Prioritization of Strategic Agricultural Crops in Alborz Province Using the Fuzzy Delphi Method and The Analytical Hierarchy Process (AHP)

Document Type : Research Article

Authors

M. Sharifi ¹

A. Akram ¹

Sh. Rafiee ¹

M. Sabzehparvar ²

¹ University of Tehran

² Iran University of Science & Technology

https://doi.org/10.22067/jam.v4i1.33174

Abstract

Alborz province with an area of about 5121.7 km2 has about 0.31% of the total area of the country. The total arable area of the province is about 48954 hectares. Water, land and capital are the most important factors for agricultural production. By understanding the subjective beliefs, decision-making criteria and economic incentives of local farmers, the priority of crops can be achieved with the maximum profitability of farmers and the least damage to the resources (water and land). The combination of Fuzzy Delphi techniques and methods of integrating analytical hierarchy process (AHP) can be an appropriate approach for achieving this goal. By employing the above combination of Fuzzy and AHP techniques, the priorities of the strategic agricultural crops in Alborz province achieved as wheat, barley, corn silage, alfalfa, cotton and canola, with final priority weighting factors of 0.496, 0.403, 0.354, 0.320, 0.183, and 0.090, respectively. By comparing the decision criteria it has been determined that the farmers prefer the amount of cultivation area, net income, production costs and livestock needs with the relative importance factors of 0.487, 0.410, 0.346 and 0.188, respectively. Among all prioritization criteria, the cultivated area had the highest priority. Water shortage, labor costs, lack of financial support, and governmental purchase allowance for wheat, were the main reasons for shifting the cultivated area towards wheat cultivation with total area of 14350 hectares.

Keywords

Alborz province

Fuzzy Delphi method

Analytical Hierarchy Process (AHP)

Strategic agricultural products

20.1001.1.22286829.1393.4.1.14.8

Subjects

• Resilience, Risk, and Uncertainty Engineering in Agricultural Systems

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