domain: sdv info shs

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Mohammed Gagaoua

Claudia C Terlouw

Didier D Micol

J.-F Hocquette

Aidan P Moloney

Karin Nuernberg

Dominique Bauchart

Abdelghani Boudjellal

Nigel D Scollan

Robert Ian Richardson

M C Terlouw

B Picard

Sensory quality of meat from eight different types of cattle in relation with their biochemical characteristics

Keywords: cattle, muscle characteristics, meat sensory qualities, gender, breed, prediction

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Meat quality attributes (colour, tenderness, flavour and juiciness) have major effects on the satisfaction of the consumer [START_REF] Dransfield | Meat quality and composition of three muscles from French cull cows and young bulls[END_REF]. These attributes are influenced by muscle characteristics of the animal and post-mortem biochemical reactions [START_REF] Ouali | Meat tenderization: Possible causes and mechanisms. A review[END_REF][START_REF] Dransfield | Meat quality and composition of three muscles from French cull cows and young bulls[END_REF][START_REF] Jurie | Muscle and meat quality characteristics of Holstein and Salers cull cows[END_REF]. Muscle characteristics are influenced by management factors such as breed, age, sex and diet [START_REF] Cuvelier | Comparison of composition and quality traits of meat from young finishing bulls from Belgian Blue, Limousin and Aberdeen Angus breeds[END_REF][START_REF] Jurie | The separate effects of the nature of diet and grazing mobility on metabolic potential of muscles from Charolais steers[END_REF]. They depend on the contractile and metabolic properties of the different categories of the myofibres (type I, type IIa, type IIx and/or type IIb) that compose the bovine skeletal muscles [START_REF] Picard | Evidence for expression of IIb myosin heavy chain isoform in some skeletal muscles of Blonde d'Aquitaine bulls[END_REF] and on the attachment of these fibres to the intramuscular connective tissues (IMCT) of which collagen is the major protein component [START_REF] Nishimura | The role of intramuscular connective tissue in meat texture[END_REF][START_REF] Dubost | Structural and biochemical characteristics of bovine intramuscular connective tissue and beef quality[END_REF]. Muscle fibre composition is known to influence colour, tenderness and ultimate pH [START_REF] Muchenje | Some biochemical aspects pertaining to beef eating quality and consumer health: A review[END_REF][START_REF] Wu | Effect of beef ultimate pH and large structural protein changes with aging on meat tenderness[END_REF]Gagaoua et al. 2015a) and intramuscular fat (IMF) content is believed to influence tenderness and juiciness [START_REF] Mandell | Effects of gender and breed on carcass traits, chemical composition, and palatability attributes in Hereford and Simmental bulls and steers[END_REF][START_REF] Scollan | Manipulating the fatty acid composition of muscle and adipose tissue in beef cattle[END_REF][START_REF] Gagaoua | Biomarkers of meat sensory qualities of Angus beef breed: Towards the development of prediction equations[END_REF].

The mechanisms underlying the relationships between muscle fibre type composition and sensory qualities are complex and results are inconsistent across studies. In a study on young Charolais bulls, [START_REF] Renand | Relationships between muscle characteristics and meat quality traits of young Charolais bulls[END_REF] explained 25 to 35% of the variability in global tenderness by collagen characteristics and metabolic properties. In a study combining seven breeds and cross-breeds from different experiments, Longissimus thoracis muscles with lower collagen contents and increased contractile and metabolic activities had greater tenderness, but each correlation explained at most 4% of the variability between animals (Chriki et al. 2012a). In other studies, muscle characteristics could predict sensory qualities across, but not within muscles and with varying precision [START_REF] Keith | Chemical and sensory properties of thirteen major beef muscles[END_REF][START_REF] Bonny | Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles[END_REF].

Little or no information is available on the existence of consistent relationships between various traits in different muscles or animal types. The present study aims to compare relationships between muscle characteristics (fibre type, collagen, intramuscular fat contents and enzyme activities) and meat sensory qualities in Longissimus thoracis muscle between different types of cattle. The main objective was to determine whether consistent relationships exist between sensory qualities and muscle characteristics, independently of gender and breed or rearing site. The study is a part of the European ProSafeBeef project (www. prosafebeef.eu).

Materials and methods

Animals

The study used 265 beef cattle of comparable chronological age (less than two years old) and different genders of four different experiments of the European ProSafeBeef project. The eight animal types included young bulls (B), i.e, 25 Limousin (Li), 25 Blond d'Aquitaine (BA) and 24 Angus (AA) reared in France (FR) and 25 Holstein (Ho) reared in Germany (DE); steers (S), i.e., 40 Belgian-Blue×Holstein (BH) and 32 Charolais×Friesian (CF) reared in Wales (UK); and heifers (H), i.e., 47 Belgian-Blue×Friesian (BF) and 47 Angus×Friesian (AF) reared in Ireland (IE). Hence each experiment corresponded to a different gender of cattle, and young bulls were reared in two experiments. The aim of the study was not to compare genders or breeds, but to evaluate differences and similarities between different animal types.

Management, slaughtering and sampling

During the finishing period (90 to 110 days), the animals were housed in groups of four animals of a same breed in 4 m×4 m pens with ad libitum access to high energy feed in the four experimental farms. The diets of the animals consisted of pasture, grass silage or concentrates, supplemented with lipids and/or antioxidant from plants additives according to the ProSafeBeef project. Details concerning the feeding regimens are as described in the ProSafeBeef project (www. prosafebeef.eu) and synthesised in the following sections.

The experiment in France was performed with 74 young bulls varying in their earliness of puberty. Bulls were fed, for a 100 days finishing period, rations composed of a 80% concentrate and 20% straw, supplemented with 1.3% Na bicarbonate and 0.75% vitamins and minerals. Within each breed, 25% of the animals received the control regime in which the concentrate contained 17% wheat, 34% maize, 25% beetroot pulp, 15% soybean meal and 8% alfalfa. For 75% of the animals, maize was removed and the regime was supplemented with unsaturated fatty acids. Hence the concentrate was composed of 15% wheat, 10% wheat middlings, 15% wheat bran, 25% beetroot pulp, 4% sunflower meal, 5% rapeseed meal and 25% extruded linseed.

The experiment in Germany used 30 Holstein young bulls assigned to two dietary treatments. Half of the animals received concentrate based on 40% crushed wheat, 10% maize, 41% soybean meal, 5% minerals, 2% molasses and 2% straw. The experimental group received grass silage with concentrate containing 58% crushed wheat, 20% crushed maize, 12% rapeseed cake, 3% linseed oil, 5% minerals, and 2% molasses.

The experiment in Ireland used 96 heifers of two genotypes (BF and AF) on pasture as described in [START_REF] Dunne | Concentrations of specific unsaturated fatty acids in semitendinosus muscle of early and late maturing heifer calves offered concentrates containing either safflower oil or ruminally-protected fish oil while at pasture[END_REF]. Briefly, at four months of age, within each breed one-third of the animals were assigned to a standard grassbased production system only, one-third were assigned to this system but supplemented with a sunflower oil containing concentrate and one-third were assigned to this system but supplemented with a ruminally protected fish oil containing concentrate (920 g dry matter kg -1 , 302 g lipid kg -1 DM, 3.47 g EPA (20:5n-3)/100 g -1 and 5.74 g DHA (22:6n-3)/100 g -1 ). Supplements were designed to enhance conjugated linoleic acid (CLA) or n-3 polyunsaturated fatty acid (PUFA) depo-sition in muscle. The cattle were housed in a slatted floor shed during winter. They were slaughtered at the end of the second grazing season or after a second winter indoors.

The experiment in the United Kingdom used 72 steers initially housed and fed ad libitum on first cut perennial ryegrass silage. Feeding regimes were based on the addition of plant extracts (PX): a PUFA-rich luzerne based plant extract obtained from the liquid fraction extracted from fresh luzerne (Medicago sativa L.), and then heat-treated and dried. The first group of 40 Belgian-Blue×Holstein was allocated to one of five dietary treatments: 1) Grass silage only, 2) grass silage plus 75 kg PX/DM intake, 3) grass silage plus 150 kg PX/DM intake, 4) straw plus control concentrate and 5) straw plus PX-supplemented concentrate and vitamin E (~300 mg kg -1 ). The second group of 32 Charolais×Friesian were housed indoors and fed on ad libitum grass silage and a conventional commercial concentrate at 70:30 forage:concentrate ratio on a DM basis, for a 30 day finishing period. After this period, eight animals were allocated at random to one of four dietary treatments: 1) grass silage, 2) grass silage plus 1.5% Echium oil/silage dry matter intake, 3) grass silage plus 3.0% Echium oil/ silage DMI and 4) grass silage plus 3.0% linseed oil/silage DMI. Approximately 1 kg of sugar beet pulp and higher level of vitamin E (300 IU kg -1 ) was also offered to all animals. However, results presented in the present study were not influenced by feed composition.

The 265 beef animals were slaughtered when they achieved the fat class 3 on the EUROP grid of carcass classification (European Economic Community (EEC) Regulations No. 1208/81). Each research group slaughtered approximately equal numbers of cattle from each nutritional diet/animal type combination on each slaughtering day. They were all slaughtered under standard conditions in either commercial or experimental slaughterhouses, depending on the facilities of each country. Before slaughter, all animals were food deprived for 24 hours and had free access to water. Slaughtering was performed in compliance with the welfare regulations of each country and respecting EU regulations (Council Regulation (EC) No. 1099/2009). All animals were stunned using a penetrative captive bolt, prior to exsanguination. The carcasses were not electrically stimulated and they were chilled and stored at 4°C until 24 h post-mortem. Ultimate pH was recorded between the 6th and 7th rib using a pH meter equipped with a glass electrode 24 or 48 h post-mortem (Gagaoua et al. 2015a).

The Longissimus thoracis muscle (LT, fast oxido-glycolytic) was excised from the right side of the carcass 24 h after slaughter. The epimysium was carefully dissected and about 400 g of muscle was taken between the 6th and 11th ribs of the LT muscle. Muscle cuts were divided into 3 parts, one for sensory evaluation and two for biochemical analysis. Part of the sample was frozen in liquid nitrogen and kept at -80°C until analysed for determination of enzyme activities, protein extraction and myosin heavy chain (MyHC) quantification. Another part of the sample was cut in pieces (1-2 cm cross-section), vacuum packed and stored at -20°C until analysed for collagen and intramuscular fat content. Samples for sensory evaluation were cut into steaks and placed in sealed plastic bags under vacuum and kept between 2-4°C for 14 days (bulls from France and Germany and heifers from Ireland) or 10 days (steers from UK) of ageing. Each loin sample was then frozen and stored at -20°C until sensory evaluation. All evaluations of muscle characteristics, intramuscular fat content excepted (using the same protocol), were conducted by the same laboratory (INRA, France).

Enzyme activities measurement

Glycolytic enzyme activities (phosphofructokinase (PFK; EC 2.7.1.11); lactate dehydrogenase (LDH; EC 1.1.1.27)) and oxidative enzyme activities (isocitrate dehydrogenase (ICDH; EC 1.1.1.42), citrate synthase (CS; EC 4.1.3.7) and cytochrome c oxidase (COX; EC 1.9.3.1)) were quantified as described by [START_REF] Jurie | The separate effects of the nature of diet and grazing mobility on metabolic potential of muscles from Charolais steers[END_REF]. These different enzymes representative of different steps of the glycolytic and oxidative pathways are currently used for the characterization of the metabolic types of muscles in beef [START_REF] Sudre | Biochemical and transcriptomic analyses of two bovine skeletal muscles in Charolais bulls divergently selected for muscle growth[END_REF][START_REF] Jurie | The separate effects of the nature of diet and grazing mobility on metabolic potential of muscles from Charolais steers[END_REF], poultry [START_REF] Eadmusik | Are one early muscle pH and one early temperature measurement sufficient to detect PSE breast meat in turkeys[END_REF]), pig (Demars et al. 2007), sheep [START_REF] Mascio | Myocardial vascular and metabolic adaptations in chronically anemic fetal sheep[END_REF] and camel [START_REF] Abdelhadi | Effect of season on contractile and metabolic properties of desert camel muscle (Camelus dromedarius)[END_REF][START_REF] Suliman | Chemical composition and structural characteristics of Arabian camel (Camelus dromedarius) m. longissimus thoracis[END_REF]. For each of the 265 animals, 200 mg of frozen muscle was thawed, ground and homogenized with a Polytron for 15 s in a 5% (w/v) solution buffer of 10 mmol L -1 Trizma-Base (pH 8.0), 250 mmol L -1 sucrose and 2 mmol L -1 EDTA. One aliquot of homogenate was centrifuged at 6 000×g for 15 min at 4°C for determination of PFK, LDH and ICDH activities. The rest of the homogenate was freeze thawed and sonicated for determination of CS and COX activities before centrifugation for the determination of CS activity. Enzyme activities (means of triplicate) were measured at 25 or 28°C using an automatic spectrophotometer (Uvikon 860, Kontron Instruments, Milan, Italy). The results were expressed as units per gram of wet muscle.

Intramuscular connective tissue measurement

Lyophilized muscle powder was prepared for collagen determination as described by [START_REF] Jurie | Muscle and meat quality characteristics of Holstein and Salers cull cows[END_REF]. Briefly, frozen muscle was homogenized in a household cutter, freeze-dried for 48 h, pulverized in a horizontal blade mill and stored at 4°C until analysed. To estimate total and insoluble collagen, the amount of total hydroxyproline (OH-prol) content was measured.

Total collagen content was determined after overnight hydrolysis of 50 mg of lyophilized muscle powder with 10 mL HCl 6 N at 105°C according to the method of [START_REF] Listrat | Effect of the type of diet on muscle characteristics and meat palatability of growing Salers bulls[END_REF]. Insoluble collagen was determined in triplicate according to a procedure adapted from [START_REF] Hill | The Solubility of intramuscular collagen in meat animals of various ages[END_REF]. Lyophilised muscle powder (100 mg) was rehydrated for 1 h in 10 mL of buffer (0.23 mol L -1 NaCl, 25 mmol L -1 Trizma, pH 7.4) before being heated in a water bath at 75°C for 1 h. After centrifugation at 4 000×g for 15 min at 20°C, the pellets were evaporated for 4 h to dryness at 45°C. After this, they were hydrolysed with 10 mL of HCl 6 N and treated as for total collagen. The data (means of triplicates) are expressed in µg of OH-prol per mg of dried matter for both total and insoluble collagen.

Intramuscular fat content measurement

Steaks (20 mm thick) of LT muscle were taken as described by [START_REF] Scollan | Manipulating the fatty acid composition of muscle and adipose tissue in beef cattle[END_REF] for the analysis of fatty acid (FA) composition. Briefly, total intramuscular fat content from a tissue powder were extracted with chloroform-methanol (2:1, v/v) according to the method of [START_REF] Folch | A simple method for the isolation and purification of total lipides from animal tissues[END_REF] by homogenisation at room temperature. The lipid contents were determined by gas liquid chromatography (GLC) on CP Sil 88 glass capillary column. Muscle total lipids are reported as g of fatty acid per 100 g wet tissue.

Protein content quantification

The protein concentrations of the samples were determined according to the Bradford method [START_REF] Bradford | A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding[END_REF]) using the Bio-Rad Protein Assay. Bovine serum albumin (BSA) at a concentration of 1 mg mL -1 was used as standard.

Electrophoresis and quantification of MyHC

Myofibrillar proteins from the LT muscles were extracted on ice as described by [START_REF] Picard | Quantitative determination of type I myosin heavy chain in bovine muscle with anti myosin monoclonal antibodies[END_REF]. Briefly, 100 mg of frozen muscle were ground in 5 mL of extraction buffer solution containing 0.5 mol L -1 NaCl, 20 mmol L -1 Na pyrophosphate, 50 mmol L -1 Tris, 1 mmol L -1 EDTA and 1 mmol L -1 dithiothreitol. After 10 min at 4°C on ice, the sample was centrifuged for 5 min at 5 000×g. Following centrifugation, the supernatant was diluted 1:1 (v/w) with glycerol at 87% and stored at -20°C until used. The samples were then mixed with an equal volume of loading buffer containing 4% SDS (w/v), 125 mmol L -1 Tris, pH 6.8, 20% glycerol (v/v), 10% β-mercatptoethanol (v/v) and 0.02% pyronin Y (w/v). The proteins were separated by SDS-PAGE electrophoresis according to [START_REF] Picard | Protocol for high-resolution electrophoresis separation of myosin heavy chain isoforms in bovine skeletal muscle[END_REF] using 9.2% polyacrylamide gels which were made in the Bio-Rad mini-Protean II Dual Slab Cell System. After staining, the gels were scanned and the proportions of the different MyHC bands were quantified by densitometry with ImageQuant software 5500 (Amersham Biosciences/GE Healthcare).

The quantification of the bands revealed the existence of MyHC-IIb isoform (Picard & Cassar-Malek 2009) in only 22 of the 265 animals (BH (8); BA (6); CH (5); AA (2); and Li (1)) with a maximal percentage of 5.5%. Consequently MyHC-IIb percentages were totalled with those of MyHC-IIx creating a new variable "MyHC-IIx+b" (fast glycolytic fibres).

Sensory analysis

The panellists were trained in accordance with the ISO standards ISO/TC 34 (ISO_8586 2012) and the accuracy and precision of the panellists were verified before sensory analysis. Sensory analysis was performed at Bristol University in the United Kingdom on the LT muscle taken 24 h after slaughter as previously described by [START_REF] Karamichou | Genetic analyses of sensory characteristics and relationships with fatty acid composition in the meat from Scottish Blackface lambs[END_REF] and [START_REF] Gagaoua | Relationships between overall liking score and sensory meat attributes in different types of beef cattle[END_REF]. Each loin sample was aged 14 days (bulls from France and Germany and heifers from Ireland) or 10 days (steers from the United Kingdom). Approximately 40 h before sensory assessment, samples were thawed, without stacking or overlapping, at 4-5°C. The morning of the analysis, the meat samples were cut into two 1.9 cm thick steaks and cooked under domestic grills, turning every 2 min until the temperature of 74°C (typical in the UK) was reached as measured in the geometric centre of the steak (measured by a thermocouple probe). After grilling, each steak was cut into 3 cm×2 cm×2 cm portions which were immediately presented to 10 panellists trained in beef meat sensory analysis. Each tasting booth was equipped with computer terminals linked to a fileserver also running a sensory software programme (FIZZ ver. 2.20h, Biosystemes, Couternon, France) that facilitated the direct entry of assessor ratings on a 0 to 10 unstructured scale to evaluate the following attributes: global tenderness (0, extremely tough; 10, extremely tender), juiciness (0, extremely dry; 10, extremely juicy), beef flavour intensity (0, extremely weak; 10, extremely strong), abnormal flavour intensity (0, extremely weak; 10, extremely strong) and overall liking (0, dislike very much; 10, like very much). All sensory assessments were completed under red light in a purpose built sensory analysis room.

Statistical analysis

The SAS software (ver. 9.1, 2002; SAS Institute Inc., Cary, North Carolina, USA) was used to verify the normality of the data and to conduct ANOVA and principal component analyses (PCA). Pearson correlations, ANCOVA and regression analyses were carried out using XlStat (ver. 2009.1.01, Addinsoft ® , New York, NY, USA). Data were normally distributed (Shapiro-Wilk test). ANOVA was used to compare animal types. For these comparisons, the general linear model (GLM) procedure fitting animal type as fixed effect, and Tukey test were used to compare LSmeans (SAS ver. 9.1, 2002; SAS Institute Inc.). PCA (Pearson) was conducted on all variables using all animal types to produce graphs to illustrate visually the different characteristics of the animal types. An overall Kaiser's measure of sampling adequacy (MSA) was calculated using PROC FACTOR of SAS. Variables with low MSA (<0.5) were removed from the final PCA (Gagaoua et al. 2015a). ANOVA was carried out to compare the individual PCA scores on the first and second axis between breeds.

Pearson correlations were calculated across animal types using average values to determine which muscle characteristics and sensory qualities were associated at the level of animal types. Pearson correlations were further calculated within animal types, to determine consistency of relationships among muscle characteristics and sensory qualities across animal types. Results are reported in figures referred to as "correlation networks". ANCOVA was used to determine relationships among sensory qualities and muscle characteristics within genders while taking into account breed.

The ANCOVA model used was

y ij =µ+α i +β(x ij -x)+ε ij
Where, y ij is the value of the dependent variable for the jth observation in the ith animal type.

µ is the overall (constant) mean value of the dependent variable.

α i is the effect of the ith animal breed on the dependent variable.

β is the pooled regression slope of the dependent variable with the explicative variable for each breed.

x ij is the value of the explicative variable for the jth observation from the ith breed.

x is the common mean of x of all samples, ε ij is the random or unexplained error associated with the jth observation in the ith animal type group not explained by the animal type of the explicative variable.

If non-significant, breed was removed from the model, i.e., α i =0, and the model became a simple linear regression (y ij =µ+β(x ij -x)+ε ij ).

For ANCOVA and regression analyses, the option "optimal model" was selected. This option produces the model with the highest adjusted r 2 value. The adjusted r 2 value expressed as a percentage will be referred to as the % of variability explained. The maximal number of explanatory variables was fixed at 3. Variables that were significant but contributed less than 2% in terms of explanatory power (r 2 ) were excluded from the model. The standardised coefficients are reported in the Results section and refer to how many standard deviations the explained variable will change, per standard deviation change in the explanatory variable.

Finally, for all variables Z-scores were calculated, removing animal type effects [START_REF] Picard | Inverse relationships between biomarkers and beef tenderness according to contractile and metabolic properties of the muscle[END_REF]. This data set was used to determine associations among variables after removal of breed effects. More specifically, breeds showing a significant correlation between two given variables were combined and an overall r-value was calculated using Z-scores and reported in the correlation networks.

Results

Associations among muscle characteristics and sensory qualities at the level of the animal type

Differences between animal types in terms of LT muscle characteristics and sensory qualities are described in Table 1. Correlations based on the means presented in Table 1 indicate that certain traits are strongly associated at the level of the animal type (Table 2-A-C; Fig. 1). For example, animal types with high COX activity had also high ICDH activity but low LDH activity. High COX activity was further associated with high MyHC-I proportions, low MyHC-IIx+b proportions and high ultimate pH. Animal types with higher proportions of MyHC-IIa had higher levels of collagen. Certain correlations did not reach significance due to the low level of degrees of freedom (df=6). Animal types with high tenderness had high beef flavour and overall liking and were characterised by low PFK and high CS activities (Table 2-C). High tenderness was also associated with high IMF (Table 2-C). The PCA plots illustrate visually the relationships between muscle characteristics and sensory qualities (variable loadings: Fig. 2-A) and the similarities and differences between the breeds and genders of the different experiments (average individual scores: Fig. 2-B). The first principal component accounting for 28% of variability was positively correlated with oxidative enzyme activities (ICDH, COX and CS), MyHC-I fibres, tenderness, juiciness, beef flavour and overall liking and negatively correlated with MyHC-IIx+b and the activity of the glycolytic enzymes PFK and LDH. The second principal component accounting for 21.7% of the variability was relatively strongly positively correlated with total and insoluble collagen and negatively with IMF content and the activity of the glycolytic enzyme LDH. Individual scores of the first axis averaged per breed discriminated between nearly all breeds, apart from AF heifers and Ho bulls, who had similar scores, and BF heifers LDH, lactate dehydrogenase; PFK, phosphofructokinase; ICDH, isocitrate dehydrogenase; COX, cytochrome c oxidase; CS, citrate synthase. The same as below.

2)

Heifers (AF, Aberdeen Angus×Friesian; BF, Belgian-Blue×Friesian).

3) Bulls (Ho, Holstein; Li, Limousin; BA, Blond d'Aquitaine; AA, Aberdeen Angus).

4)

Steers (BH, Belgian-Blue×Holstein; CF, Charolais×Friesian).

3) SEM, standard error of mean.

Least square means in the same row for animal type effect not followed by a common letter (a-e) differ significantly, P<0.05. *** , P<0.0001.

and AA bulls, who had also similar scores (Fig. 2-C). Briefly, CF and BH steers were characterised by high activities of oxidative enzymes and MyHC-I and high scores for tenderness, juiciness, beef flavour and overall liking, while for Li and BA bulls this was the opposite. BF heifers and AA bulls had the same profile as the latter group, but less extreme. AF heifers and Ho bulls had intermediate profiles. Individual scores of the second axis averaged per breed formed 3 groups that differed significantly (Fig. 2-C). The AA and Ho bulls scored relatively high for collagen and PFK and low for LDH and MyHC-IIx+b while BF and AF heifers scored the opposite. The BA and Li bulls and BH and CF steers had intermediate levels. In conclusion, the eight groups differed on at least one of the two first principal axes.

Correlations among muscle characteristics within animal types

Correlations calculated per animal type using Z-scores (Fig. 3-A) found that MyHC-IIx+b proportions were negatively correlated with MyHC-I and MyHC-IIa proportions for nearly all animal types. LDH and PFK activities were weakly positively correlated for all breeds apart from BA and Ho. ICDH, COX and CS were positively correlated for at least half of the animal types. ICDH and LDH, and MyHC-I and LDH were negatively correlated for four animal types. These correlations were not gender specific, as the three genders were represented in each of the correlations. Total collagen content was strongly correlated with insoluble collagen for all animal types, as expected. In addition to the figure, for BH heifers LDH activity was negatively correlated (r=-0.44; P<0.05) with COX activity, and for AA bulls, with CS activity (r=-0.44; P<0.05).

Correlations among sensory qualities within animal types

With respect to sensory qualities, for all animal types, overall liking was positively correlated with beef flavour and negatively with abnormal flavour. For all animal types except for AF heifers, beef flavour and abnormal flavour were negatively correlated (Fig. 3-B). Overall liking was further correlated with global tenderness for all animal types except for CF steers. These correlations were again not gender specific, as the three genders were represented in each of the correlations found. In addition, global tenderness was positively correlated with juiciness for three of the animal types and with beef flavour, also for three animal types (Fig. 3-B). None of the animal types showed a correlation between juiciness and beef flavour (r between -0.20 and 0.28; NS).

Correlations between sensory qualities and muscle characteristics within animal types

It was not possible to establish a coherent correlation network for correlations between sensory qualities and muscle characteristics as only one significant (P<0.05) correlation was found that showed some consistency across animal types. Tenderness was correlated with CS content for Li bulls (r=0.43), AF heifers (r=0.34) and BH steers (r=0.39). For these animal types, the overall r-value (on Z-scores) was 0.38 (P<0.0001). In addition, fourteen more correlations were found between muscle characteristics and sensory qualities with r-values over 0.40 (P<0.05), but showed no consistency across animal types. Most correlations were found for Li bulls: abnormal beef flavour with PFK (r=0.47), beef flavour with MyHC-IIa, MyHC-IIb+x and LDH (r=0.40; -0.47 and -0.52, respectively), overall liking with insoluble Maximal number of variables allowed was set at three, minimal explanatory power was set at 2% apart from the global models using Z-scores. Positive correlations are represented by a continuous line; negative correlations are represented by a dotted line. The animal types for which the correlation was significant are indicated next to the arrow. If "all" is indicated, the correlation was significant for all animals. The values next to the arrows represent the regression coefficients calculated using Z-scores including only the animal types for which the correlation was significant.

collagen and PFK (r=-0.63 and -043, respectively) and juiciness with ultimate pH (pHu) (r=0.48). For Ho bulls, beef flavour was correlated with MyHC-IIa and COX (r=-0.52 and 0.49, respectively) and juiciness with MyHC-IIa, ICDH and COX (r=-0.50; 0.51 and 0.67, respectively). For AF heifers, juiciness was correlated with insoluble collagen and lipid content (r=-0.40 and 0.55, respectively). Other significant correlations were found for AF and BF heifers and BH steers, but they were relatively weak (r<0.40).

The lack of consistency between animal types explains the weak explanatory power of the regression models subsequently established. When genders were considered separately using raw data of muscle characteristics, the models explained between 4.6 and 39.5% of the variability between animals (Table 3). However, breed explained most of the variability and the contribution of muscle characteristics was weak. The strongest contribution was from IMF, explaining 9% of the variability in overall liking between bulls. LDH activity in heifers, and pHu and CS activity in steers, contributed between 6 and 7% to the varaibility of tenderness.

The explanatory power of regression analyses between Z-scores of sensory qualities and muscle characteristics (Table 3) was also very weak. For tenderness, regression analyses using Z-scores found that CS, MyHC-IIa and IMF explained together 4.8% of the variability between animals. For overall liking, total collagen content and IMF explained together 7.2% of the variability between animals in overall liking.

Discussion

The present study compared Longissimus thoracis muscle characteristics and sensory qualities to explore consistencies and differences in correlations among muscle characteristics and sensory qualities in eight animal types. The animals were similar in age and had all been subjected to a finishing period of 100 days on average. The animal types differed in breed, gender and rearing site, where each rearing site corresponded to a given gender, breed and rearing environment. Untransformed data were used to compare animal types, and Z-scores, after removing the effects of animal type, were used to describe similarities across animal types.

Across all animal types, the LT muscle had high glycolytic and intermediate oxidative properties. Similarly, Chriki et al. (2012b) classified the LT muscle as fast oxido-glycolytic. The animal types differed in all the measured contractile and metabolic muscle characteristics and sensory qualities. The animal types were characterised by significantly different positions along the first principal axes of the PCA indicating that the first two axis had good discriminatory power for the animal types used in the study. Due to the choice of breeds, breed effects were stronger for steers and bulls than for heifers. Overall, the LTs of heifers and steers were more glycolytic and oxidative oriented, respectively, while the LT of bulls was intermediate, as also previously reported by [START_REF] Jurie | Comparison of cloned and non-cloned Holstein heifers in muscle contractile and metabolic characteristics[END_REF]. More specifically, compared to the steers and bulls, the heifers had lower MyHC-I proportions, higher LDH and lower COX activities. The fibre type distribution of the BH steers was close to the distribution observed in the heifers, while CF steers had high MyHC-I proportions.

Sensory analysis also revealed many significant differences between animal types. Steers had the best and bulls the worst scores for sensory qualities, with intermediate levels for heifers. The best scores were obtained for the CF steers. The CF steers and Ho bulls and both heifer breeds scored high for juiciness and Ho bulls scored high for beef flavour compared to the other bulls. These observations agree with earlier results reporting better sensory scores for steers than heifers and for heifers than bulls [START_REF] Wulf | Genetic influences on beef longissimus palatability in charolais-and limousin-sired steers and heifers[END_REF][START_REF] Choat | The effects of cattle sex on carcass characteristics and longissimus muscle palatability[END_REF][START_REF] Bureš | Growth performance, carcass traits and meat quality of bulls and heifers slaughtered at different ages[END_REF]. Other results found, in contrast, no differences between steers and heifers or between young bulls and heifers [START_REF] Hanekamp | Effects of sire breed and husbandry system on carcass, meat and eating quality of Piemontese and Limousin crossbred bulls and heifers[END_REF] in terms of tenderness. Another study found, also in contrast to our results, higher scores for juiciness and beef flavour for heifers compared to steers [START_REF] Hennessy | Effect of a preweaning growth restriction on the subsequent growth and meat quality of yearling steers and heifers[END_REF].

Correlations using average values of animal types found coherent associations between fibre type composition and glycolytic and oxidative enzymes. Coherent associations among muscle characteristics were also found within animal types. The correlation network shows that oxidative characteristics (MyHC-I, ICDH, COX and CS) were negatively associated with glycolytic characteristics (MyHC-IIx+b and LDH) for a majority of animal types.

For the eight animal types studied, ICDH activity was correlated with the proportion of slow oxidative fibres, MyHC-I. These results are coherent with earlier results showing that MyHC-I proportions may be appropriate to characterise the muscle in terms of oxidative capacity in pigs [START_REF] Gil | The relationship between pig genetics, myosin heavy chain I, biochemical traits and quality of M. Longissimus thoracis[END_REF], cattle [START_REF] Olivan | Effect of muscular hypertrophy on physico-chemical, biochemical and texture traits of meat from yearling bulls[END_REF], rabbits [START_REF] Ramirez | Effect of selection for growth rate on biochemical, quality and texture characteristics of meat from rabbits[END_REF], and sheep [START_REF] Sazili | The relationship between slow and fast myosin heavy chain content, calpastatin and meat tenderness in different ovine skeletal muscles[END_REF]. Overall, results are coherent with existing knowledge on the associations between metabolic and contractile characteristics of muscle fibres, but apart from the correlation between ICDH activity and MyHC-I proportions, many variations existed within the animal types. The relatively weak explanatory power of muscle characteristics is in accordance with other studies [START_REF] Keith | Chemical and sensory properties of thirteen major beef muscles[END_REF]Chriki et al. 2012b;[START_REF] Bonny | Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles[END_REF].

The comparison between the analyses within animal types and the analysis on average values of animal types indicates that although overall, similar biological laws operate in the eight animal types, when looked at in details, the precise balance between enzymes may be regulated differently according to animal type. For example, PFK and CS activities were strongly negatively correlated when average values of animal types were used but this correlation was not found within animal types, suggesting that these enzymes are not directly causally related. The negative association between LDH and ICDH observed in some of the animal types may be explained by the competition relative to the fate of pyruvate, conversion into lactate or entrance into the citric acid cycle. The absence of consistent correlations between two traits may be also related to the fixed effects. For example, PFK and LDH activities were not correlated when average values were used, because bull breeds had much higher PFK activity but similar LDH activity compared to the other breeds.

Correlations between sensory qualities within animal types or using averages per animal type associated high beef flavour, high tenderness and high overall liking. Beef flavour and juiciness were correlated when average values of animal types were used, but not within any of the animal types, suggesting that meat from certain animal types (i.e., heifers, steers and Ho bulls) had more beef flavour and was juicier but that there was no causal link between the two traits. The significant correlations show a strong consistency in the determinism of overall liking across animal types and suggest that flavour may be as important as tenderness in determining overall liking for fresh beef steaks as also previously indicated [START_REF] Mottram | Flavour formation in meat and meat products: A review[END_REF][START_REF] Monson | Influence of breed and ageing time on the sensory meat quality and consumer acceptability in intensively reared beef[END_REF]. No relationship was found between overall liking and juiciness. These findings are consistent with a previous study, which found tenderness and flavour to be the most important attributes in beef eating quality by UK consumers while juiciness had a relatively low impact [START_REF] Glitsch | Consumer perceptions of fresh meat quality: Cross-national comparison[END_REF]. In contrast, a previous study on bulls found that overall liking was associated with tenderness and flavour, but also with juiciness [START_REF] Monson | Influence of breed and ageing time on the sensory meat quality and consumer acceptability in intensively reared beef[END_REF].

In contrast to overall liking, the determinism of tenderness in terms of other sensory attributes showed little consistency when animal types were considered separately. The only correlation showing some consistency was between tenderness and juiciness: for three animal types, CF steers and AF and BF heifers. Similar results were earlier reported [START_REF] Serra | Eating quality of young bulls from three Spanish beef breed-production systems and its relationships with chemical and instrumental meat quality[END_REF][START_REF] Oury | Interrelationships between meat quality traits, texture measurements and physicochemical characteristics of M. rectus abdominis from Charolais heifers[END_REF][START_REF] Gagaoua | Relationships between overall liking score and sensory meat attributes in different types of beef cattle[END_REF]). These animal types had higher tenderness and juiciness scores than the other animal types. Possibly, at higher levels of tenderness and juiciness, the perceptions of tenderness and juiciness reinforce each other mutually. Meat juiciness is considered to arise from moisture released by meat during chewing, and moisture from saliva [START_REF] Juarez | Beef quality attributes as affected by increasing the intramuscular levels of vitamin E and omega-3 fatty acids[END_REF].

The negative association between tenderness and abnormal beef flavour observed for bulls may be related to the halo effect, i.e., the perceived level of a sensory quality is influenced by another sensory quality [START_REF] Gill | Consistency statistics and genetic parameters for taste panel assessed meat quality traits and their relationship with carcass quality traits in a commercial population of Angus-sired beef cattle[END_REF]. In bulls, abnormal beef flavour scores were relatively high compared to heifers and steers.

Correlations between muscle characteristics and sensory qualities were weak within and inconsistent across animal types. In contrast, high CS activities, high IMF contents and low PFK activities were very good predictors for good tenderness and overall liking, but only when average values of animal types were used. These correlations were, however, inconsistent with correlations within animal types. Thus, the relationships between high tenderness and overall liking, and high CS activities and IMF contents and low PFK activities were, at least in part, only indirect. The associations found in the regression models were, albeit weak, coherent with earlier studies. For example, tenderness was slightly better in meat from young bulls containing more MyHC-IIa, from steers with higher CS activity and from heifers with lower LDH activity. This is coherent with earlier studies showing positive correlations between LT tenderness and proportions of slow oxidative fibres [START_REF] Renand | Relationships between muscle characteristics and meat quality traits of young Charolais bulls[END_REF]Chriki et al. 2012a). [START_REF] Zamora | Predicting variability of ageing and toughness in beef M. Longissimus lumborum et thoracis[END_REF] found a positive relationship between myofibre resistance and CS activity. However, other studies found negative [START_REF] Ozawa | The characteristics of muscle fiber types of longissimus thoracis muscle and their influences on the quantity and quality of meat from Japanese Black steers[END_REF], or little or no correlations [START_REF] Vestergaard | Influence of feeding intensity, grazing and finishing feeding on muscle fibre characteristics and meat colour of semitendinosus, longissimus dorsi and supraspinatus muscles of young bulls[END_REF].

IMF content was retained in several explanatory models of tenderness and overall liking; the only meaningful contribution of IMF content was to overall liking in the young bulls, where it reached 9%. For comparison, [START_REF] Wheeler | Effect of marbling degree on beef palatability in Bos taurus and Bos indicus cattle[END_REF] who evaluated 1 667 cattle and [START_REF] Bonny | Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles[END_REF] who evaluated 6 muscles from 36 cattle found that IMF explained at most 5 to 6% of the variation in palatability traits. Recently, another study conducted by our group found no effect of IMF on the tenderness score in LT muscle of young bulls and cows [START_REF] Chriki | Meta-analysis of the relationships between beef tenderness and muscle characteristics[END_REF].

Total collagen content had a weak negative effect on overall liking both in heifers and steers. Although negative associations between total collagen content and overall liking and tenderness were earlier reported, these associations existed only across but not within muscles, suggesting that in contrast to our study, in these studies, there was no direct causal relationship, but rather an effect of muscle [START_REF] Schonfeldt | Effect of age and cut on tenderness of South African beef[END_REF][START_REF] Bonny | Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles[END_REF].

Finally, pHu was weakly correlated with tenderness in steers. Earlier reports indicated that ultimate pH may influence meat quality including flavour, juiciness and tenderness [START_REF] Mottram | Flavour formation in meat and meat products: A review[END_REF][START_REF] Calkins C R | A fresh look at meat flavor[END_REF][START_REF] Boudjellal | Is the pH drop profile curvilinear and either monophasic or polyphasic? Consequences on the ultimate bovine meat texture[END_REF]. The absence of relationships for heifers and bulls may be related to the narrow range of ultimate pH in these animal groups (5.50 to 5.62).

Conclusion

Overall, across animal types, markers of oxidative metabolism and slow contractile fibres, and increased IMF content were strongly associated with higher tenderness and overall liking of the LT muscle. Within animal types or genderss, the biological indicators varied and the associations were much weaker. For example, in heifers, higher tenderness was associated with lower LDH activity and in steers with higher CS activity. These differences and the weak correlations illustrate the multifactorial nature of the determinism of tenderness and overall liking [START_REF] Renand | Relationships between muscle characteristics and meat quality traits of young Charolais bulls[END_REF][START_REF] Purslow | Intramuscular connective tissue and its role in meat quality[END_REF]Gagaoua et al. 2015b). In addition, associated characteristics may have opposite effects. For example, animal types with higher proportions of oxidative fibres (I and IIa) had higher tenderness but higher proportions of MyHC-IIa were associated with higher total collagen content, which reduced tenderness. Thus, a given characteristic such as high proportions of a given fibre type may produce contrasting effects on sensory qualities. Multiple and partly opposite effects add to the complexity of the determinism of sensory qualities and may explain the relatively strong effects of animal type in the present study.

In conclusion, when considering average values per animal type, the present results show strong associations between increased tenderness and overall liking, and oxidative and slow contracting muscle fibre characteristics of the LT muscle. However, to understand and predict meat quality at the level of the individual animal based on muscle characteristics, the animal characteristics need to be taken into account, including breed, gender and undoubtedly also, age.

Fig. 1

 1 Fig. 1 Correlation graphs to illustrate associations between means per animal type of cytochrome c oxidase (COX) activities and ultimate pH (pHu, A) and phosphofructokinase (PFK) activities and tenderness (B). AF, Aberdeen Angus×Friesian; BF, Belgian-Blue×Friesian; BA, Blond d'Aquitaine; Li, Limousin; Ho, Holstein; AA, Aberdeen Angus; BH, Belgian-Blue×Holstein; CF, Charolais×Friesian. The same as below.

Fig. 2

 2 Fig. 2 Principal component (PC) analysis using all studied variables related to beef quality and muscle characteristics. A, loadings on the first two principal axes: ■, collagen characteristics; •, sensory quality attributes; ▲, metabolic characteristics as indicated by glycolytic and oxidative enzymes; ♦, MyHC isoforms; x, intramuscular fat content; and Ж, pHu. B, individual scores averaged per animal type (breed× gender/site) for the first two axes. The width and height of each oval represent the standard error of the mean for the first and second axis, respectively. C, mean scores per animal type on the 1st (top) and 2nd (bottom) axis of the PCA. An overall MSA (Kaiser's Measure of Sampling Adequacy) of 0.75 was obtained after removal of the variable MyHC-IIa which had the lowest MSA value (MSA=0.32). ColTot, total collagen; ColIns, insoluble collagen; PFK, phosphofructokinase; LDH, lactate dehydrogenase; ICDH, isocitrate dehydrogenase; COX, cytochrome c oxidase; CS, citrate synthase; MyHC-, myosin heavy chain-I, and -IIx+b; IMF, intramuscular fat content; T, tenderness; JUIC, juiciness; BF, beef flavour; ABF, abnormal beef flavour; OL, overall liking for m. Longissimus thoracis samples. The same as below.

AAFig. 3

 3 Fig. 3 Correlation network representing consistent correlations between muscle characteristics (A) and sensory qualities (B).Positive correlations are represented by a continuous line; negative correlations are represented by a dotted line. The animal types for which the correlation was significant are indicated next to the arrow. If "all" is indicated, the correlation was significant for all animals. The values next to the arrows represent the regression coefficients calculated using Z-scores including only the animal types for which the correlation was significant.

Table 1

 1 Effect of animal type on muscle characteristics and sensory qualities of Longissimus thoracis muscle

	Traits 1)

Table 2

 2 Correlations between means per animal type

	A Muscle characteristics
	Variables	LDH	PFK	ICDH	COX	CS	Total collagen	Insoluble collagen	MyHC-I MyHC-IIa MyHC-IIx/b
	PFK	-0.01
	ICDH	-0.52	-0.57
	COX	-0.92	-0.28	0.72
	CS	0.02	-0.98	0.62	0.28
	Total collagen	-0.67	0.09	0.36	0.54	-0.10
	Insoluble collagen	-0.73	0.16	0.41	0.60	-0.17	0.98
	MyHC-I	-0.81	-0.02	0.51	0.86	0.00	0.18	0.31
	MyHC-IIa	-0.57	0.16	0.33	0.53	-0.27	0.62	0.71	0.50
	MyHC-IIx+b	0.77	-0.10	-0.47	-0.77	0.18	-0.50	-0.62	-0.82	-0.90
	Ultimate pH	-0.87	-0.28	0.59	0.95	0.27	0.32	0.40	0.91	0.41	-0.72
	IMF 1)	0.26	-0.62	0.21	-0.04	0.48	-0.33	-0.34	-0.01	0.20	-0.13
	B Sensory qualities
	Attributes	Tenderness		Juiciness		Beef flavour	Abnormal beef flavour
	Juiciness		0.76
	Beef flavour		0.90		0.86
	Abnormal beef flavour		0.19		0.54			0.56
	Overall liking		0.84		0.50			0.81		0.28
	C Sensory qualities and muscle characteristics
		LDH	PFK	ICDH	COX	CS	IMF	Insoluble collagen	Total collagen	Ultimate pH
	Tenderness	0.04	-0.92	0.69	0.29	0.90	0.72	-0.21	-0.20	0.29
	Juiciness	0.14	-0.45	0.61	0.13	0.44	0.62	-0.25	-0.34	0.14
	Beef flavour	-0.15	-0.72	0.87	0.41	0.71	0.60	0.05	0.01	0.35
	Abnormal beef flavour	-0.31	0.06	0.71	0.35	0.03	-0.21	0.39	0.28	0.22
	Overall liking	-0.45	-0.84	0.85	0.70	0.85	0.42	0.12	0.12	0.66
	1) IMF, intramuscular fat.
	Significant correlations (P<0.05) are shown in bold characters.

Table 3

 3 Regression analyses (optimal models) per gender between sensory qualities and muscle characteristics including withingender breed effects

	Constant	μ	1st term	Equation terms (SD) 1) 2nd term	3rd term	Partial adjusted R-square (%) Significance Total adjusted R-square (%) 1st term 2nd term 3rd term
	Tenderness
	Heifers	8.5	-2.39 (0.28) LDH	-	-	6.6 **	-	-	6.6 **
	Bulls	3.2 +0.02 (0.23) MyHC-IIa	-	-	4.6 *	-	-	4.6 *
	Steers	14.1	-1.02 (0.54) BH Breed -1.88 (0.30) pHu	+0.40	14.9 ***	6.9 **	6 *	27.8 ***
						(0.31) CS
	Z-scores all		+0.16 CS		+0.13 MyHC-IIa +0.13 IMF	2.1 *	1.4 *	1.3 *	4.8 **
	animal types 2)
	Overall liking
	Heifers	5.0	+0.61 (0.37) AF Breed -0.27 (0.25) Total	-	13.8 ***	5.4 **	-	19.2 ***
					collagen
	Bulls	3.0	+0.24 (0.24) IMF	-	-	9.0 **	-	-	9 **
	Steers	7.6	-1.02 (0.54) BH Breed -0.17 (0.24) Total	-	35.5 ***	4.0 *	-	39.5 ***
					collagen
	Z-scores all		-0.17 (0.24)	+0.13 IMF	-	4.8 **	2.4 **	-	7.2 **
	animal types		Total collagen
	1)

Acknowledgements

This study was conducted within the framework of the EU Project ProSafeBeef (FOOD-CT-2006-36241) with INRA (Institut National de la Recherche Agronomique, France) Quality Assurance number AQ284. The authors thank the colleagues of the Aberystwyth University (UK), Farm Animal Biology, Germany (FBN), Teagasc (Ireland), Bristol University (England), and INRA (France) for their assistance in data collection, the management and slaughter of animals, muscle sampling, biochemical and sensory analyses. They further thank Université Frères Mentouri Constantine and the INATAA Institute, Algeria and the PROFAS B+ program for the financial support given to Dr. Mohammed Gagaoua.