The heritable landscape of near-infrared and Raman spectroscopic measurements to improve lipid content in Atlantic salmon fillets.


Journal

Genetics, selection, evolution : GSE
ISSN: 1297-9686
Titre abrégé: Genet Sel Evol
Pays: France
ID NLM: 9114088

Informations de publication

Date de publication:
05 Feb 2021
Historique:
received: 05 08 2020
accepted: 18 01 2021
entrez: 6 2 2021
pubmed: 7 2 2021
medline: 6 7 2021
Statut: epublish

Résumé

Product quality and production efficiency of Atlantic salmon are, to a large extent, influenced by the deposition and depletion of lipid reserves. Fillet lipid content is a heritable trait and is unfavourably correlated with growth, thus genetic management of fillet lipid content is needed for sustained genetic progress in these two traits. The laboratory-based reference method for recording fillet lipid content is highly accurate and precise but, at the same time, expensive, time-consuming, and destructive. Here, we test the use of rapid and cheaper vibrational spectroscopy methods, namely near-infrared (NIR) and Raman spectroscopy both as individual phenotypes and phenotypic predictors of lipid content in Atlantic salmon. Remarkably, 827 of the 1500 individual Raman variables (i.e. Raman shifts) of the Raman spectrum were significantly heritable (heritability (h Both NIR and Raman spectral landscapes show substantial additive genetic variation and are highly genetically correlated with the reference method. These findings lay down the foundation for rapid spectroscopic measurement of lipid content in salmonid breeding programmes.

Sections du résumé

BACKGROUND BACKGROUND
Product quality and production efficiency of Atlantic salmon are, to a large extent, influenced by the deposition and depletion of lipid reserves. Fillet lipid content is a heritable trait and is unfavourably correlated with growth, thus genetic management of fillet lipid content is needed for sustained genetic progress in these two traits. The laboratory-based reference method for recording fillet lipid content is highly accurate and precise but, at the same time, expensive, time-consuming, and destructive. Here, we test the use of rapid and cheaper vibrational spectroscopy methods, namely near-infrared (NIR) and Raman spectroscopy both as individual phenotypes and phenotypic predictors of lipid content in Atlantic salmon.
RESULTS RESULTS
Remarkably, 827 of the 1500 individual Raman variables (i.e. Raman shifts) of the Raman spectrum were significantly heritable (heritability (h
CONCLUSIONS CONCLUSIONS
Both NIR and Raman spectral landscapes show substantial additive genetic variation and are highly genetically correlated with the reference method. These findings lay down the foundation for rapid spectroscopic measurement of lipid content in salmonid breeding programmes.

Identifiants

pubmed: 33546581
doi: 10.1186/s12711-021-00605-6
pii: 10.1186/s12711-021-00605-6
pmc: PMC7866706
doi:

Substances chimiques

Lipids 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

12

Subventions

Organisme : Norges Forskningsråd
ID : 244200

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Auteurs

Gareth F Difford (GF)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway. Gareth.difford@nofima.no.

Siri S Horn (SS)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

Katinka R Dankel (KR)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

Bente Ruyter (B)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

Binyam S Dagnachew (BS)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

Borghild Hillestad (B)

Benchmark Genetics Norway AS, Sandviksboder 3A, NO-5035, Bergen, Norway.

Anna K Sonesson (AK)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

Nils K Afseth (NK)

Nofima, Norwegian Institute for Food, Fisheries and Aquaculture Research, NO-1433, Ås, Norway.

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Classifications MeSH