Determining the Optimal Cropping Pattern with Emphasis on Proper Use of Sustainable Agricultural Disruptive Inputs: Application of Robust Multi-Objective Linear Fractional Programming

One of the challenges in developing of sustainable agriculture is the non-optimal and excessive use of disruptive inputs of sustainable agriculture. The purpose of this study was to optimize the cropping pattern in the lands of drainage and Irrigation network of Mianab-e- Shooshtar with an emphasis...

Full description

Bibliographic Details
Main Authors: Mostafa Mardani Najafabadi, Abas Abdeshahi, Somayeh Shirzadi Laskookalayeh
Format: Article
Language:fas
Published: University of Tabriz 2020-03-01
Series:Journal of Agricultural Science and Sustainable Production
Subjects:
Online Access:https://sustainagriculture.tabrizu.ac.ir/article_10422_7159d7b2884f699491e164c8b7f43ec6.pdf
Description
Summary:One of the challenges in developing of sustainable agriculture is the non-optimal and excessive use of disruptive inputs of sustainable agriculture. The purpose of this study was to optimize the cropping pattern in the lands of drainage and Irrigation network of Mianab-e- Shooshtar with an emphasis on reducing the use of chemical fertilizers and pesticides. For this purpose, the multi-objective fractional linear programming method was used without and with considering uncertainty (scenarios 1 and 2, respectively) via robust optimization. Data were collected from Agricultural Jihad Organization, Water and Power Organization of Khuzestan and the Utilization Company of Karun Irrigation Networks in 2017-2018 cropping year. The results showed that in the second scenario, the amount of fertilizer, pesticides, crop area and irrigation water consumption decreased by 17, 15, 8 and 1.1 percent, respectively. It was also found that increasing the system's protection against uncertainty, decreases the use of fertilizers and chemical pesticides. Therefore, the optimal cultivation pattern of robust multi-objective linear fractional programming method should be recommended to farmers.
ISSN:2476-4310
2476-4329