Two separate artificial sensors, an electronic eye (EE) and an electronic tongue (ET), were recently developed to monitor grape ripening based on the analysis of must. The aim of this research is to exploit the complementary information obtained by means of EE and ET sensing systems using different data fusion strategies, in order to develop an integrated device able to quickly and easily quantify the physico-chemical parameters that are used to assess phenolic ripeness. To this purpose, both low-level and mid-level data fusion approaches were investigated. Partial Least Squares (PLS) regression was applied to the fused data, with the aim of relating the information brought by the two sensors with twelve physico-chemical parameters measured on the must samples by standard analytical methods. The results achieved with mid-level data fusion outperformed those obtained using EE and ET separately, and highlighted that both the artificial sensors have made a significant contribution to the prediction of each one of the considered physico-chemical parameters.

Data fusion of electronic eye and electronic tongue signals to monitor grape ripening / Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Pigani, Laura; Vasile Simone, Giuseppe; Ulrici, Alessandro. - In: TALANTA. - ISSN 0039-9140. - 195:(2019), pp. 181-189. [10.1016/j.talanta.2018.11.046]

Data fusion of electronic eye and electronic tongue signals to monitor grape ripening

ORLANDI, GIORGIA;Calvini, Rosalba;Foca, Giorgia;Pigani, Laura;Vasile Simone, Giuseppe;Ulrici, Alessandro
2019

Abstract

Two separate artificial sensors, an electronic eye (EE) and an electronic tongue (ET), were recently developed to monitor grape ripening based on the analysis of must. The aim of this research is to exploit the complementary information obtained by means of EE and ET sensing systems using different data fusion strategies, in order to develop an integrated device able to quickly and easily quantify the physico-chemical parameters that are used to assess phenolic ripeness. To this purpose, both low-level and mid-level data fusion approaches were investigated. Partial Least Squares (PLS) regression was applied to the fused data, with the aim of relating the information brought by the two sensors with twelve physico-chemical parameters measured on the must samples by standard analytical methods. The results achieved with mid-level data fusion outperformed those obtained using EE and ET separately, and highlighted that both the artificial sensors have made a significant contribution to the prediction of each one of the considered physico-chemical parameters.
2019
16-nov-2018
195
181
189
Data fusion of electronic eye and electronic tongue signals to monitor grape ripening / Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Pigani, Laura; Vasile Simone, Giuseppe; Ulrici, Alessandro. - In: TALANTA. - ISSN 0039-9140. - 195:(2019), pp. 181-189. [10.1016/j.talanta.2018.11.046]
Orlandi, Giorgia; Calvini, Rosalba; Foca, Giorgia; Pigani, Laura; Vasile Simone, Giuseppe; Ulrici, Alessandro
File in questo prodotto:
File Dimensione Formato  
TAL-D-18-02793R1.pdf

Accesso riservato

Tipologia: Versione dell'autore revisionata e accettata per la pubblicazione
Dimensione 2.57 MB
Formato Adobe PDF
2.57 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
orlandi2019.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 4.96 MB
Formato Adobe PDF
4.96 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
POSTPRINTj.talanta.2018.11.046.pdf

Open access

Tipologia: Versione dell'autore revisionata e accettata per la pubblicazione
Dimensione 1.38 MB
Formato Adobe PDF
1.38 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1167799
Citazioni
  • ???jsp.display-item.citation.pmc??? 11
  • Scopus 43
  • ???jsp.display-item.citation.isi??? 34
social impact