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Energies 2017, 10(7), 831; doi:10.3390/en10070831

A Computational Tool for Comparative Energy Cost Analysis of Multiple-Crop Production Systems

1
Department of Agriculture, Forestry and Food Science (DISAFA), University of Turin, Largo Braccini 2, 10095 Grugliasco, Italy
2
Institute for Research and Technology—Thessaly IRETETH/Centre for Research & Technology Hellas CERTH, Dimitriados Str. 95, GR 38333 Volos, Greece
*
Author to whom correspondence should be addressed.
Academic Editor: Thomas E. Amidon
Received: 5 April 2017 / Revised: 29 May 2017 / Accepted: 13 June 2017 / Published: 22 June 2017
(This article belongs to the Collection Bioenergy and Biofuel)
View Full-Text   |   Download PDF [2119 KB, uploaded 22 June 2017]   |  

Abstract

Various crops can be considered as potential bioenergy and biofuel production feedstocks. The selection of the crops to be cultivated for that purpose is based on several factors. For an objective comparison between different crops, a common framework is required to assess their economic or energetic performance. In this paper, a computational tool for the energy cost evaluation of multiple-crop production systems is presented. All the in-field and transport operations are considered, providing a detailed analysis of the energy requirements of the components that contribute to the overall energy consumption. A demonstration scenario is also described. The scenario is based on three selected energy crops, namely Miscanthus, Arundo donax and Switchgrass. The tool can be used as a decision support system for the evaluation of different agronomical practices (such as fertilization and agrochemicals application), machinery systems, and management practices that can be applied in each one of the individual crops within the production system. View Full-Text
Keywords: energy cost; energy balance; efficiency of energy; agriculture energy cost; energy balance; efficiency of energy; agriculture
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Rodias, E.; Berruto, R.; Bochtis, D.; Busato, P.; Sopegno, A. A Computational Tool for Comparative Energy Cost Analysis of Multiple-Crop Production Systems. Energies 2017, 10, 831.

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