Literature DB >> 22063061

Application of an electronic nose for measurements of boar taint in entire male pigs.

Jannie S Vestergaard1, John-Erik Haugen, Derek V Byrne.   

Abstract

An electronic nose based on ion mobility spectrometry was used for boar taint measurements of entire male pig samples varying in androstenone and skatole levels (0.09-0.88μg/g fat and 0.01-0.26μg/g fat, respectively). Sensory perceptible boar taint (especially boar odour) was found to be more related to androstenone than to skatole, whereas a rancid note was determined more related to skatole than to androstenone. Multivariate models implementing some generally prescribed cut-off limits for androstenone (0.50μg/g) and skatole (0.21μg/g) indicated that the e-nose could be used for ordering samples with respect to low and high levels of androstenone and skatole. Studying the direct relationships between e-nose data, sensory data, androstenone and skatole showed better predictivity of the chemical compounds (androstenone: r=-0.948, RMSEP=0.309; skatole: r=-0.629, RMSEP=0.069) than for single sensory descriptors (boar odour r=0.409, RMSEP=0.789). The results thus suggest that the e-nose technology based on ion mobility spectrometry as in the MGD-1 may have a potential for future rapid sorting of boars at the slaughter line. The study provides new knowledge of the applicability of ion mobility spectrometry for measuring boar taint and also confirms the challenge of measuring boar taint using chemically determined cut-off limits for a sensory perceptible phenomenon. Thus, future development should be more devoted to developing holistic approaches rather than focusing on the influence of single variables on boar taint.

Entities:  

Year:  2006        PMID: 22063061     DOI: 10.1016/j.meatsci.2006.05.005

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  3 in total

1.  Nondestructive methods for quality evaluation of livestock products.

Authors:  K Narsaiah; Shyam N Jha
Journal:  J Food Sci Technol       Date:  2011-02-17       Impact factor: 2.701

2.  Machine Learning: A Crucial Tool for Sensor Design.

Authors:  Weixiang Zhao; Abhinav Bhushan; Anthony D Santamaria; Melinda G Simon; Cristina E Davis
Journal:  Algorithms       Date:  2008-12-01

3.  High throughput method for quantifying androstenone and skatole in adipose tissue from uncastrated male pigs by laser diode thermal desorption-tandem mass spectrometry.

Authors:  Birgitte Winther Lund; Claus Borggaard; Rune Isak Dupont Birkler; Kirsten Jensen; Susanne Støier
Journal:  Food Chem X       Date:  2021-01-08
  3 in total

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