J. Sci. Fd Agric. 1977, 28, 1-10

Correlations between Physicochemical and Organoleptic Characteristics of Lamb L. dorsi Muscle Ali Asghara and Neil T. M. Yeates

Department of Animal Production, Fuculty of Rural Science, New England University, Armidale, Australia

(Munuscript received 13 August 1975)

L. dorsi muscles from 23 lamb carcases were tested for a range of organoleptic, physicochemical and microstructural properties and the results subjected to statistical analysis. Tenderness was found to be directly correlated with the content of sarco- plasmic protein, myofibrillar protein, free amino nitrogen, swelling factor of stroma, and sarcomere length in pre-rigor condition, while inversely associated with alkali- insoluble stroma, total water, total stroma and ultimate pH value of muscle. Fibre diameter in pre-rigor condition and lipid content showed a second-degree polynomial relationship with tenderness. The number of cationic groups and the amounts of acid- soluble stroma and ash were positively related to juiciness. These physicochemical characteristics, on an individual basis, accounted for 19-77% of the variation in different attributes of meat quality. This indicates a very close association between chemistry of muscle and meat quality. However, the degree and nature of the corre- lation between a physicochemical characteristic and an attribute of quality seem to depend considerably on the variation in other physicochemical aspects. This signifies a high degree of interdependence among the components of muscle. The “relative” effect of different physicochemical variables, independent of each other, on the parameters of quality could not be partitioned by multiple regression analysis.

1. Introduction

Meat quality, in a subjective sense, is a cumulative function of tenderness, juiciness, taste and flavour. These attributes are a reflection of physicochemical and microstructural properties of muscle but attempts by earlier workers 1-4 to derive mathematical relationships between physicochemical characteristics of muscle and quality of meat have shown little agreement. A number of zoo- t e c h n i ~ a l ~ ~ ~ ~ 5 (ante mortem) and technologica16-8 (post mortem) factors have also been associated with meat quality but these may be regarded as secondary factors which affect the quality by altering the primary characteristics of muscle.

Most of the earlier studies considered only a few selected aspects of the muscle rather than all the important characteristics at one time. This paper attempts to determine the significance and form of the functional relationship between a wide range of primary physicochemical aspects of raw muscle and sensory attributes of cooked meat keeping as many extraneous factors constant as possible.

2. Experimental 2.1. Source of material and data Analytical and microscopic data, on left L. dorsi muscle from 23 Dorset Horn x Poll Merino breed- ing lambs (all by one sire and of age varying between 10 to 28 weeks) and organoleptic data,5 taken on cooked meat from the corresponding right L. dorsi muscle were used in this study. Two lambs, at a time, were slaughtered. Samples from the 612 th thoracic, 13th thoracic-2nd lumbar and

a Present address: Department of Food Technology, University of Agriculture, Lyallpur, Pakistan.

1 1

2 A. Asghar and N. T . M. Yeates

3-6th lumbar regions of the left side were used respectively for physicochemical, microscopic and different protein estimations. Most of the measurements were started about 45 min post mortem according to a planned schedule, while protein fractionation was commenced about 8 h after slaughter. The right halves of the two carcases were held post mortem, in a chill room at 2 + 1 “C, for 48 h, suspended vertically (hanging) but away from the air inlet.

2.2. Physicochemical analysis Various protein fractions and swelling factor (which is inversely related to the extent of cross- linkages in stroma protein) were determined as described by Asghar and ye ate^.^ The amount of stroma divided by the amount of sacroplasmic plus myofibril protein was regarded as extra/intra- cellular protein ratio. Total water, cationic groups and anionic groups were determined by the procedure employed by Hamm and Deatherage.lo The method of Sanderson and Vailll was used with some variations5 to estimate “free” water, and the difference between total and free water represented the “bound” water. The myoglobin content was determined by the procedure of Fleming et a1.12 The pH value of minced muscle was recorded at frequent intervals at room tempera- ture till ultimate-pH value was reached.13 A strip of muscle, as described by Locker and Hagyard,14 was used to record the extent of shortening (unrestrained) at 24°C. For the measurement of fibre diameter and sarcomere length, the samples were immediately fixed within 45 min post mortem in Susa’s solution*5 at room temperature and processed according to the method5 modified from Carleton and Drury.15

2.3. Organoleptic evaluation The loin piece between 13th thoracic and 7th lumbar region was cut, from the chilled right half carcase packed in polythene and transferred to a still-air freezer at - 10°C, until used for subjective evaluation of quality. Chops, 14 in thick, were then cut with a meat saw and deep-fat-fried in peanut oil (182°C) to an internal temperature of 68”C, heat penetration being recorded with a thermocouple probe in the centre of the chop. Cores (1 x 3 in) were prepared from the “eye” of L. dorsi muscle.16 The 9-point score sheet of Cover et ~ 1 . ~ 7 as modified by Ritchey and Hostetler,18 was adopted for sensory evaluation by a trained panel of judges. However, the components of tenderness were reduced to four rather than using the original scheme of six.

2.4. Statistical analyses Simple, partial and multiple correlation/regressions were computed between organoleptic attributes of meat and physicochemical characteristics of muscle according to standard statistical meth0ds.1~ Fortran program of Burrz0 was used for all the analyses on a computer, IBM 1620, model 2.

3. Results

The results are summarised in Tables 1-6. In some cases the details of the statistical analysis have been omitted for brevity.

3.1. Correlations between muscle characteristics and meat quality Table 1 contains the correlation matrix of physicochemical characteristics of raw muscle with attributes of meat quality after cooking. The range of values of muscle components is also presented in the table. It can be seen that sarcoplasmic protein, myofibrillar protein, free amino nitrogen, lipid content, swelling factor of stroma, fibre diameter and sarcomere length were all positively correlated with the components of tenderness. The percentages of total stroma, alkali-insoluble stroma, total water, and extra-/intra-cellular protein ratio and ultimate pH value of muscle were negatively associated with tenderness. The number of cationic groups, ash content and acid- soluble stroma were directly related to juiciness, whereas the percentage of “bound” water and sarcoplasmic/myofibrillar protein ratio were inversely correlated with flavour of meat. In all these cases the coefficients of correlation were significant at or below 5 % probability. The other character- istics such as the amount of myoglobin, alkali-soluble stroma and “free” water and the number of anionic groups did not show significant relationship with any quality criterion of meat CP> 0.05).

Organanoleptic characteristics of lamb muscle 3

Table 1. Simple correlations between physicochemical characteristics of muscle and attributes of meat quality

Tenderness ~~

Softness to Amount of Softness of Range of tongue and Fragmentation connective connective

Muscle characteristics values tooth pressure of fibres tissue ~- - - -_ - - -

Ultimate pH value Cationic groupsn Anionic groups" Shortening (%) Free water (%) Bound water ( %) Total water (%) Ash ( %) Lipid (%) Sarcoplasmic protein (%) Myofibrillar protein (%) Free amino-Nz

(mmol/102 g muscle) Myoglobin (%) Stroma (%total) Acid-soluble stroma (%) Alkali-soluble strorna (%) Alkali-insoluble stroma

Swelling factor of strorna Sarcoplasmic/myofibril

Extra-/intra-cellular

Fibre diameter (prn) Sarcomere length (pm)

( %)

protein ratio

protein ratio

5.25-5.90 11.9-19.1 11.8-17.8 6.1-22.4

50.6-63.5 14.7-23.1 74.0-79.5 1.08-1.19 0.20-2.30 5.31-8.10 7.26-10.4

3.31-4.96

3.88-6.30 0.19-0.36

0.13-0.29 2.51-5.08

0.33-1.35 28.5-45.9

0.66-0.83

0.19-0.47 20 .744 .6 1.40-1 .79

-0.735 0.131 0.397

-0.006 -0.414

0.150

0.231 0.743 0.594 0.691

-0.757

0.566 0.041

0.239 -0.436

-0.231

-0.799 0.509

0.271

-0.543 0.602 0.446

-0.733 0.204 0.337

-0.051 -0.372

0.153 -0.623

0.354 0.610 0.390 0.606

0.581 -0.063 -0.354

0.267 -0.152

-0.813 0.471

0.026

-0.443 0.451 0.456

.__-

-0.814 0.124 0.345

-0.069 -0.328

0.051

0.231 0.713 0.471 0.724

0.665 -0.102 -0.512

0.302

-0.721

-0.309

-0.861 0.463

0.037

-0.600 0.524 0.501

tissue -

-0.777 0.123 0.333

-0.062 -0.264

0.007

0.161 0.637 0.456 0.682

0.660

-0.650

-0.048 -0.499

0.366 -0.301

-0.844 0.508

0.090

- 0 . 5 5 5 0.455 0.405

Juiciness Flavour -~ -. ___-

-0.316 -0.212 0.449 -0.138 0.331 -0.270

-0.124 -0.420 -0.161 0.382

0.126 -0.428 -0.147 0.103

0.549 0.051 0.025 -0.112

-0.083 -0.144 0.078 0.131

0.214 -0.058 -0.221 -0.047

0.120 -0.213 0.486 0.253 0.267 -0.170

-0.355 -0.158 0.172 0.014

-0.158 -0.413

0.064 -0.145 -0.081 -0.144

0.048 0.129

The correlation Coefficients equal to or greater than 0.423, 0.492, 0.537 and 0.652 are significant respectively at

a Eq./104 g proteins. 5 %, 2%, 1 % and 0.1 % probabilities.

3.2. Simple linear regressions Regression analysis was performed to estimate the functional relationship of only those physico- chemical aspects of muscle which indicated significant correlation with quality parameters in Table 1. The results of simple regression are presented in Table 2. It shows that the regression coefficients b in most of the cases are highly significant (P<O.Ol). It may be pointed out that the functional relationships do not always have clearly interpretable meaning and it is difficult to assign a biological explanation to the values of intercept a and slope b in Table 2. Nevertheless, the data do signify the relative change in meat quality with a change in the values of different characteristics of muscle. The regression coefficients in Table 2 may be useful for intrapolation but care should be taken in extrapolation.

The values of coefficients of determination (v2), which measure the fraction of variance of Y- variate that may be ascribed to the effect of X-variate, are also recorded in Table 2. The data suggest that, on an individual basis, alkali-insoluble stroma of muscle accounted for 64-72 %, myofibrillar protein 36-52%, sarcoplasmic protein 21-35 %, free amino nitrogen 32-44%, total water 42-57 %, ultimate pH value 54-66 %, stroma 19-24 %, swelling factor 22-26 % and sarcomere length 21-25 % of the variation in different components of tenderness. The ash content, acid-soluble stroma and cationic groups respectively accounted for 30, 24 and 20% of the variation in juiciness, whereas bound water accounted for 18 % of the variation in flavour.

4 A. Asghar and N. T. M. Yeates

Table 2. Simple regressions for various characteristics of muscle ( L . dorsi) with meat quality parameters ( Y=nf b X ) .

Quality characteristics

( Y ) __ _ _ - Softeness to tongue and

tooth pressure

Fragmentation of fibres

Amount ofconnective tissue

Softness of connective tissue

Juiciness

Flavour

Muscle characteristics

( X ) -. __ - - -

Alkali-insoluble fraction of stroma (%)

Total water (%) Ultimate pH value Sarcoplasmic protein (%) Free amino nitrogen

Extra/intra-cellular protein

Swelling factor of stroma Sarcomere length (pm) Stroma (%) Myofibril protein (%) Alkali-insoluble fraction of

stroma (%) Ultimate pH value Total water ( %) Free amino nitrogcn

(mmol. /lo2 gm) Swelling factor of stroma Sarcomere length (pm) Extra/intra-cellular protein

Myofibril protein (%) Alkali-insoluble fraction of

stroma (%) Ultimate pH value Total water (%) Free amino nitrogen

(mmol/102 g) Extra/intra-cellular protein

ratio Stroma (%) Sarcomere length (pm) Sarcoplasmic protein (%) Swelling factor Myofibril protein (%) Alkali-insoluble fraction of

Ultimate pH value Free amino nitrogen

(mmol/102 g) Total water (%) Extraiintra-cellular protein

Swelling factor of stroma Stroma (%) Sarcoplasmic protein (%) Myofibril protein (%) Ash ( %) Acid-soluble fraction of

stroma (%) Cationic groups

(Eq./lO4 protein) Bound water (%) Sarcoplasmic/myofibriI

protein ratio

(mmol/102 g)

ratio

ratio

stroma (%)

ratio

Constant (a) __ .-

9.24

48.48 31.50

1.85

2.62

9.21 2.49

9.70 -0.66

9.03 28 I 75 37.42

2.99 3.30

- 1 . 1 5

-0.42

8.63 1.04

9.07 28. I4 37.70

3.22

9.08 9.64 0.13 4.10 4.06 1.02

9.27 29.55

2.82 37.95

9.19 3.37 9.89 3.87 0.73

-1.19

6.31

6.02 8.03

8.99

Regression coefficient

(b) -. - -

-3.15k0.52

-0.54kO.10 -4.46f0.90

0.77k0.23

1.03 f0 .03

-7.OOk2.56 0.13k0.05 5.01k2.19

0.84+ 0.19 -0.55fO.25

-2.85k0.45 -3.96k0.80 -0.4OfO.11

0.94k0.29 0.10k0.04 4 .56k 1.94

- 5.08 5 2.24 0.66 LO. 19

-2.62k0.34 -3.81k0.59 -0.40+0.08

0.94f0.23

- 5.97 f I .74 -0.49+0.18

4 .34k1.64 0.47k0.19 0.09 rt 0.04 0.68k0.14

-2.90+0.40 -4.0650.72

1.04+0.26 -0.40?0.10

-6.17k2.02 O . l l i 0 . 0 4

0.5150.22 0.71k0.17 7.20k2.39

3.37k1.32

-0.54kO.20

0.07k0.03 -0.05+0.02

-2.60k1.25

Statistical significance

P<O.OOl

P<O.OOl P<O.OOI P<O.Ol

P<O.Ol

P<O.Ol P<0.05 P<0.05 P<0.05 P<O.OOl

P < 0.001 P<O.OOl P<O.Ol

P<0.01 P<0.05 P<0.05

P<0 .05 P < O . O l

P < O . O O I P < 0.001 P<O.01

P < O . O O l

P<O.OJ P<0 .05 P i 0 . 0 5 P i 0 . 0 5 P<0 .05 P<O.OOl

P<O 001 P < O . O O I

P<O.OOl P i o .001

P<O.Ol P<0.05 P<0 .05 P<0 .05 P < O . O O l PiO.01

P<0.05

P i 0 . 0 5 P<0.05

_ - _ r2 100

63.8

57.3 54.0 35.3

32.0

29.5 25.9 19.9 19.0 47.7

66.0 53.8 38.8

33.8 22.2 20.8

19.6 36.8

74.1 66.3 52.0

44.2

36.1 26.2 25.1 22.2 21.5 52.4

71.3 60.4

43.6 42.2

30.8 25.8 24.9 20.8 46.6 30.1

23.6

20.1 18.4

-

0 .05 iP0 .1 17.1 ~~~ ~~ ~

r2100 is the coefficient of determination of simple regression. It is an estimate of the percent variation in dependent varibale, accounted for by independent variable.

Organanoleptic characteristics of lamb muscle 5

3.3. Polynomial regressions Non-linear regressions were computed according to the equation shown in Table 3 for those charac- teristics which exhibited non-linear relationship with meat quality; namely lipid content and fibre diameter. A second-degree polynomial relationship of these variables accounted for a greater proportion of the variation in tenderness (51-77 % and 37-51 % respectively) than the linear rela- tionship (37-55 % and 20-36%). The reduction in sum of squares, tested against the mean squares remaining after curvilinear regression, was significant at 1 % or 5 % probability.

Table 3. Polynomial regressions (second-degree) for some characteristics of muscle with tenderness of meat: Y=a =k b X f c X Z

Components of Muscle tenderness ( Y ) characteristics ( X ) - - - - - - .. - - - - -

Softness to Lipid (%) tongue and tooth pressure Fibre diameter (pm)

Fragmentation Lipid (%) of fibres

Fibre diameter (pm)

Amount of Lipid (%) connective tissue Fibre diameter (pm)

Myofibrillar protein (%)

Softness of Lipid (%) connective tissue Fibre diameter (pm)

Type of regression

- -. .- -

Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear Linear Non-linear

a

5.69 5.05 3.74

NS 6.07 5.21 4.87

-2.62 6.25 5.37 5 .05

-2.65 1.02

-26.94 6 .30 5.35 5.16

-2.65

b _ _ _ - -

1.26+0.25*** 2.87f0.80** 0.10+0.03**

0.92+0.26** 3.10+0.78*** 0.07+0.03* 0.55 + 0.21 * 0.93+0.20***

0.07+0.02* 0.57+0.16**

7 .00f2 .29** 0 .93f0 .25**

0.07+0.03* 0.57+0.20**

-

3.17 f 0.49***

0.68+0.14***

3.35+0.68***

C R2100

- 25.2

- 36.3

- 37.3 -0.98 +0.34** 55.9

- 20.2 -0.007+0.003* 36.9

- 50.8

- 27.4

52.4

- 40.6

- 20.7

-~

-0.72f0.35* 63.3

- -

-1.01+0.21*** 76.9

-0.008 + 0.002** 50.9 -

-0.35+0.13* 65.5

-1.09+0.29** 65.0

-0.008+0.003* 40.0

R2100 is the coefficient of determination of multiple regression, multiple correlation is equal to d(Ra/ lOO) P10.05; **, P<O.Ol; ***, P<O.OOI; NS=Non-significant.

3.4. Multiple regressions Tables 2 and 3 indicate that single variables (alkali-insoluble stroma or lipid content) accounted maximally for 74-77% of the variation in tenderness, leaving 23-26% of the variation still un- explained. To account for the latter, multiple regressions were tried. Table 4 shows the results of multiple regression in which organoleptic scores for the “amount of connective tissue” were regres- sed on those physicochemical variables, XI to X11 (from Table 2) which were significantly associated with tenderness. The regression coefficients and coefficient of determination of multiple regression (R2100) were also computed, stepwise, after addition of each independent variable in the equation, so that successive reduction in the unexplained error variance of dependent variate could be identi- fied at each stage. Since the values of all the regression coefficients change with either adding or substracting any one independent variable in the regression equation, they have been omitted from the table and only the values of R2100 are presented.

The 11 variables in the left column of Table 4 collectively accounted for 80% of the variation in tenderness, of which 74% was due to variable X I , the alkali-insoluble stroma alone. The contribu- tion of X2 to X11 variables was very small. This was further supported by the fact that all the regression coefficients, when examined individually by t-test at each stage were found to be non- significant. (It may be pointed that these tests were more appropriate than merely testing the overall multiple correlation coefficient, which always increases with the number of Xs in the multiple regression equation). When the same variables were rearranged in the regression equation, their “relative” contribution in accounting for the quality criterion also changed. The right column in

6 A. Asghar and N. T. M. Yeates

Table 4. The change in the “relative” contribution of physicochemical variables (Xs) of muscle in accounting for the variation in scores for tendcrness ( v), as observed from the changes in the coefficients of determination of multiple regression (R2100) by rearranging the order of the variables (left vs right column) in the multiple regression equation:O Y=

a f b X 1 i - r X z f d X 3 . . . k X k

Muscle characteristics (Xs) R2100 Muscle characteristics (Xs) R2100

XI + xz + x3

+ x4 + x5

+ + x7 + XS + xs + XI0 + XI 1

x6

Alkali-insoluble stroma (%)

Total stroma (%)

Lipid (%)

Swelling factor

Sacroplasmic protein (%)

Fibre diameter (prn)

Sarcomere length (pm)

Total water %

Ultimate pH value

Myofibrillar protein %

Free amino nitrogen (mmo1/100 g muscle)

74.1 x1 +

74.4 xz +

77.4 x3

+ 78.6 x4

+ 79.9 x 5

+ +

80.0 x7 +

80.0 XS +

80.8 xe +

80.8 XI 0 +

80.8 Xl 1

79.9 x6

Lipid (%) 50.8

Myofibrillar protein (%) 58.6

Sarcoplasmic protein (%) 65.2

Free amino nitrogen 69.2

Alkali-insoluble stroma (%) 78.8

Total stroma (%) 79.7

Swelling factor 80.2

Fibre diameter (pm) 80.2

Sarcomere length (pm) 80.3

Total water (%) 80.3

Ultimate pH value 80.8

a In the equation a is intercept, * is regression coefflcient of X I independent of other vari- ables (Xs) and c to k are partial regression coefficients. Since the values of the constants (a to k) change every time with adding or substracting independent variable in the equation, they are not shown. But, only the value of R2100 are given, which were computed after each addition of a X-variate, stepwise, in the equation.

Table 4 shows that the lipid percentage at XI now accounted for about 51 % of the variation in tenderness, while the contribution of each of the remaining 10 variables was quite insignificant, including that of alkali-insoluble stroma.

The multiple regressions involving different combinations of linear and curvilinear functions, and the first-order interactions of the physicochemical variables were also computed according to the equation, shown in Table 5, to examine whether or not this approach accounts for a greater proportion of the variation in quality parameters than the preceding attempts. The results of such a computation are shown in Table 5 . This approach also failed to yield any significant improvement in the regression coefficients or in the value of R2100 as compared to simple regressions. For example Table 5 shows that about 12% of the variation in scores for “softness of connective tissue” was accounted for by the linear regression of three variables, about 9 % by their non-linear functions and 1 % by their first-order interactions. The results of other combinations of independent variables were similar to those shown in Table 4 and 5 , for different quality traits and hence have been omitted from the tables. These observations strongly suggest that the physicochemical character- istics of muscle were interrelated. If so, then statistically the contribution of the variables at position XZ and onward in a multiple regression would not be independent in reducing the error variance. This is why the multiple regressions failed to provide significant results.

3.5. Partial correlations As the multiple regressions partly failed to show the relative contribution of the physicochemical characteristics of muscle in affecting the intrinsic quality of meat, partial correlation analysis was

Organanoleptic characteristics of lamb muscle 1

Table 5. Relative contribution of linear, non-linear and first-order interactions of three inuscle characteristics in accounting for the variation in quality traits of meat as observed from comutation of R2 100 at each stage, following

equation: Y = a + bX1+ cXz + . . . dXlz+ e X 2 + . . . f X l X z + . . .

Muscle characteristics

- - - -. . - - Alkali-insoluble

stroma (Ais) (%) +

Lipid (%) +

Fibre diameter (Fd) +

(Ais)2 +

(Lipid)z +

( W z + Ais x Lipid

+ Ais x Fd

+ Lipid x Fd

Tenderness - - - - - - - - - - - - - - - - - - Softness to tongue and Amount of Softness of tooth Fragmentation connective connective

Stage pressure of fibres tissue tissue Juiciness Flavour

Xl 63 .8 66.0 74.1 7 1 . 2 12 .6 2 . 5

XZ 70.5 6 6 . 4 76 .5 71 .7 2 2 . 5 12.1

xs 71.1 66 .8 76 .6 72 .5 30 .9 17.0

x12 71 .6 66 .8 77 .4 74.7 31 .2 17 .2

x22 7 1 . 6 67 .6 83 .7 78 .5 3 3 . 2 19 .4

x32 72 .8 6 9 . 0 84 .8 81 .4 33.3 20 .6

X i X z 72 .9 69 .6 8 5 . 0 81.7 3 3 . 6 22 .9

XI& 78 .0 70.1 87.1 8 2 . 2 4 7 . 2 2 6 . 2

x2x3 79 .6 71.2 87.2 82 .3 53 .9 26 .5

R2100 is the coefficient of determination of niultiple regression and the values are shown in the table.

performed to determine the cause of the discrepancy. Table 6 records the results of partial correla- tions, computed between the ultimate pH value of muscle and the parameters of meat quality, holding other physicochemical variables constant, step by step. Two interesting features of the data are evident. Firstly, there was a tendency to change in the form of the correlation between pH value and the quality attributes when other variables were kept constant. For example, the apparent relation between the scores for “softness to tongue and tooth pressure” of meat and pH value of muscle remained negative up to the stage where the amount of sarcoplasmic protein, myofibrillar protein, free amino nitrogen and stroma were held constant. But, when the variations in the values of alkali-insoluble stroma, swelling factor, total water and fibre diameter were also eliminated, the correlation tended to be positive. It had a tendency to become negative again when the remaining variables were held constant.

Secondly, the data in Table 6 also show that the partial correlation coefficients tended to approach zero with each addition to the number of constant variables (except in a few cases) during partial correlation analysis. This suggests that a high degree of interdependence existed among the physico- chemical characteristics of muscle. Since the muscle characteristics seem to be highly correlated with one another, this posed the problem of “multi-collinearity”z1 in partitioning their relative effect on the quality of meat by multiple regression analysis. Johnston21 gave a graphical inter- pretation of multi-collinearity as follows: “The scatter of points in the XZ and X3 plane must lie exclusively on the straight line Xz=bz+b3X3; and Y values then give rise merely to a vertical scatter of points (i.e. in the Y-direction) above and below a single straight line in three dimensional space”.

4. Discussion

Excellent reviewsz-5 have covered the earlier work on correlations between muscle components and meat quality. The present study, besides providing a number of new correlations, substantiates

8 A. Asghar and N. T. M. Yeates

None (Simple r) Sarcoplasmic protein

constant +

Myofibril protein constant

+ Free amino nitrogen

constant

Stroma constant

Alkali-insoluble stroma

+ +

constant +

Swelling factor of stroma constant

Total water constant

Fibre diameter constant

Sarcomere length

+ + +

constant

Lipid constant +

Table 6. Change in the form of partial correlations between ultimate pH value of muscle and parameters of meat quality, on holding other characteristics of the muscle constant, step by step

Tenderness - - - - - - - - - - - - - - - - - .

Softness to Amount of Softness of tongue and Fragmentation connective connective

Constant variables tooth pressure of fibres tissue tissue Juiciness Flavour -

-0.735***

- 0 . 5 5 8 * *

-0.377'

-0.321

-0.136

0.155

0.254

0.254

0.115

-0.016

-0.091

-0.733***

- 0.696***

-0.531*

-0.469*

-0.313

-0.035

0.016

0.016

-0.051

-0.065

-0.143

-0.814***

-0.767***

-0.527*

-0.445*

-0.327

-0.092

-0.044

-0.050

-0,023

-0.106

-0. I69

-0.777***

-0.718***

-0.498*

-0.405a

-0.329

-0.080

0.011

0.13

0.130

0.020

0.001

-0.316

-0.516*

-0.562**

-0.536"

- 0 . 42In

-0.288

-0.313

-0.313

-0.252

-0.300

-0.239

-0.212

- 0.434*

-0.174

-0.313

- 0.458*

-0.432"

- 0 . 442a

-0.442

-0.309

-0.256

-0.205 ~~~~~~~~~~~~~~~ ~~~~~

*P<O.O5; **P<O.OI; ***P<O.OOI; Q 0.1 > P>O.O5. The degree of freedom decreases by one with each addition in the number of constant variables.

many of the previous findings, while disagreeing with others. For example, the curvilinear relation- ship of tenderness with fibre diameter and fat content in the present study is at variance with several earlier reports which have shown inverse and direct correlations respectively for these variables. This disparity may be ascribed to two possibilities. Firstly, some difference in tenderness in the pre- sent study might have been the result of different degrees of cold shortening in the intact muscle of the right half carcases during cooling, since the carcases were not identical with respect to weight (range 6.3-25.4 kg) and degree of subcutaneous fat-cover (range 0.01-0.55 cm). The latter factor, however, seems to have played the major role as the simple correlations of thickness of fat-cover with the components of tenderness were found to be quite high (r= 0.433 to 0.631,0.05 > P < 0.01), whereas the carcase size had shown little relationship (r=0.141 to 0.351, P > 0.05).5 This indicates that the risk of cold shortening would be more in least fatty (young) carcases due to susceptibility to rapid cooling than in fatter ones (mature).

Secondly, it is accepted that with the age of animal, both fibre diameter5,2?.23 and magnitude of cross-linkages in stroma5 increase. The latter change may be more important in determining tender- ness than the change in fibre diameter. For purely arithmetical reasons, muscle with fibres of small diameter would contain more fibres per unit area and, therefore, comparatively more of the sarco- lemma and endomysial tissue. This may make the meat less tender than the one composed of fibres with larger diameter (other factors being constant), although the texture (grain) in the latter case may relatively be coarser. In the case of animals at different ages, the extent of cross-linkages in stroma may become a more important quality limiting factor than the amount of stroma, despite

Organoleptic characteristics of lamb muscle 9

the fact that the relative percentage of stroma in muscle remains constantz4* 26 or tends to decrease with agesz6 These considerations may also apply to inter-cellular fat (marbling) which increases with normal growth and development of the animals.27 The favourable effect of fat-cells on the palatability of fibres is likely to be counteracted by the increase in number of cross-linkages in stroma with age.

These interactions and complexities explain the disagreement in the findings of different workers on the relationship between tenderness and amount of lipid, stroma or c ~ l l a g e n . ~ - ~ The present study provides further evidence to show that the correlation of a physicochemical variable of muscle with meat quality is strongly influenced by changes in the values of other primary character- istics of muscle due to secondary (ante and post mortem) factors.

With regard to the association between pH of muscle and tenderness, Birmingham ei ~ 1 . 2 8

reported an increase in tenderness with decrease in pH. Others implied that high pH was associated with more tender and flavour-some meat27s29 and some found no effect of high pH on quality. However, Bouton et nL30 observed that around pH 6.0 the tenderness was minimum, while it increased linearly on either side of this pH value. The present results partly substantiate their findings.

In accordance with the present study, Ahmad3l reported negative correlation between total water of muscle and tenderness, whereas Ritchey and H ~ s t e t l e r ~ ~ found positive relationship between these variables. Interestingly, the correlation between “free” water and tenderness was found to be negative for L. dorsi muscle, but positive in the case of Biceps fem0ris.3~ The results in Table 6 present a likely explanation for such controversy. It is true that the evidence provided is not very strong, because the coefficients of correlation in most of the cases were not significant; nevertheless, the trend of the results does indicate a potential change in the form of correlation between a physico- chemical variable and a trait of quality on eliminating variation in other characteristics of the muscle.

In a few earlier s t~d ie s~3- -3~ significant multiple correlations of bi- or tri-variates of muscle with tenderness have been reported. But, the present results indicate that multiple regressions would not furnish useful information if the independent variables (to be used in regression analysis) are highly interrelated, that is, the correlations among them are significantly greater than zero. Another noticeable feature of the present study was that a number of muscle characteristics showed correla- tion with kinesthetic property (tenderness), but only a few of them indicated any association with juiciness and flavour of meat. It may be that these quality traits are governed more by other com- ponents36--39 of the muscle, not covered in the present investigation.

Acknowledgements Thanks ‘are due to Professor E. J. Burr for his advice in the statistical analysis of the data, and to Dr M. A. Beg for critical study of the manuscript. Thanks are also due to Mrs Marnie F. Yeates for her assistance in microscopic study.

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