Land Evaluation and Suitability
Nikrooz Bagheri; Alireza Sabzevari; Ali Rajabipour
Abstract
Introduction: One of the decision-making methods using quantitative data is multi-criteria decision-making, which helps the manager make rational decisions by considering different conflicting criteria. Planning for the optimal use of water and soil resources, in addition to their conservation, involves ...
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Introduction: One of the decision-making methods using quantitative data is multi-criteria decision-making, which helps the manager make rational decisions by considering different conflicting criteria. Planning for the optimal use of water and soil resources, in addition to their conservation, involves increasing production, income growth for farmers, and rural economic prosperity. Given the limited resources, the optimal cropping pattern should be appropriate and effective for each region. The selection of an appropriate cropping pattern and, if necessary, adjusting the cultivation based on regional and national needs and the relative advantage of products in different regions is of great importance. So far, many studies have been conducted to optimize cropping patterns. The main reasons for the low productivity in agricultural production are the inappropriate allocation of resources and production factors. Although farmers are faced with various options for agricultural activities and crop selection, their production factors are limited. By formulating and implementing an optimal cropping pattern in a region, it is possible to familiarize farmers with the available potentials while considering the constraints of production resources, reducing risk, ensuring system stability, improving income in production, and creating the groundwork for the growth and prosperity of agricultural regions. This leads to agricultural development, increased profitability, and profitability. Decision-making is one of the most important and fundamental tasks of management, and the quality of decision-making determines the achievement of organizational goals. However, the main focus of research has been on improving the productivity of crops based on water and soil resources, with little attention given to the subject of agricultural mechanization and the criteria of regional operators. Considering the criteria of farmers in decision-making processes increases the acceptance of programs and better collaboration in implementing them. Additionally, most studies have only used one decision-making method, but each decision-support method provides a unique outcome and may differ from the results of other methods. Therefore, in this study, multiple decision-making methods were evaluated and compared to determine the best method to be used. Based on the given explanation, the objective of this research is to prioritize the factors influencing the determination of suitable cropping patterns for agricultural products using four different decision-making methods and introduce the best method. Materials and Methods:The research area is sited in Silakhour Plain, in Lorestan Province, between the cities of Doroud and Borujerd, at geographical coordinates 38 degrees 36 minutes north and 48 degrees 31 minutes east, in coordinate zone 39. In this study, Analytic Hierarchy Process (AHP), TOPSIS, VIKOR, and Simple Weighted Average methods were used for decision-making. The parameters investigated in this study included technical-agricultural, economic, macro-governmental, soil and climate, social, and production support factors. These factors included sub-factors such as the presence of mechanized planting and harvesting equipment, farming unit larger than one hectare, water requirements of plants, distance from the place of consumption, farming unit smaller than one hectare, crop profitability, required capital, suitable market for the product, customs and farmer habits, farmer education, crop cultivation experience, guaranteed purchase of the product, government incentive policies, physical characteristics of the soil in the region, chemical characteristics of the soil in the region, average temperature during the growing season, elevation of the region, average rainfall in the region, insurability of the product, sustainability of crop production, availability of seeds compatible with regional conditions, and prevalent pests in the region. To validate all judgments made in the analytic hierarchy process method, the inconsistency ratio was calculated using Expert Choice11 software. Based on this, the inconsistency ratio was calculated to be less than 0.1 in all steps of this method. If the consistency ratio is 0.1 or less, it indicates consistency in the comparisons and confirms the validity of the judgments. To reach a general consensus on the ranking of parameters, the method of merging average ranks was used. Results and Discussion: In this study, 22 indicators were identified, including the presence of mechanized planting and harvesting equipment (0.061), operational unit larger than one hectare (0.021), crop water requirement (0.014), distance from consumption site (0.008), operational unit smaller than one hectare (0.006), product profitability (0.125), required cash capital (0.116), suitable market for the product (0.020), agricultural customs and habits (0.028), education of the farmer (0.006), crop cultivation experience (0.130), guaranteed purchase of the product (0.3), government incentive policy (0.122), physical characteristics of the soil in the region (0.075), chemical characteristics of the soil in the region (0.022), average temperature during the growth season (0.022), elevation of the region (0.008), average precipitation in the region (0.006), insurability of the product (0.013), stability of crop production (0.007), availability of seeds compatible with the regional conditions (.0004), and common pests in the region (0.0002). Among the mentioned parameters, cash capital (0.236), water requirement for cultivation (0.233), product profitability (0.098), and operational unit larger than one hectare (0.039) are considered the most important factors. Certain purchase of the product (0.3), product profitability (0.0125), government incentive policy for products (0.122), and required cash capital for cultivation (0.116) were identified as the most important factors influencing the cropping pattern, respectively, using the hierarchical weighted method. product profitability and required cash capital are among the influential factors in the design of cropping patterns for agricultural products. The results showed that the ranking of agricultural products for inclusion in the regional cropping pattern differs in each decision-making method. Although grains and sugar beets have high rankings in all groups, it is necessary to validate and finalize these methods with integrated approaches to reach a general conclusion. In a multi-criteria decision-making problem, multiple decision-making methods may be used because decision-makers do not limit themselves to one decision-making method, and they may obtain different results using different methods. In fact, in such situations where the results of different methods of multi-criteria decision-making are not the same, the question is which option should be chosen. To reach a general conclusion, it is necessary to validate and finalize these methods with integrated validation and finalization approaches. Among the integration methods,
