Cristin-resultat-ID: 2055601
Sist endret: 12. februar 2023, 15:37
NVI-rapporteringsår: 2022
Resultat
Vitenskapelig artikkel
2022

Multivariate correlation of infrared fingerprints and molecular weight distributions with bioactivity of poultry by-product protein hydrolysates

Bidragsytere:
  • Liudmila Sorokina
  • Anne Rieder
  • Shiori Koga
  • Nils Kristian Afseth
  • Rita de Cássia Lemos Lima
  • Steven Ray Haakon Wilson
  • mfl.

Tidsskrift

Journal of Functional Foods
ISSN 1756-4646
e-ISSN 2214-9414
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2022
Volum: 95
Artikkelnummer: 105170
Open Access

Importkilder

Scopus-ID: 2-s2.0-85133703488

Klassifisering

Emneord

Fourier transform infrared spectroscopy • Protein hydrolysate • Angiotensin 1 converting enzyme inhibition • Multivariate statistics • Antioxidant

Beskrivelse Beskrivelse

Tittel

Multivariate correlation of infrared fingerprints and molecular weight distributions with bioactivity of poultry by-product protein hydrolysates

Sammendrag

Characterization of protein hydrolysates is a vital step in developing peptide-based bioactive ingredients. Multivariate correlation of chemical fingerprints and bioactivity of poultry by-product protein hydrolysates is explored as a potential analytical strategy for characterization and quality control. Chemical fingerprints of sixty hydrolysates were acquired using Fourier-transform infrared spectroscopy (FTIR) and size exclusion chromatography (SEC). Bioactivities (2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and angiotensin-1-converting enzyme (ACE-1) inhibition) were measured in vitro. Partial least squares regression models based on FTIR fingerprints or SEC chromatograms showed a better prediction performance for ACE-1 inhibition (coefficients of determination (R2) = 0.91, root mean square error of prediction (RMSECV) = 2.8; R2 = 0.85, RMSECV = 3.5, respectively) than for DPPH radical scavenging (R2 = 0.74, RMSECV = 0.3; R2 = 0.75, RMSECV = 0.3, respectively). Such models are promising tools for rapid prediction of bioactivities and as a quality control technology in production of bioactive peptides.

Bidragsytere

Liudmila Sorokina

  • Tilknyttet:
    Forfatter
    ved Kjemisk institutt ved Universitetet i Oslo
  • Tilknyttet:
    Forfatter
    ved Råvare og prosess ved NOFIMA

Anne Rieder

  • Tilknyttet:
    Forfatter
    ved Mat og helse ved NOFIMA

Shiori Koga

  • Tilknyttet:
    Forfatter
    ved Råvare og prosess ved NOFIMA

Nils Kristian Afseth

  • Tilknyttet:
    Forfatter
    ved Råvare og prosess ved NOFIMA

Rita de Cássia Lemos Lima

  • Tilknyttet:
    Forfatter
    ved Råvare og prosess ved NOFIMA
1 - 5 av 7 | Neste | Siste »