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Can I read A Model to Predict Fish Quality from Instrumental Features on EtoBox?
A Model to Predict Fish Quality from Instrumental Features by A. Macagnano; M. Careche; A. Herrero; R. Paolesse; E. Martinelli; G. Pennazza; P. Carmona; A. D’Amico; C. Di Natale is a Engineering article available to read on EtoBox.
What is A Model to Predict Fish Quality from Instrumental Features about?
Sensorial evaluation of fishes, using a well-defined scheme including several qualitative attributes, can give a reliable quantitative evaluation of freshness (quality index method, QIM). The introduction of artificial instruments, mimicking human senses, seems a promising approach to obtain a comparable judgment with trained panels one. The outputs of colour, texture and electronic nose measurements can be compared and combined by data fusion, to construct an artificial quality index (AQI), describing the quality of fish at least as well as the QIM predicted. In this paper, the application of such approach to build a fish freshness indicator of sardine fishes is illustrated.
Who reads A Model to Predict Fish Quality from Instrumental Features?
It is typically read by researchers, students, and practitioners in Engineering.
- Author
- A. Macagnano; M. Careche; A. Herrero; R. Paolesse; E. Martinelli; G. Pennazza; P. Carmona; A. D’Amico; C. Di Natale
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0925-4005)
- Published
- 2005
- Language
- EN
- Field
- Engineering (Physical Sciences)