Analysis of the production of salmon fillet - Prediction of production yield

Gine Ørnholt Johansson, María Guðjónsdóttir, Michael Engelbrecht Nielsen, Jacob Lercke Skytte, Stina Frosch

Research output: Contribution to journalJournal articleResearchpeer-review

2023 Downloads (Orbit)

Abstract

The aim was to investigate the influence of raw material variation in Atlantic salmon from aquaculture on filleting yield, and to develop a decision tool for choosing the appropriate raw material for optimized yield. This was achieved by tracking salmon on an individual level (n = 60) through a primary production site. The majority of the salmon exhibited a heavier right fillet compared to the left fillet after filleting. No explicit explanation was found for this observation although the heading procedure was shown to have a large impact. A Partial Least Square model was built to predict the yield after filleting. The model was based on six pre-processing variables and allowed an acceptable prediction of the filleting yield with a root mean square error cross validation of 0.68. The presented model can estimate the slaughter yield for a certain batch before ordering from the slaughterhouse. This may facilitate optimal planning of the production of salmon fillets by ordering and assigning the right batch to the right product category to obtain an optimal yield and quality.
Original languageEnglish
JournalJournal of Food Engineering
Volume204
Pages (from-to)80-87
Number of pages8
ISSN0260-8774
DOIs
Publication statusPublished - 2017

Keywords

  • Production analysis
  • Prediction
  • Atlantic salmon
  • Yield
  • Multivariate data analysis
  • PLS

Fingerprint

Dive into the research topics of 'Analysis of the production of salmon fillet - Prediction of production yield'. Together they form a unique fingerprint.

Cite this