Abstract

In this study a multi-objective genetic algorithm (MOGA) was applied to find the best combination of mixing energy, economic and environmental indices concerning oilseed canola production. Data were collected from oilseed farming enterprises in Mazandaran province of Iran. Life cycle assessment of canola production from cradle to farm gate was investigated to calculate the environmental emissions. Econometric modelling was applied to find the relationship functions between energy inputs and three individual output parameters including environmental emissions, output energy and economic productivity. A multi-objective model was formulated in order to maximise the output energy and benefit to cost ratio, and minimise the final score of environmental emissions in order to obtain a set of Pareto frontier. When applying CML-IA methodology, multi-objective optimization resulted in a 32.1% reduction of the total environmental emissions as well as simultaneous increase of output energy and benefit cost ratio by 24.1% and 14.2%, respectively. More specifically, the reduction of chemicals by 82.2%, nitrogen by 11.1% and other chemical fertilisers by 70.7% would be beneficial from environment, energy and economic viewpoints. This work highlights the usefulness of the implementation of MOGA in agricultural production systems to find an optimized combination of mixing energy, economic and environment

Autore Pugliese

• Notarnicola Bruno , Tassielli Giuseppe , Renzulli Pietro Alexander

Tutti gli autori

• NOTARNICOLA B.;TASSIELLI G.;RENZULLI P.A.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2016

ISSN

0959-6526

ISBN

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Numero di citazioni Wos

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Numero di citazioni Scopus

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Settori ERC

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Codici ASJC

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