عنوان مقاله [English]
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.
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.