An Agent-Based Model-Driven Decision Support System for Assessment of Agricultural Vulnerability of Sugarcane Facing Climatic Change

Alina Evelyn Badillo-Márquez, Alberto Alfonso Aguilar-Lasserre, Marco Augusto Miranda-Ackerman, Oscar Osvaldo Sandoval-González, Daniel Villanueva-Vásquez and Rubén Posada-Gómez
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Alina Evelyn Badillo-Márquez: Division of Research and Postgraduate Studies, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Mexico
Alberto Alfonso Aguilar-Lasserre: Division of Research and Postgraduate Studies, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Mexico
Marco Augusto Miranda-Ackerman: Facultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Tijuana 22390, Mexico
Oscar Osvaldo Sandoval-González: Division of Research and Postgraduate Studies, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Mexico
Daniel Villanueva-Vásquez: Departamento de Investigación y Posgrado, Tecnológico Nacional de México/Instituto Tecnológico Superior de Misántla, Km 1.8 Carretera a lomas de Cojolite, Misántla 93821, Mexico
Rubén Posada-Gómez: Division of Research and Postgraduate Studies, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Av. Oriente 9, 852. Col. Emiliano Zapata, Orizaba 94320, Mexico

Mathematics, 2021, vol. 9, issue 23, 1-32

Abstract: In recent years, there have been significant changes in weather patterns, mainly caused by sharp increases in temperature, increases in carbon dioxide, and fluctuations in precipitation levels, negatively impacting agricultural production. Agricultural systems are characterized by being vulnerable to the variation of biophysical and socioeconomic factors involved in the development of agricultural activities. Agent-based models (ABMs) enable the study, analysis, and management of ecosystems through their ability to represent networks and their spatial nature. In this research, an ABM is developed to evaluate the behavior and determine the vulnerability in the sugarcane agricultural system; allowing the capitalization of knowledge through characteristics such as social ability and autonomy of the modeled agents through fuzzy logic and system dynamics. The methodology used includes information networks for a dynamic assessment of agricultural risk modeled by time series, system dynamics, uncertain parameters, and experience; which are developed in three stages: vulnerability indicators, crop vulnerability, and total system vulnerability. The development of ABM, a greater impact on the environmental contingency is noted due to the increase in greenhouse gas emissions and the exponential increase in extreme meteorological phenomena threatening the cultivation of sugarcane, making the agricultural sector more vulnerable and reducing the yield of the harvest.

Keywords: agent-based modeling; agricultural vulnerability; climatic change; system dynamics; decision-support system; sugarcane vulnerability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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