Modelling Faba Bean ( Vicia faba L.) Biomass Production for Sustainability of Agricultural Systems of Pampas

Yolanda Villacampa, Francisco José Navarro-González, Gabriela Hernández, Juan Laddaga and Adriana Confalone
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Yolanda Villacampa: Department of Applied Mathematics, University of Alicante, Apartado 99, E-03080 Alicante, Spain
Francisco José Navarro-González: Department of Applied Mathematics, University of Alicante, Apartado 99, E-03080 Alicante, Spain
Gabriela Hernández: Núcleo de Investigación NAACCE, Facultad de Agronomía-Universidad Nacional del Centro de la Provincia de Buenos Aires, Azul 7300, BA, Argentina
Juan Laddaga: Núcleo de Investigación NAACCE, Facultad de Agronomía-Universidad Nacional del Centro de la Provincia de Buenos Aires, Azul 7300, BA, Argentina
Adriana Confalone: Núcleo de Investigación NAACCE, Facultad de Agronomía-Universidad Nacional del Centro de la Provincia de Buenos Aires, Azul 7300, BA, Argentina

Sustainability, 2020, vol. 12, issue 23, 1-17

Abstract: The Pampas region is characterized by a high complexity in its productive system planning and faces the challenge of satisfying future food demands, as well as reducing the environmental impact of the activity. Climate change affects crops and farmers should use species capable of adapting to the changed climate. Among these species, faba bean ( Vicia faba L.) cv. ‘Alameda’ has shown good adaptation to weather variability and, as a winter legume, it can help maintain the sustainability of agricultural systems in the area. The main purpose of this research was to select the models which describe the production characteristics of the ‘Alameda’ bean by using the least number of variables. Experimental and agrometeorological data from the cultivation of the ‘Alameda’ in Azul, Buenos Aires province, Argentina were used to generate mathematical models. Several modelling methodologies have been applied to study the production characteristics of the faba bean. The prediction of the models generated was analyzed by randomly disturbing the experimental data and analyzing the magnitude of the errors produced. The models obtained will be useful for predicting the biomass production of the faba bean cv. ‘Alameda’ grown in the agroclimatic conditions of Azul, Buenos Aires province, Argentina.

Keywords: prediction model; PAR radiation; thermal time; biomass accumulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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