Predicting Gilthead Sea Bream (Sparus aurata) Freshness by a Novel Combined Technique of 3D Imaging and SW-NIR Spectral Analysis

Sensors (Basel). 2016 Oct 19;16(10):1735. doi: 10.3390/s16101735.

Abstract

A technique that combines the spatial resolution of a 3D structured-light (SL) imaging system with the spectral analysis of a hyperspectral short-wave near infrared system was developed for freshness predictions of gilthead sea bream on the first storage days (Days 0-6). This novel approach allows the hyperspectral analysis of very specific fish areas, which provides more information for freshness estimations. The SL system obtains a 3D reconstruction of fish, and an automatic method locates gilthead's pupils and irises. Once these regions are positioned, the hyperspectral camera acquires spectral information and a multivariate statistical study is done. The best region is the pupil with an R² of 0.92 and an RMSE of 0.651 for predictions. We conclude that the combination of 3D technology with the hyperspectral analysis offers plenty of potential and is a very promising technique to non destructively predict gilthead freshness.

Keywords: 3D segmentation; 3D structured light; SW-NIR; fish freshness; hyperspectral imaging.

MeSH terms

  • Animals
  • Biosensing Techniques / methods*
  • Food Preservation / methods*
  • Imaging, Three-Dimensional / methods*
  • Multivariate Analysis
  • Sea Bream*
  • Spectroscopy, Near-Infrared / methods*