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FOCUS : JSMTV
Joint analysis of sensory and instrumental data applied to the investigation
of the texture of Charolais meat
A. Lebecque, A. Laguet, M. Chanonat, S. Lardon, E. Dufour1
AIM
Texture is a major component of meat quality and acceptability, particularly for pieces to broil. This project aims at the evaluation of a rapid, non-destructive and on- line method for the prediction of optimal ageing time considering meat tenderness.
This study has been designed in order to validate fluorescence spectros- copy as a grading tool for Charolais carcass muscles two days post-mortem.
The spectroscopic data recorded on muscles have been related to sensory and rheological data measured on the same samples.
MATERIALS AND METHODS
Meat samples :
Semitendinosus muscles of 25 Charolais carcasses of different sexes and ages (30 months to 8 years) have been considered for the study. The samples were chosen by butchers at a slaughterhouse in order to cover a wide range of meat tenderness. Sensory analyses were performed at D+7 and D+12. After slau- ghter, the meat samples were kept in a vacuum packaging between 0 and 2˚C.
Instrumental measurements:
Front-face fluorescence spectra were recorded on meat samples at D+7 and D+12. 3 samples (2 cm ✕ 1 cm ✕ 0.5 cm) were cut perpendicular to the myofibrils
1. UR Typicté des Produits Alimentaires. ENITA de Clermont-Ferrand, site de Marmilhat, 63370 Lempdes- France ; E-mail: lebecque@enitac.fr.
Joint analysis of sensory and instrumental data… 173
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on each meat piece and placed between two quartz slides. The fluorescence emis- sion spectra (excitation: 290 nm; emission: 305-400 nm; step: 0,5 nm) were recor- ded using a Fluoromax spectrofluorimeter (Spex/Jobin-Yvon, Longjumeau, Fr).
Sensory Analysis :
Ten subjects (ranging between 25 to 45 years old) were selected for their sensory ability and trained for descriptive analysis according to the guidelines in ISO 11036:1995 standard. The panel chose eight attributes for texture. 43 sam- ples, broiled at 180 ˚C for 30 sec. on each surface, were tasted (3 pieces (15 ✕
15 ✕ 15 mm) for each sample at room temperature. A 0 to 9 scale was used to evaluate the intensity of the attributes. The assessors were trained in the use of definitions of sensory attributes and scales by pre-testing extreme and different meat pieces.
The data were evaluated using TASTEL software (ABT Informatique, Paris, France).
RESULTS
The panel chose eight attributes for texture. Three of them were related to surface properties: marbled, stringy, moist and 5 attributes perceived by mouth : elasticity, initial tenderness, juiciness, global tenderness, mouth’s resi- due.
The data were evaluated by principal component analysis. The variance explained by principal components 1 and 2 was 44.97 and 24.41%, respecti- vely. The attributes perceived by the mouth were discriminated according to principal component 1. Initial and global tenderness were closed together and opposed to residue, elasticity and juiciness. The surface properties attributes were discriminated according to principal component 2.
Table 1
Correlation coefficients between the attributes
Map 1 shows that the samples are mainly discriminated according to the texture attributes perceived by the mouth. As it was anticipated, the texture range was sufficiently broad and should allow to assess the spectroscopic method. On the other hand, the ageing of meat between D+7 and D+12 had 2 effects on texture perceived by the mouth: either the texture barely did not
Negative correlations Positive correlations
Initial tenderness /elasticity : - 0.89 Global tenderness /elasticity : - 0.87 Global tenderness /residue : - 0.74 Initial tenderness /residue : - 0.61
Initial tenderness / global tenderness : + 0.90 stringy/marbled : + 0.80
Elasticity/residue : + 0.60 Juiciness/elasticity : + 0.47
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change or the tenderness increased. Indeed, the tender meats became more tender (ex : 7R36 et 12R36) whereas the most elastic meats did not improve (7R37 et 12R37) agreeing with the literature.
Map 1
PCA similarity map 1-2 for sensory data
The performed Canonical Correlation Analysis considered the 2 whole data sets containing the fluorescence spectra and the sensory attributes recorded for all the investigated samples. CCA is a multivariate treatment, which descri- bes the correlation between two sets of variables. Linear combinations of the variables of each data set are assessed by CCA so that these linear combina- tions are as correlated as possible. The first two canonical variates were corre- lated with squared canonical correlation coefficient equal to 0.57 (level of confidence, p < 0.001). It is concluded that the fluorescence spectra of tryp- tophan recorded on the meat samples were related to sensory measurements.
These results confirm the results obtained in a previous study on sensory and spectroscopic data where the first two canonical variates were correlated with squared canonical correlation coefficient equal to 0.93 (level of confidence, p <
0.001).
residue
global tenderness
juiciness
initial tenderness
elasticity
moist
stringy
marbled 12R48
12R46
12R45
12R44
12R42
12R39 12R38
12R37
12R36 12R28
12R26
12R23 12R21
12R18
12R17 12R14
12R12 12R11 7R48 7R46
7R45
7R44 7R42
7R39 7R38 7R37
7R36
7R32 7R28
7R26 7R23
7R22
7R21
7R18
7R17
7R14 7R12 7R9
7R8
7R6 7R5
7R1
-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1
-1 -0,8 -0,6 -0,4 -0,2 0
0,2 0,4 0,6 0,8 1
Axe1 (44.97%)
Axe 2 (24.41%)
Sample legend:
- 1st digit: ageing days, - R semitendinosus, - last digit: sample N°
Joint analysis of sensory and instrumental data… 175
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CONCLUSION
The reliability of fluorescence spectroscopy for the on-line measurement of meat tenderness has been proved.
ACKNOWLEDGEMENTS
This program was a collaboration with Institut Charolais (Y.Mercier), Cham- bre d’Agriculture de Saône et Loire (Y. Durand) and ADIV (J. Francia, E.Thomas) ; and partly funded by a LEADER program.
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