In southern Italy, the olive oil sector is an important part of the primary sector and its development requires support from research to ensure its sustainability. This work proposes the first step for set up a decision support system (DSS) for establishing mechanisation in agricultural operations for different olive groves. To contribute to this goal researches have been carried out to test the ability of remote sensing (RS) and geographic information system (GIS) to map olive groves and their agronomic characteristics. In detail, this study aimed to classify olives grove areas in terms of agronomic suitability and detect horticultural characteristics of olive groves in order to develop a fuzzy multi-criteria decision-making method for managing mechanical harvesting and pruning. The detection and interpretation of horticultural traits was conducted on two different olive groves areas of Sicily. Results demonstrate that fuzzy technique for order performance by similarity to ideal solution can be a useful decision-making tool combined with the automatable methodology for data acquisition. Copyright © 2016 Inderscience Enterprises Ltd.

La Scalia, G., Marra F.P., Rühl, J., Sciortino, R., & Caruso, T. (2016). A fuzzy multi-criteria decision-making methodology to optimise olive agro-engineering processes based on geo-spatial technologies. INTERNATIONAL JOURNAL OF MANAGEMENT AND DECISION MAKING, 15(1), 1-15 [10.1504/IJMDM.2016.076834].

A fuzzy multi-criteria decision-making methodology to optimise olive agro-engineering processes based on geo-spatial technologies

La Scalia, G.;Marra F. P.;Rühl, J.;Sciortino, R.;Caruso, T.
2016

Abstract

In southern Italy, the olive oil sector is an important part of the primary sector and its development requires support from research to ensure its sustainability. This work proposes the first step for set up a decision support system (DSS) for establishing mechanisation in agricultural operations for different olive groves. To contribute to this goal researches have been carried out to test the ability of remote sensing (RS) and geographic information system (GIS) to map olive groves and their agronomic characteristics. In detail, this study aimed to classify olives grove areas in terms of agronomic suitability and detect horticultural characteristics of olive groves in order to develop a fuzzy multi-criteria decision-making method for managing mechanical harvesting and pruning. The detection and interpretation of horticultural traits was conducted on two different olive groves areas of Sicily. Results demonstrate that fuzzy technique for order performance by similarity to ideal solution can be a useful decision-making tool combined with the automatable methodology for data acquisition. Copyright © 2016 Inderscience Enterprises Ltd.
Settore AGR/03 - Arboricoltura Generale E Coltivazioni Arboree
Settore ING-IND/17 - Impianti Industriali Meccanici
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973370369&partnerID=40&md5=dbba67d51f0f9688a4c50d3aa6d121f4
La Scalia, G., Marra F.P., Rühl, J., Sciortino, R., & Caruso, T. (2016). A fuzzy multi-criteria decision-making methodology to optimise olive agro-engineering processes based on geo-spatial technologies. INTERNATIONAL JOURNAL OF MANAGEMENT AND DECISION MAKING, 15(1), 1-15 [10.1504/IJMDM.2016.076834].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/189747
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