Maize under Sprinkler Irrigation in Dasht-e-Moghan. Water and Soil Science 27(2): 45-59. (In Persian with English abstract)
19. Seyedmohammadi J., Sarmadian F., Jafarzadeh A.A., Ghorbani M.A., and Shahbazi F. 2018. Application of SAW, TOPSIS and fuzzy TOPSIS models in cultivation priority planning for maize, rapeseed and soybean crops. Geoderma 310: 178-190. https://doi.org/10.1016/j.geoderma.2017.09.012.
20. Sys C., Van Ranst E., and Debaveye I.J. 1991. Land evaluation. Part I: principles in land evaluation and crop production calculations. General Administration for Development Cooperation, Agricultural Publication-No. 7, Brussels, Belgium, p 274.
21. Tale Jenekanlou A., Karimi M., and Taleai M. 2015. Residential Land Suitability Assessment Using Fuzzy Group TOPSIS-OWA. Journal of Geomatics Science And Technology 4(4) :29-46. http://jgst.issge.ir/article-1-82-fa.html.
22. Tzeng G., and Huang J. 2011. Multiple Attribute Decision Making Methods and Applications. CRC Press, Taylor and Francis Group, A Chapman and Hall Book, Boca Raton.
23. 2012. Field Book for Describing and Sampling Soils. Version 3, Natural Resources Conservation Service, National Soil Survey Center, Lincoln, NE.
24. 2014. 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.
25. Vafabakhsh J. 2003. Finding the potential of saffron cultivation areas in Iran. Mashhad, Publications of Scientific and Industrial Research Organization of Khorasan Center. Pages 99-108. (In Persian)
26. Vafaeinejad A. 2016. Cropping Pattern Optimization by Using of TOPSIS and Genetic Algorithm Based on the Capabilities of GIS. Iranian Journal of Ecohydrology 3(1): 69-82. (In Persian with English abstract). https://dx.doi.org/10.22059/ije.2016.59191.
27. Wang P., Zhu Z., and Huang S. 2017. The use of improved TOPSIS method based on experimental design and Chebyshev regression in solving MCDM problems, Journal of Intelligent Manufacturing 28(1): 229-243. https://doi.org/10.1007/s10845-014-0973-9.
28. Zeinadini, Navidi M., Asadi Kangarshahi A., Eskandari M., Seyedjalali S., Salmanpour A., Seyedmohammadi J., Ghasemi M., Ghaffarinejad S., and Zareian G. 2021. Effect of Soil Characteristics on Yield and Preparing the Crop Requirements Table of Oranges in Selected Areas of Iran. Water and Soil, 35(3): 395-407. (In Persian with English abstract). https://doi.org/10.22067/jsw.2021.68421.1017.
29. Zeinadini A., Navidi M., Eskandari M., Seyedmohammadi J., Toomanian N., Hosseinifard S., Farajnia A., and GhasemzadehGanjehie M. 2020. Determination of Soil and Landscape Requirements of Pistachio for Use in Land Suitability Evaluation. Journal of Pistachio Science and Technology 5(9): 70-88. (In Persian with English abstract). http://pistachio.vru.ac.ir/article_119177.html?lang=en.
30. Zeinadini A., Navidi M.N,. Seyedmohammadi J,. Jafari M., Salmanpour A,. Eskandari M., Moghimi A., and Fatehi Sh. Investigating the effect of land characteristics on yield and rating of fig vegetative requirements in important cultivated areas. Iranian Journal of Horticultural Science and Technology (Accepted). (In Persian with English abstract). http://dorl.net/dor/20.1001.1.16807154.1400.22.2.8.1.
31. Zeinadini A., Navidi M.N., Eskandari M., Seyedjalali S., Seyed Mohammadi J., Moghimi A., Gasemzade Ganjehie M., Moghri A., and Pahlavanrad M. 2022. Investigation of land characteristics and preparation of soil requirements table for saffron. Saffron Agronomy and Technology 9(4): 395-408. (In Persian with English abstract). https://doi.org/10.22048/jsat.2021.286314.1426.
32. Zeinadini A., Seyedjalali S., Navidi M., Eskandari M., Seyedmohammadi J., Dialami H., Moghimi A., and Pozeshshirazi M. 2020. Preparation of soil and landscape requirements table for Date palm to use in land suitability evaluation. Journal of Water and Soil Conservation 27(5): 89-107. (In Persian with English abstract). https://doi.org/10.22069/jwsc.2021.17510.3297.
33. Zeinadini A., Toomanian N., Navidi M.N., Farajnia A., and SeyedJalali A.R. 2019. horticultural crops requierments. Soil and Water Research Institute. Karaj. 310p. (In Persian)