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Development and validation of a classification model for boar taint detection in pork fat samples.

Authors :
Rodrigues, Anaïs
Massenet, Thibault
Dubois, Lena M.
Huet, Anne-Catherine
Markey, Alice
Wavreille, José
Gengler, Nicolas
Stefanuto, Pierre-Hugues
Focant, Jean-François
Source :
Food Chemistry. Jun2024, Vol. 443, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

[Display omitted] • Untargeted volatolomics to determine VOC profiles from boar tainted meat. • GC×GC-TOFMS is a powerful tool for untargeted volatolomics. • Characterization of fat volatolome specific to boar tainted whole males. • Statistical model elaboration for boar taint discrimination. • Statistical classification model available for phenotyping and genomic studies. This study aims to characterize a complete volatile organic compound profile of pork neck fat for boar taint prediction. The objectives are to identify specific compounds related to boar taint and to develop a classification model. In addition to the well-known androstenone, skatole and indole, 10 other features were found to be discriminant according to untargeted volatolomic analyses were conducted on 129 samples using HS-SPME-GC×GC-TOFMS. To select the odor-positive samples among the 129 analyzed, the selection was made by combining human nose evaluations with the skatole and androstenone concentrations determined using UHPLC-MS/MS. A comparison of the data of the two populations was performed and a statistical model analysis was built on 70 samples out of the total of 129 samples fully positive or fully negative through these two orthogonal methods for tainted prediction. Then, the model was applied to the 59 remaining samples. Finally, 7 samples were classified as tainted. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03088146
Volume :
443
Database :
Academic Search Index
Journal :
Food Chemistry
Publication Type :
Academic Journal
Accession number :
175603959
Full Text :
https://doi.org/10.1016/j.foodchem.2024.138572