Master Thesis Online
Evaluating Raman Spectroscopy as a Tool for Genetic Selection Against Boar Taint.
Genin, Armelle 
Promotor(s) :
Gengler, Nicolas
;
Fernandez Pierna, Juan Antonio
Date of defense : 3-Sep-2025 • Permalink : http://hdl.handle.net/2268.2/24432
ArmelleGenin_TFE_2025.pdfDetails
| Title : | Evaluating Raman Spectroscopy as a Tool for Genetic Selection Against Boar Taint. |
| Translated title : | [fr] Évaluation de la spectroscopie Raman comme outil de sélection génétique contre l’odeur de verrat |
| Author : | Genin, Armelle
|
| Date of defense : | 3-Sep-2025 |
| Advisor(s) : | Gengler, Nicolas
Fernandez Pierna, Juan Antonio
|
| Committee's member(s) : | Schroyen, Martine
Markey, Alice
Soyeurt, Hélène
Beckers, Yves
|
| Language : | English |
| Number of pages : | 78 |
| Keywords : | [en] Raman spectroscopy [en] Boar taint [en] Androstenone [en] Genetic selection [en] Genomic [en] Phenomic [en] Chemometrics [en] skatole |
| Discipline(s) : | Life sciences > Agriculture & agronomy Life sciences > Genetics & genetic processes |
| Funders : | Public Service of Wallonia (SPW) Agriculture of the Walloon Region (RW), Belgium |
| Research unit : | Centre Wallon de recherche agronomiques (CRA-W) |
| Name of the research project : | NoWallOdor |
| Target public : | Researchers Professionals of domain Student General public |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en bioingénieur : sciences agronomiques, à finalité spécialisée |
| Faculty: | Master thesis of the Gembloux Agro-Bio Tech (GxABT) |
Abstract
[en] Boar taint, caused by androstenone and skatole in entire male pigs, remains a major challenge as the European pig industry moves away from surgical castration for welfare reasons. This study assessed Raman spectroscopy as a tool for genetic selection against boar taint through three approaches: building a classification model, integrating predictions into genetic evaluations, and exploring phenomic selection using spectral similarities. The PLS-DA model achieved 75% sensitivity and 67% specificity, while Raman-based predictions were moderately heritable, correlated with reference traits, and could increase genetic gain by 5%. Although the phenomic selection approach tested with spectral similarities has not yet matched the predictive potential of genomic selection, it offers promising avenues for optimization.
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