The use of computed tomography to estimate proximate body composition in yellowtail kingfish (Seriola lalandi)

Read full text
Authors: Dino Milotic, Alan John Lymbery, Fiona Anderson, Gavin J. Partridge, L. Pannier, Graham Edwin Gardner
Cited by: 0
References: 43

Abstract

Yellowtail kingfish ( Seriola lalandi , YTK) is growing in popularity as a production species in the Australian aquaculture industry and has potential in high-value, premium grade sashimi markets internationally. Non-invasive and chain-speed measures of carcase composition within the red meat industry have allowed effective phenotyping for genetic improvement of meat quality traits, which is yet to be developed in the aquaculture industry. Here, a computed tomography scanner (CT) was used to scan YTK at various machine settings, including voltage (100 kV, 120 kV, 135 kV), field of view (FoV) (500 mm and 320 mm) and slice width (0.5 mm, 1 mm, 3 mm and 4 mm). Four tissue segmentation thresholds were applied to determine the optimal machine settings to estimate chemical proximate composition (body fat %, fillet fat % and protein %) of whole, bulleted and skinned fillets. CT accuracy was verified through Soxhlet fat extraction and protein extraction. The best precision of estimation of body fat % and body protein % was found using fat density (−115 to 50 HU) and protein density (51 to 200 HU), at voltage 100 kV and FoV of 500 mm, while slice width had minimal effect on accuracy. While the best precision was seen in the bullet scans, the addition of whole fish weight as a model covariate substantially improved precision seen in whole fish scans.

Fields of Study & Subjects

Fish Ecology and Management Studies Aquaculture Nutrition and Growth Fish Biology and Ecology Studies

Publication details

Journal / source
Aquaculture
Publisher
Elsevier BV
Volume
625
Pages
744363–744363
Publication date
5 July 2026
Language
EN