Non-destructive grading of peaches by near-infrared spectrometry (Articolo in rivista)

Type

• Prodotto della ricerca (Classe)
• Articolo in rivista (Classe)

Label

• Non-destructive grading of peaches by near-infrared spectrometry (Articolo in rivista) (literal)

Anno

• 2004-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1016/j.infrared.2004.03.004 (literal)

Alternative label

• G. Carlomagno, L. Capozzo, G. Attolico, A. Distante (2004)
  Non-destructive grading of peaches by near-infrared spectrometry
  in Infrared physics & technology
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• G. Carlomagno, L. Capozzo, G. Attolico, A. Distante (literal)

Pagina inizio

• 23 (literal)

Pagina fine

• 29 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 46 (literal)

Rivista

• Infrared physics & technology (Rivista)

Note

• Scopus (literal)
• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Istituto di Studi sui Sistemi Intelligenti per l'Automazione - Consiglio Nazionale delle Ricerche (literal)

Titolo

• Non-destructive grading of peaches by near-infrared spectrometry (literal)

Abstract

• This paper describes an experimental study on non-destructive methods for sorting peaches according to their degree of ripeness. The method is based on near-infrared (NIR) transmittance spectrometry in the region between 730 and 900 nm. It estimates the ripeness in terms of internal sugar content and firmness. A station for acquiring the NIR signal has been designed and realized, carefully choosing between several options for each component. Four different stations have been realized and compared during the experimental phase. The signals acquired by the station have been pre-processed using a noise-reducing method based on a packets-wavelet transform. In addition, an outlier detection technique has been applied for identifying irregular behaviors inside each of the considered classes. Finally, a minimum distance classifier estimates the grade of each experimental data. The results obtained in classification show that this early version of the station enables the correct discrimination of peaches with a percentage of 82.5%. (C) 2004 Elsevier B.V. All rights reserved. (literal)

Prodotto di

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Sistemi sensoriali e di attuazione per l'interazione evoluta uomo-macchina (SP.P06.003.001) (Modulo)

Autore CNR

• GIOVANNI ATTOLICO (Unità di personale interno)
• ARCANGELO DISTANTE (Persona)
• LIBORIO CAPOZZO (Persona)

Insieme di parole chiave

• Parole chiave di "Non-destructive grading of peaches by near-infrared spectrometry" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Sistemi sensoriali e di attuazione per l'interazione evoluta uomo-macchina (SP.P06.003.001) (Modulo)

Autore CNR di

• ARCANGELO DISTANTE (Persona)
• GIOVANNI ATTOLICO (Unità di personale interno)
• LIBORIO CAPOZZO (Persona)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Infrared physics & technology (Rivista)

Insieme di parole chiave di

• Parole chiave di "Non-destructive grading of peaches by near-infrared spectrometry" (Insieme di parole chiave)