Measurements of quality of cod by electronic noses (Contributo in volume (capitolo o saggio))

Type
Label
  • Measurements of quality of cod by electronic noses (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 2003-01-01T00:00:00+01:00 (literal)
Alternative label
  • Guðrún Ólafsdóttir, Di Natale C. and Macagnano A (2003)
    Measurements of quality of cod by electronic noses
    Wageningen Academic Publishers, Wageningen (Paesi Bassi) in Quality of Fish from Catch to Consumer, 2003
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Guðrún Ólafsdóttir, Di Natale C. and Macagnano A (literal)
Pagina inizio
  • 225 (literal)
Pagina fine
  • 234 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • Quality of Fish from Catch to Consumer (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Iceland Fisheries Laboratories, Reykjavik, Iceland University of Rome Tor Vergata, Rome, Italy (literal)
Titolo
  • Measurements of quality of cod by electronic noses (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 9076998140 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autoriVolume
  • J.B. Luten, J B Oehlenschlager and G. Olafsdottir (literal)
Abstract
  • Odor is an important attribute to evaluate the freshness of food. Electronic noses can give objective information about the freshness odor quality of fish by detecting volatile compounds produced during storage. The results of mesurements of code stored for 17 days in ice using two electronic noses will be compared to sensory analysis using the quality index method (QIM). The two electronic noses LibraNose and Freshsense are based on different sampling procedures and sensor technologies. LibraNose is based on an array of eight thickness shear mode resonators coated with metalloporphyrins. FreshSense is based on four electrochemical sensors: CO, H2S, SO2 and NH3. The data of the two instruments have been integrated using conventional chemometrics and neural network techniques. The prediction of the odor evaluation scores of the QIM using the output of the sensors of the different noses and their combination shows that better performance is achieved when their data are fused. (literal)
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