Understanding the Determination of Meat Quality Using Biochemical Characteristics of the Muscle: Stress at Slaughter and Other Missing Keys

Abstract

Despite increasingly detailed knowledge of the biochemical processes involved in the determination of meat quality traits, robust models, using biochemical characteristics of the muscle to predict future meat quality, lack. The neglecting of various aspects of the model paradigm may explain this. First, preslaughter stress has a major impact on meat quality and varies according to slaughter context and individuals. Yet, it is rarely taken into account in meat quality models. Second, phenotypic similarity does not imply similarity in the underlying biological causes, and several models may be needed to explain a given phenotype. Finally, the implications of the complexity of biological systems are discussed: a homeostatic equilibrium can be reached in countless ways, involving thousands of interacting processes and molecules at different levels of the organism, changing over time and differing between animals. Consequently, even a robust model may explain a significant part, but not all of the variability between individuals.

Keywords: behavior; biochemistry; meat quality; modeling; physiology; postmortem muscle metabolism; proteomics; slaughter; stress.

Figure 1

Squares: Piétrain × (Large White × Landrace) pigs. Number of skin lesions, indicative of agonistic interactions during mixed lairage at the abattoir (18 h), were correlated with the pH 24 h postmortem of the Adductor femoris muscle (r = 0.89; p < 0.001). Adapted from [55,61], with permission from INRAE, 2020. Circles represent nonexisting hypothetical data from Hampshire pigs in which fighting is not expected to influence ultimate pH due to their high muscle glycogen content. If all points are combined irrespective of breed, the correlation is no longer significant showing the necessity to take influencing factors into account in the statistical model (see Section 3.1).

Figure 2

Faster heart rates are associated with faster early postmortem pH decline of the Semitendinosis muscle, explaining 34% of the variability between the individuals (r = 0.58; p = 0.0001). Rhombuses, squares and triangles represent Angus, Blond d’Aquitaine and Limousin young bulls, respectively. Reproduced from [38], with permission from Elsevier, 2020.

Figure 3

Duration of wing flapping significantly hastens the rate of early postmortem pH decline of fillets. Squares, circles, and triangles indicate broilers of a Standard (r = 0.80; p < 0.001), Label (r = 0.71; p < 0.001) and Heavy line (r = 0.66; p < 0.001), respectively. Slopes do not differ significantly (ANCOVA on pH 15 min postmortem; interaction line x duration of wing flapping: p = 0.51). Data from [71].

Figure 4

The way the animal evaluates its situation in slaughter (or other) contexts depends on the context itself and the genetic background (e.g., certain breeds or genetic types may be more reactive) and prior experiences of the animal (e.g., the experience an animal has with a certain situation influences the way it evaluates it). The context refers to the physiological state of the animal (e.g., fatigue, hunger, level of arousal, estrus) and its environment (e.g., presence of fear-inducing aspects). The way the animal evaluates its situation is related to its welfare state; the way it reacts to the preslaughter situation influences the qualities of its future meat. The effects of stress on meat quality also depend on the genetic and rearing background of the animal. Reproduced from [87], with permission from Elsevier, 2020.

Figure 5

The faster the heart rate response of young bulls of different breeds when exposed to a novel object (a closed umbrella) during a test during the rearing period, the less tender their meat (r = −0.59; p = 0.01). The tenderness scale goes from 0 (tough) to 10 (tender). Squares, circles and triangles represent Angus, Blonde d’Aquitaine and Limousine bulls, respectively. A faster heart response is indicative of increased fear reactions in unfamiliar situations. Heart rate data are from [38] and meat quality data from [88,89], who worked on the same animals. Adapted from [61], with permission from INRAE, 2020.

Figure 6

(A) Plasma cortisol levels of trout just before slaughter (bars where letters (a–c) differ have significantly different values (p < 0.0001)) and (B) relationship between calculated and measured pH just after slaughter: pH = 6.8 − 0.003 × slaughter order +0.1 × high reactivity +0.4 × No additional stress at slaughter −0.2 × high reactivity × No additional stress at slaughter. The equation explains 53.3% of the variability between individuals. Dark bars (A) and dark symbols (B) indicate slaughter following additional stress (15 min waiting in a tank with 20 cm depth of water). Triangles and circles indicate selection lines with high and low stress reactivity, respectively. Adapted from [61,81], with permission from INRAE, 2020 and Elsevier, 2020.

Figure 7

The slopes of correlations between the noradrenaline (NA) content of urine obtained just after slaughter and the pH of the Longissimus lumborum measured 24 h postmortem depended on the slaughter method. Pigs had been slaughtered either following mixing and transport to the abattoir the day before slaughter (light-gray symbols; pH = 5.02 + 0.00001 × NA; r = 0.92; p = 0.001) or without mixing, immediately following transport (dark-gray symbols; pH = 5.37 + 0.000003 × NA; r = 0.57; p = 0.14). The slopes differ p = 0.004 (ANCOVA on pH; NA content × slaughter method: p = 0.02). Data from [120] and adapted from [61], with permission from INRAE, 2020. Urinary noradrenaline reflects the amount of noradrenaline secreted into the blood over several tens of minutes preceding the sample collection [122].

Figure 8

Illustration of the concept that correlations may be reversed if multiple factors are involved in a phenomenon. (A) Semitendinosus (ST) muscles containing greater proportions of white fibers have greater potential to produce good-quality meat [113], (B,C) but are also more sensitive to the negative effects of stress; (B,D) ST muscles containing a greater proportion of oxidative fiber types have less potential to produce good-quality meat but are less sensitive to preslaughter stress. In this example, if we compare low-stress and high-stress slaughter conditions, the correlation between fiber type composition and meat quality is reversed if the negative effects of stress outweigh the positive effects of a high proportion of white fibers (A,B). The composition of the muscle in terms of fiber type determines whether stress has a measurable impact on meat quality (C,D). High preslaughter stress will influence the postmortem metabolism of any muscle. Adapted from [61], with permission from INRAE, 2020.

Figure 9

Example of correlation between muscle characteristics and beef quality traits. (A) Average values of phosphofructokinase (PFK; glycolytic enzyme) and tenderness score are strongly negatively correlated (r = −0.92; p < 0.0001) when using average values of different animal types. (B) However, when Z-scores are used, removing the effects of animal type, the correlation is nonexistent (r = −0.06; NS), indicating that PFK activity was not directly related to tenderness [88]. Animals were steers: 40 Belgian-Blue × Holstein (BH) and 32 Charolais crossbred (CF) reared in the United Kingdom; heifers: 47 Angus × Friesian (AF) and 47 Belgian-Blue × Friesian (BF) reared in Ireland; young bulls: 25 Holstein (HO) reared in Germany, and 24 Angus (AA), 25 Limousin (LI), and 25 Blond d’Aquitaine (BA) reared in France. Higher tenderness scores indicate greater tenderness.

Figure 10

Pig Semimembranosus (SM) slaughtered following gas stunning: relationship between the glycolytic potential 45 min postmortem (GP) and pH measured 24 h postmortem. The best logarithmic fit was ultimate pH = 8.40 − 65 × ln (GP), illustrated by the curved line (r = 0.69; p < 0.0001). The different symbols refer to pigs with different liver GP; circles: 10–39, squares: 40–99, triangles 100–170; rhombuses: 268–289 µmol/g fresh tissue; none of the pigs had values between 170 and 268 µmol/g. GP in muscle and liver was calculated from lactate, glucose and glycogen content, following [138]. The results illustrate that with GP below 80 µmol/g fresh tissue, ultimate pH rises. They also show that some of the pigs with low muscle glycogen had liver GP contents over 100 µmol/g. Hence, although liver glycogenolysis helps to replenish glucose, the remaining liver glycogen contents did not match SM muscle contents. This may be due to a combination of factors; for instance, resting liver glycogen contents may have varied, the rate of glycogenolysis may depend on additional factors, such as stress, or there may be a delay between need and actual glycogenolysis. The figure illustrates the heterogeneity of physiological adaptive responses. Adapted from [139], with permission from ADIV, 2020.

Figure 11

Example of disparity among beef studies on dark-cutting (Dark, Firm and Dry (DFD); ultimate pH > 6.0) Longissimus thoracis muscle using proteomics (Gagaoua, unpublished data). The seven selected proteomic studies reported in total 78 proteins, which were compared by means of a Cricos plot for overlap (A) and a heat map using the enriched gene ontology pathways for their functions (B). In the heat map, colors from gray to brown indicate p-values from high to low, and gray cells indicate the lack of significant enrichment. The two analyses based on the proteins or the biological pathways illustrate the little consistency among studies in terms of the identified proteins and pathways involved in the production of DFD meat in contrast to what is known for normal meat on the same muscle, i.e., normal color (Gagaoua et al. [126]) or tenderness (Gagaoua et al. [4]). This inconsistency indicates the existence of other influencing factors that need to be controlled in order to construct accurate and robust models (see Section 4: Conclusion).