Texture quality analysis of rainbow trout using hyperspectral imaging method

Mohammad Hadi Khoshtaghaza, Mostafa Khojastehnazhand, Barat Mojaradi, Mohammad Goodarzi, Wouter Saeys

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this study a hyperspectral imaging system (short wave infrared range from 1000 to 2500 nm) was used to model fish texture by experimental compression test. Partial least square-discriminate analysis modeling technique was used for classifying the samples by linking the hyperspectral information and their measured texture. The R2 of cross validation and prediction were 0.97 and 0.96, respectively. The root mean squared errors for cross validation and prediction were 0.07 and 0.09, respectively. Sensitivity and specificity for both class I and II were 1.00. Results indicated that hyperspectral imaging in short wave infrared range has ability to detect texture stiffness of rainbow trouts which is affected by freshness.

Original languageEnglish (US)
Pages (from-to)974-983
Number of pages10
JournalInternational Journal of Food Properties
Volume19
Issue number5
DOIs
StatePublished - 2016

Keywords

  • Compression test
  • Hyperspectral imaging
  • Rainbow trout
  • Short wave infrared
  • Texture

ASJC Scopus subject areas

  • Food Science

Fingerprint Dive into the research topics of 'Texture quality analysis of rainbow trout using hyperspectral imaging method'. Together they form a unique fingerprint.

Cite this