INDEXED IN ISI BOOK CITATION INDEX, INDEXED IN SCOPUS ABSTRACT The evolution of olive oil technology is related to research raised to deepen the understanding of biological and biophysical phenomena during the machining process olives, thus allowing the introduction of sensors able to monitoring the parameters and the process according to the characteristics of olives themselves. Current research has identified manufacturing protocols that can enable the achievement levels of product quality required by the market, mainly by reducing the time between collection and processing of olives and raising the technological level of extraction lines. In this context, the present chapter aims to describe the results of a three-years project developed by the PIN-University of Florence (Italy) in collaboration with the Tuscan Regional Agricultural Development, the Florence Commerce Chamber “Laboratorio Chimico Merceologico— Azienda Speciale CCIAA di Firenze” and the SME “TEM” (Toscana Enologica Mori). The chapter will describe the development of an innovative olive oil extraction process, characterized by a series of automatic controls (sensors, Machine Vision systems, etc.) of several agronomical and technological parameters during the extraction phases. This system allows several settings of the extraction process in order to dynamically modify the quality properties of the olive oil extracted. The oil mill is supported by computers and electronics systems (Machine Vision, sensors and Artificial Neural Network based software) that consents (1) the acquisition of data from the raw material, the extracted oil and the process parameters and (2) the development of a series of algorithms able to estimate the olive oil quality before the extraction process has started and to simulate the process. After some experimental campaigns conducted during the harvesting period of years 2005-2008, the devised approach identified the interrelationships between acquired data and quantitative characteristics of the product extracted. Based on the findings of the analysis of experimental data, software has then been implemented and validated. The validation comprises an iterative process that will impose changes to the software, general procedures, the possible amendment of the basic mathematics of the system, the estimate of the error, the statistical analysis of data and the development of new graphical user interfaces. The results of the devised system have been conducted according in force to European Union Rules standards and have been compared with the ones suggested by the literature.

Computers and Electronics in Innovative Olive Oil Mill Production Chain: Development of Integrated Hardware plus Software Systems for Control, Simulation, Estimation and Enhancement of Olive Oil Quality / M. Carfagni; R. Furferi; E. Cini; M. Migliorini; M. Daou; C. Cherubini; P. Boncinelli. - STAMPA. - (2011), pp. 1-82.

Computers and Electronics in Innovative Olive Oil Mill Production Chain: Development of Integrated Hardware plus Software Systems for Control, Simulation, Estimation and Enhancement of Olive Oil Quality

CARFAGNI, MONICA;FURFERI, ROCCO;CINI, ENRICO;DAOU, MARCO;BONCINELLI, PAOLO
2011

Abstract

INDEXED IN ISI BOOK CITATION INDEX, INDEXED IN SCOPUS ABSTRACT The evolution of olive oil technology is related to research raised to deepen the understanding of biological and biophysical phenomena during the machining process olives, thus allowing the introduction of sensors able to monitoring the parameters and the process according to the characteristics of olives themselves. Current research has identified manufacturing protocols that can enable the achievement levels of product quality required by the market, mainly by reducing the time between collection and processing of olives and raising the technological level of extraction lines. In this context, the present chapter aims to describe the results of a three-years project developed by the PIN-University of Florence (Italy) in collaboration with the Tuscan Regional Agricultural Development, the Florence Commerce Chamber “Laboratorio Chimico Merceologico— Azienda Speciale CCIAA di Firenze” and the SME “TEM” (Toscana Enologica Mori). The chapter will describe the development of an innovative olive oil extraction process, characterized by a series of automatic controls (sensors, Machine Vision systems, etc.) of several agronomical and technological parameters during the extraction phases. This system allows several settings of the extraction process in order to dynamically modify the quality properties of the olive oil extracted. The oil mill is supported by computers and electronics systems (Machine Vision, sensors and Artificial Neural Network based software) that consents (1) the acquisition of data from the raw material, the extracted oil and the process parameters and (2) the development of a series of algorithms able to estimate the olive oil quality before the extraction process has started and to simulate the process. After some experimental campaigns conducted during the harvesting period of years 2005-2008, the devised approach identified the interrelationships between acquired data and quantitative characteristics of the product extracted. Based on the findings of the analysis of experimental data, software has then been implemented and validated. The validation comprises an iterative process that will impose changes to the software, general procedures, the possible amendment of the basic mathematics of the system, the estimate of the error, the statistical analysis of data and the development of new graphical user interfaces. The results of the devised system have been conducted according in force to European Union Rules standards and have been compared with the ones suggested by the literature.
2011
9781607418504
Agriculture Research and Technology
1
82
M. Carfagni; R. Furferi; E. Cini; M. Migliorini; M. Daou; C. Cherubini; P. Boncinelli
File in questo prodotto:
File Dimensione Formato  
Agriculture Research And Tecnology (2010)_rid.pdf

Accesso chiuso

Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 2.26 MB
Formato Adobe PDF
2.26 MB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/361776
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 1
social impact