Classification of Classification of
meat with boar meat with boar
taint using an taint using an electronic nose electronic nose
Agnes KIRSCHING,
Gy. BAZAR, Z. HAZAS, R. ROMVARI
Boar Boar taint odor taint
Meat from young boars (uncastrated male pigs) can present a distinctive unpleasant odor, known as boar taint, wich is detected during cooking and eating.
Meat from young boars (uncastrated male pigs) can
present a distinctive unpleasant odor, known as boar
taint, wich is detected during cooking and eating.
Boar Boar taint odor substances taint
Patterson, 1968 Patterson, 1968
• Deposited in the fat
• Testicular steroid
• Urinary odour
• A part of the human population is insensible
• Treshold value 1.0 µg/g fat
Vold, 1970;
Vold, 1970;
Walstra & Maarse, 1970Walstra & Maarse, 1970
• Deposited in the fat
• Product of the bacterial degra-
dation of tryptophan in the gut
• Fecal odour
• Treshold value 0.21 µg/g fat
Androstenone
Androstenone + + Skatole
Skatole
Detection
Detection methods methods of boar of boar taint
taint
Chemical methods:
Chemical methods:
• Several methods: colorimetric, chromatographic, immunological
• Not applicable on the slaughter line
• Complicated sample preparation
• Labor and time demanding Human sensory method Human sensory method:
• Mainly used in slaughter houses the cooking/melting tests
• It is subjective
At the present there is no on-line method for detecting At the present there is no on-line method for detecting
and sorting out the boar tainted carcasses at the and sorting out the boar tainted carcasses at the slaughter line.
slaughter line.
New possibilities the chemical gas sensor arrays, Electronic Noses (EN)
Aim of the study Aim of the study
To test the applicability of electronic nose (EN) instrument for a discrimination of boar tainted samples of different meat parts.
To test the applicability of electronic
nose (EN) instrument for a
discrimination of boar tainted samples
of different meat parts.
Samples and preparation
• Pork chops from two entire male pigs with definite boar odor.
• Five different carcass parts:
1) loin 2) neck 3) shoulder 4) other thigh 5) inner thigh
• Meat samples of the two animals were
cut into pieces and mixed
heated for 1 hour at 75 ºC
homogenized.Human sensory analysis EN measurement
0
Electronic nose (EN) measurement
Sample preparation for EN
• 1 g homogenised pork meat + 1 ml of dilution into vials;
closed with silica septa
• 20 parallels for each carcass parts (n=5×20) Headspace analysis
• An αFox 4000 (ALPHA MOS, Toulouse, France) type EN with 18 metal oxide sensors (MOS) in 3 chambers was used.
Data evaluation
•AlphaSoft V.12 software
•SPSS 16 software package
Sampl e temp.
Equilibratio
n time Injection
volume Injection
speed Flow rate
80 ºC 180s with
agitation 3000μl 500μl/s 150m l/min
Human sensory analysis procedure
Selection of panelists,
the training (n=17)
Androstenone sensitivity
of panelist was tested by triangle test
(Lunde et al. , 2009).
Selection of panelists,
the training (n=17)
Androstenone sensitivity
of panelist was tested by triangle test
(Lunde et al. , 2009).
The sensory analysis procedure (n=11)
•The feshly cooked and
homogenized meat
samples were placed on the coded and covered plates.
•Panelists were required to rate the boar taint intensity of samples on 9 cm
undivided line scale.
Results of human sensory Results of human sensory
analysis analysis
Result of androstenone sensitivity test:
Among 17 panellists (12 women, 5 men) 4 (23.5%) were insensitive to androstenone.
Samples Boar taint
Loin (1) 1.81
Neck (2) 3.25
Shoulder (3) 2.43 Thigh outer (4) 2.63 Thigh inner (5) 2.37
The average boar taint score values by the human sensory panel (n=11) The average boar taint score values by the human sensory panel (n=11)
5 0
-5
Function 1
4
2
0
-2
-4
Function 2
5 4 3
1 2 Group Centroid
5 4 3 2 1
cat
Canonical Discriminant Functions
Results of EN
Results of EN measurement
loin neck shoulder outer thigh
inner thigh The first 2 function describing 97.2% of the total variance.
The first 2 function describing 97.2% of the total variance.
Discrimination of the five meat samples using all EN sensors determined by the 1st and 2nd discriminant function
Discrimination of the five meat samples using all EN sensors determined by the 1st and 2nd discriminant function
Correctly classified samples: 94.8%
Cross-validation: 83.3%
Results of EN
Results of EN measurement
9 sensors (LY2/LG, LY2/G, LY2/AA, LY/gCT, P10/2, P40/1, T70/2, P30/1, P40/2) were chosen by the stepwise
optimization method, and only these were involved in the DA.
Discrimination of the meat samples using stepwise method Discrimination of the meat samples using stepwise method
Correctly classified samples: 91.7%
Cross-validation: 86.5%
Cross- validation
Loin Neck Shoulder Outer Thigh Inner Thigh Total
Loin 15 0 2 0 0 17
Neck 0 20 0 0 0 20
Shoulder 0 0 15 4 0 19
Outer thigh 0 0 3 16 1 20
Inner thigh 1 0 0 2 17 20
Correlation between sensory panel and EN responses to boar taint
Association between predicted (PLS) and reference (sensory panel) values of boar taint, based on EN data and human
nose score obtained for the different meat parts
Association between predicted (PLS) and reference (sensory panel) values of boar taint, based on EN data and human
nose score obtained for the different meat parts
R
2=0.92
thigh outer thigh inner neck
shoulder loin
Conclusions Conclusions
• Based on the results of sensory panel it can be concluded that the intensity of boar taint
perception increases with increasing level of fat content.
• The EN is able to discriminate with high accuracy different meat parts presenting different levels of boar taint.
• The EN responses were successfully calibrated
against sensory panel scores.
Thank you for your attention!
Thank you for your attention!
The financial support of TÁMOP-4.2.2/B-10/1 2010-0019 research grant is greatly acknowledged
