Predicting the Quality of Meat: Myth or Reality?

Metabolomics Changes in Meat and Subcutaneous Fat of Male Cattle Submitted to Fetal Programming

This study investigated changes in meat and subcutaneous fat metabolomes and possible metabolic pathways related to prenatal nutrition in beef cattle. For this purpose, 18 Nellore bulls were used for meat sampling and 15 for fat sampling. The nutritional treatments during the gestation were: NP-not programmed or control, without protein-energy supplementation; PP-partially programmed, with protein-energy supplementation (0.3% of body weight (BW)) only in the final third of pregnancy; and FP-full programming, with protein-energy supplementation (0.3% of BW) during the entire pregnancy. The meat and fat samples were collected individually 24 h after slaughter, and the metabolites were extracted using a combination of chemical reagents and mechanical processes and subsequently quantified using liquid chromatography or flow injection coupled to mass spectrometry. The data obtained were submitted to principal component analysis (PCA), analysis of variance (ANOVA), and functional enrichment analysis, with a significance level of 5%. The PCA showed an overlap between the treatments for both meat and fat. In meat, 25 metabolites were statistically different between treatments (p ≤ 0.05), belonging to four classes (glycerophospholipids, amino acids, sphingolipids, and biogenic amine). In fat, 10 significant metabolites (p ≤ 0.05) were obtained in two classes (phosphatidylcholine and lysophosphatidylcholine). The functional enrichment analysis showed alterations in the aminoacyl-tRNA pathway in meat (p = 0.030); however, there was no pathway enriched for fat. Fetal programming influenced the meat and fat metabolomes and the aminoacyl-tRNA metabolic pathway, which is an important candidate for the biological process linked to meat quality and related to fetal programming in beef cattle.

Effects of maternal calcium propionate supplementation on offspring productivity and meat metabolomic profile in sheep

This study determined the effect of dietary calcium propionate (CaPr) as a source of energy supplementation during the First Half of Gestation (FMG), the Second Half of Gestation (SMG), and during All Gestation (AG), on offspring post-weaning growth performance, meat quality, and meat metabolomic profile. Thirty-one pregnant ewes were assigned to one of four treatments: a) supplementation of 30 gd-1 of CaPr during the first half of gestation (day 1 to day 75, n = 8) (FMG); b) supplementation of 30 gd-1 of CaPr during the second half of gestation (day 76 to day 150, n = 8) (SMG); c) supplementation of 30 gd-1 of CaPr during all gestation (AG, n = 8); d) no CaPr supplementation (control; CS, n = 7). The ewes were ad libitum fed a basal diet based on oat hay and corn silage. Ewes were distributed in a completely randomized unbalanced design to four treatments. The FMG group had lower (P ≤ 0.05) birth weight and weaning weight than the CS group. However, the average daily gain was similar across all treatments. Empty body weight and FMG had lower values (P ≤ 0.05) than the other groups. Both FMG and AG had lower hot carcass weight (P ≤ 0.05) compared to CS, while CaPr treatments resulted in reduced hot carcass yield (P ≤ 0.05). Meat color and texture were similar among treatments. A principal component analysis between gestation stages showed a trend for separating CS and FMG from SMG and AG, and that was explained by 93.7% of the data variability (PC1 = 87.9% and PC2 = 5.8%). Regarding meat metabolomic profile, 23 compounds were positively correlated between all treatments. Only 2 were negatively correlated (eicosane and naphthalene 1,2,3); but tetradecanoic acid, hexadecane, undecane 5-methyl, (-)-alpha, hexadecenoic acid, octadecanoic acid, and octadecane had a highly significant correlation (P ≤ 0.05). Overall, dam supplementation with CaPr during different periods of gestation provoked changes in meat metabolites related to the biosynthesis of fatty acids in lambs without negative changes in lamb's growth performance and carcass quality.

- Invited Review - Postmortem skeletal muscle metabolism of farm animals approached with metabolomics

Skeletal muscle metabolism regulates homeostatic balance in animals. The metabolic impact persists even after farm animal skeletal muscle is converted to edible meat through postmortem rigor mortis and aging. Muscle metabolites resulting from animal growth and postmortem storage have a significant impact on meat quality, including flavor and color. Metabolomics studies of postmortem muscle aging have identified metabolisms that contain signatures inherent to muscle properties and the altered metabolites by physiological adaptation, with glycolysis as the pivotal metabolism in postmortem aging. Metabolomics has also played a role in mining relevant postmortem metabolisms and pathways, such as the citrate cycle and mitochondrial metabolism. This leads to a deeper understanding of the mechanisms underlying the generation of key compounds that are associated with meat quality. Genetic background, feeding strategy, and muscle type primarily determine skeletal muscle properties in live animals and affect post-mortem muscle metabolism. With comprehensive metabolite detection, metabolomics is also beneficial for exploring biomarker candidates that could be useful to monitor meat production and predict the quality traits. The present review focuses on advances in farm animal muscle metabolomics, especially postmortem muscle metabolism associated with genetic factors and muscle type.

Technological properties, chemical composition, texture profile, and sensory evaluation of goose muscles from Polish native breeds

The study aimed to determine the technological and sensory properties of the breast and thigh muscles of geese from the Polish native varieties: Kartuska (Ka) and Suwalska (Su) (from northern Poland) as well as Lubelska (Lu) and Kielecka (Ki) (from southern Poland). The color parameters: L*, a*, b*, ΔE, C, h°, total heme pigments (THPs), and share of myoglobin (Mb), metmyoglobin (MMb), and oxymyoglobin (MbO₂) in muscles were determined. In terms of technological properties, the following were determined: pH₂₄, water-binding capacity (WBC), water-holding capacity (WHC), cooking (CL), and roasting losses (RL). In addition, a sensory evaluation of the raw meat color was performed. In roasted meat, a sensory evaluation and texture profile analysis (TPA) were carried out, as well as the shear force (SF) and chemical composition were determined. Roasted muscles of varieties native to northern Poland (Ka and Su) were higher in lipids (P≤0.05) than the muscles of southern varieties (Lu and Ki). Ka meat had the highest protein content, and Lu meat had the lowest (P≤0.05). The raw muscle color sensory evaluation results, the THP, and the L* and ΔE values indicated that the darkest color among the studied genotypes were the Ka muscles, and the lightest was Ki meat (P≤0.05). Lu's muscles are distinguished by better usability for processing and culinary purposes than the muscles of the other genotypes due to high pH₂₄, WBC, WHC, and low RL and CL of thigh muscles, as well as high WHC and low RLs of the breast muscles (P≤0.05). Due to the tenderness, juiciness, and high general evaluation (P≤0.05), the best sensory features among the studied genotypes were found in the Ka breast and thigh muscles. The low SF value proved the higher tenderness of Ka geese muscles.

Comparisons of carcass traits, meat quality, and serum metabolome between Shaziling and Yorkshire pigs

This study aims to compare the meat quality of Shaziling and Yorkshire pigs and to find the potential indicator in serum for superior meat quality. Six Shaziling and Yorkshire pigs at 30, 60, 90, 150, 210, and 300 d of age were selected to examine carcass traits, meat quality, and serum metabolome. The results showed that the body weight, carcass length, and loin eye area of Shaziling pigs at 150, 210, and 300 d of age were significantly lower than those of Yorkshire pigs (P < 0.05). Shaziling pigs at 150 and 300 d of age had significantly lower backfat thickness than Yorkshire pigs (P < 0.05). Compared with Yorkshire pigs, Shaziling pigs at all 6 ages had a lower lean percentage and a higher fat percentage (P < 0.05). At 60, 90, and 150 d of age, the post-mortem pH-decline, b∗ value (yellowness), and drip loss of Shaziling pigs were significantly lower than those of Yorkshire pigs (P < 0.05). Moreover, at 150 d of age, Shaziling pigs had significantly higher a∗ value (redness) and intramuscular fat (IMF) content than Yorkshire pigs (P < 0.05). Correlation analysis between the top 40 metabolites and phenotypes indicated that L-carnitine had positive correlations with fat percentage, pH_24h, and IMF content, but had negative correlations with lean percentage, L∗ value (lightness), and b∗ value (P < 0.05). Serum L-carnitine content, fat percentage, pH_24h, and IMF content all decreased first and then increased as the pigs grew, which verified the positive correlations between L-carnitine and these phenotypes. In conclusion, Shaziling pigs have a slower growth rate but a better meat quality than Yorkshire pigs. The meat quality of Shaziling pigs is the best from 150 to 210 d of age. This study suggests that a higher serum L-carnitine content is a promising indicator for better meat quality.

Review: Quality of animal-source foods

This article critically reviews the current state of knowledge on the quality of animal-source foods according to animal production and food processing conditions, including consumer expectations-behaviours and the effects of consumption of animal-source foods on human health. Quality has been defined through seven core attributes: safety, commercial, sensory, nutritional, technological, convenience, and image. Image covers ethical, cultural and environmental dimensions associated with the origin of the food and the way it is produced and processed. This framework enabled to highlight the priorities given to the different quality attributes. It also helped to identify potential antagonisms and synergies among quality attributes, between production and processing stages, and among stakeholders. Primacy is essentially given to commercial quality attributes, especially for standard commodity animal-source foods. This primacy has strongly influenced genetic selection and farming practices in all livestock commodity chains and enabled substantial quantitative gains, although at the expense of other quality traits. Focal issues are the destructuration of chicken muscle that compromises sensory, nutritional and image quality attributes, and the fate of males in the egg and dairy sectors, which have heavily specialised their animals. Quality can be gained but can also be lost throughout the farm-to-fork continuum. Our review highlights critical factors and periods throughout animal production and food processing routes, such as on-farm practices, notably animal feeding, preslaughter and slaughter phases, food processing techniques, and food formulation. It also reveals on-farm and processing factors that create antagonisms among quality attributes, such as the castration of male pigs, the substitution of marine-source feed by plant-based feed in fish, and the use of sodium nitrite in meat processing. These antagonisms require scientific data to identify trade-offs among quality attributes and/or solutions to help overcome these tensions. However, there are also food products that value synergies between quality attributes and between production and processing phases, particularly Geographical Indications, such as for cheese and dry-cured ham. Human epidemiological studies have found associations between consumption of animal-source foods and increased or decreased risk for chronic non-communicable diseases. These associations have informed public health recommendations. However, they have not yet considered animal production and food processing conditions. A concerted and collaborative effort is needed from scientists working in animal science, food process engineering, consumer science, human nutrition and epidemiology in order to address this research gap. Avenues for research and main options for policy action are discussed.

Applications of Biosensors for Meat Quality Evaluations

The aim of this study was to apply biosensors in the assessment of meat quality. The research was carried out on 20 samples of the Longissimus muscle obtained from pork of Polish Landrace and Polish Large White hybrids of fattening pigs. In the samples, 48 h after slaughter pH values, color parameters in the CIE system (L* a* b*), the volume of natural drip loss and intramuscular fat content were measured. The commercially available biosensor Accutrend Plus was used to measure glucose, triglycerides and lactic acid in meat juice. Significant (p ≤ 0.05) relationships between glucose, triglycerides, lactic acid levels and pork quality characteristics, i.e., pH (r = -0.62; r = -0.78; r = -0.68 respectively), natural drip loss and (r = 0.57; r = 0.58; r = 0.49), color parameters as L*, a* and b* (r = from 0.47 to 0.79) were demonstrated. The study showed a negative correlation between the intramuscular fat content and acidification of muscle tissue (r = -0.49), and a positive one with the brightness of color (r = 0.46). The results of the canonical analysis show that the measurement of all three metabolites in muscle juice allows the evaluation of the technological quality of meat with an accuracy of 86.54% (Rc = 0.93, p < 0.01).

Review: Improving the nutritional, sensory and market value of meat products from sheep and cattle

This paper focuses on improving the sensory, health attributes and meat yield of beef and lamb meats. Value for meat is defined as the weight of meat × price/kg received with price linked to eating quality. To maximise value across the supply chain, accurate carcass grading systems for eating quality and yield are paramount. Grading data can then be used to target consumers' needs at given price points and then to tailor appropriate production and genetic directions. Both the grading methodologies and key phenotypes are complex and still under intensive research with international collaboration to maximise opportunities. In addition, there is value in promoting the health aspects of red meats served as whole trimmed meats. Typically, the total fat content is relatively low (less than 5%) and for forage systems, they deliver a very significant content of long-chain n-3 fatty acids. Further research is needed to clarify the healthiness or otherwise of ground beef served as burgers given the fat content is typically 20% or more. It is important to continue to improve the feedback to producers regarding the quantity and quality of the products they produce to target new value opportunities in a transparent and quantitative manner.

Electronic Tongue as a Correlative Technique for Modeling Cattle Meat Quality and Classification of Breeds

Discrimination and species identification of meat has always been of paramount importance in the European meat market. This is often achieved using different conventional analytical methods but advanced sensor-based methods, such as the electronic tongue (e-tongue), are also gaining attention for rapid and reliable analysis. The aim of this study was to discriminate Angus, domestic buffalo, Hungarian Grey, Hungarian Spotted cattle, and Holstein beef meat samples from the chuck steak part of the animals, which mostly contained longissimus dorsi muscles, using e-tongue as a correlative technique with conventional methods for analysis of pH, color, texture, water activity, water-holding capacity, cooking yield, water binding activity, and descriptive sensory analysis. Analysis of variance (ANOVA) was used to determine significant differences between the measured quality traits of the five-meat species after analysis with conventional analytical methods. E-tongue data were visualized with principal component analysis (PCA) before classifying the five-meat species with linear discriminant analysis (LDA). Significant differences were observed among some of the investigated quality parameter. In most cases, Hungarian Grey was most different from the other species. Using e-tongue, separation patterns could be observed in the PCA that were confirmed with 100% recognition and 97.5% prediction of all the different meat species in LDA.

Phenotypic and genetic variation of ultraviolet-visible-infrared spectral wavelengths of bovine meat

Spectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet-visible and near-infrared region (UV-Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV-Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV-Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.

Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background

The study aimed to investigate possible systematic effects in the basic underlying variability of individual metabolomic data. In this context, the extent of gender- and genotype-dependent differences reflected in the metabolic composition of three tissues in fattening pigs was determined. The 40 pigs belonged to the genotypes PIx(LWxGL) and PIxGL with gilts and boars, respectively. Blood and tissue samples from M. longissimus dorsi and liver were directly taken at the slaughtering plant and directed to GC × GC qMS metabolite analysis. Differences were observed for various metabolite classes like amino acids, fatty acids, sugars, or organic acids. Gender-specific differences were much more pronounced than genotype-related differences, which could be due to the close genetic relation of the fattening pigs. However, the metabolic dimorphism between gilts and boars was found to be genotype-dependent, and vice versa metabolic differences between genotypes were found to be gender-dependent. Most interestingly, integration into metabolic pathways revealed different patterns for carbon (C) and nitrogen (N) usage in boars and gilts. We suppose a stronger N-recycling and increased energy metabolism in boars, whereas, in gilts, more N is presumably excreted and remaining carbon skeletons channeled into lipogenesis. Associations of metabolites to meat quality factors confirmed the applicability of metabolomics approaches for a better understanding about the impact of drivers (e.g., gender, age, breed) on physiological processes influencing meat quality. Due to the huge complexity of the drivers-traits-network, the derivation of independent biomarkers for meat quality prediction will hardly be possible.

Performance of different portable and hand-held near-infrared spectrometers for predicting beef composition and quality characteristics in the abattoir without meat sampling

The availability of portable and handheld NIR instruments on the market opens up new possibilities in meat analysis. However, there is lack of research comparing different NIR instruments for evaluating beef characteristics from spectra obtained directly on the meat surface. Our aim, therefore, was to build and test calibration and prediction models for predicting beef characteristics, and to compare the performances of three NIR instruments differing in size and characteristics: a transportable visible-NIR spectrometer (Vis-NIRS), a portable (NIRS), and a hand-held Micro-NIRS. Spectra were collected from 178 beef samples (Longissimus thoracis muscle) from the meat surface in the abattoir. The spectra were subjected to different mathematical pretreatments then partial least square regressions. The results showed that all instruments predicted dry matter, protein and lipids with R²_VAL 0.23 to 0.70; pH and cooking loss R²_VAL 0.19 to 0.25; and color R²_VAL 0.35 to 0.77. Overall, the prediction performances of the three instruments were similar, although Micro-NIRS performed better in some respects.

Identification of Meat Quality Determining Marker Genes in Fibroblasts of Bovine Muscle Using Transcriptomic Profiling

In the present study, we comparatively analyzed the transcriptomic profiling of fibroblasts derived from two different muscles, biceps femoris and longissimus dorsi with significant difference in the meat quality and tenderness. EBSeq algorithm was applied to analyze the data, and genes were considered to be significantly differentially expressed if the false discovery rate value was <0.05, the P value was <0.01, and the fold change was >0.585. The results revealed that 253 genes were differentially expressed genes (DEGs) (170 genes were upregulated, and 83 were downregulated) and more than 100 DEGs were probably associated with intramuscular fat deposition, tenderness, and toughness, which are driving the meat quality and were involved in biological processes such as collagen synthesis, cell differentiation, and muscle tissue and fiber development; molecular functions such as chemokine activity and collagen activity; cellular components such as cytoplasm and myofibril; and pathways such as collagen signaling and metabolic pathways. A gene-act network and a co-expression network revealed the close relationship between intramuscular fat deposition and meat tenderness. The expressions of 20 DEGs were validated by real-time PCR, and the results suggested that the DEGs are correlated with RNA-seq data and play crucial roles in muscle growth, development processes, toughness, and tenderness of the meat. Together, the genome-wide transcriptome analysis revealed that various genes are responsible for toughness and tenderness variance in the difference muscles of beef.

Invited review: Beef-on-dairy-The generation of crossbred beef × dairy cattle

Because a growing proportion of the beef output in many countries originates from dairy herds, the most critical decisions about the genetic merit of most carcasses harvested are being made by dairy producers. Interest in the generation of more valuable calves from dairy females is intensifying, and the most likely vehicle is the use of appropriately selected beef bulls for mating to the dairy females. This is especially true given the growing potential to undertake more beef × dairy matings as herd metrics improve (e.g., reproductive performance) and technological advances are more widely adopted (e.g., sexed semen). Clear breed differences (among beef breeds but also compared with dairy breeds) exist for a whole plethora of performance traits, but considerable within-breed variability has also been demonstrated. Although such variability has implications for the choice of bull to mate to dairy females, the fact that dairy females themselves exhibit such genetic variability implies that "one size fits all" may not be appropriate for bull selection. Although differences in a whole series of key performance indicators have been documented between beef and beef-on-dairy animals, of particular note is the reported lower environmental hoofprint associated with beef-on-dairy production systems if the environmental overhead of the mature cow is attributed to the milk she eventually produces. Despite the known contribution of beef (i.e., both surplus calves and cull cows) to the overall gross output of most dairy herds globally, and the fact that each dairy female contributes half her genetic merit to her progeny, proxies for meat yield (i.e., veal or beef) are not directly considered in the vast majority of dairy cow breeding objectives. Breeding objectives to identify beef bulls suitable for dairy production systems are now being developed and validated, demonstrating the financial benefit of using such breeding objectives over and above a focus on dairy bulls or easy-calving, short-gestation beef bulls. When this approach is complemented by management-based decision-support tools, considerable potential exists to improve the profitability and sustainability of modern dairy production systems by exploiting beef-on-dairy breeding strategies using the most appropriate beef bulls.

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

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.

Relationships Between Fat and Cholesterol Contents and Fatty Acid Composition in Different Meat-Producing Animal Species

The objective of this study was to determine the relationships between intramuscular fat, cholesterol contents and fatty acid composition in the muscles of different animal species. Intramuscular fat, cholesterol and fatty acid composition in 207 muscle samples from 129 animals of different species (pigs, beef cattle, farmed red deer, horses and geese) were determined and analysed. The obtained results indicated unequal relations between intramuscular fat and cholesterol contents and fatty acid proportions in the muscles of different animal species. The increase of intramuscular fat content resulted in higher monounsaturated and lower polyunsaturated fatty acid contents in most muscles of meat producing animals. In all the species higher fatness did not show any increase in cholesterol content and also cholesterol contents were lower as fat increased in m. semimembranosus of pigs and m. pectoralis profundus of horses. The cholesterol content positively correlated with saturated and monounsaturated fatty acids in the longissimus muscle with the lowest fat content found in red deer and beef cattle, whereas the correlations between these measures were negative in m. pectoralis profundus of horses and the breast of goose containing high fat levels. Negative correlations between polyunsaturated fatty acids and cholesterol content were found in the longissimus muscle of red deer and cattle, whereas these correlations in goose breast and horse meat were positive.

Near-Infrared Spectroscopy as a Beef Quality Tool to Predict Consumer Acceptance

This study was conducted to evaluate the feasibility of using near-infrared spectroscopy (NIRS) to predict beef consumers’ perceptions. Photographs of 200 raw steaks were taken, and NIRS data were collected (transmittance and reflectance). The steak photographs were used to conduct a face-to-face survey of 400 beef consumers. Consumers rated beef color, visible fat, and overall appearance, using a 5-point Likert scale (where 1 indicated “Dislike very much” and 5 indicated “Like very much”), which later was simplified in a 3-point Likert scale. Factor analysis and structural equation modeling (SEM) were used to generate a beef consumer index. A partial least square discriminant analysis (PLS-DA) was used to predict beef consumers’ perceptions using NIRS data. SEM was used to validate the index, with root mean square errors of approximation ≤0.1 and comparative fit and Tucker–Lewis index values <0.9. PLS-DA results for the 5-point Likert scale showed low prediction (accuracy < 42%). A simplified 3-point Likert scale improved discrimination (accuracy between 52% and 55%). The PLS-DA model for purchasing decisions showed acceptable prediction results, particularly for transmittance NIRS (accuracy of 76%). Anticipating beef consumers’ willingness to purchase could allow the beef industry to improve products so that they meet consumers’ preferences.

Metabolites and Metabolic Pathways Correlated With Beef Tenderness

Metabolite profile has been used to understand the causes of variability in beef tenderness, but still little is known about how metabolites contribute to beef quality. Therefore, this study was carried out to evaluate how meat metabolites and their metabolic pathways correlate to variability in beef tenderness. Carcasses from 60 noncastrated male cattle were selected, and three 2.5-cm-thick longissimus thoracis steaks were obtained and aged (0°C to 4°C) for 7d. Warner-Bratzler shear force (WBSF) was performed (steak 1). Based on WBSF data, 2 tenderness classes (n = 30; 15 per class [tender and tough]) were created to perform sarcomere length (steak 2) and metabolom ic analysis (steak 3). Meat ultimate pH did not differ between tenderness classes. However, steaks classified as tender had greater sarcomere length (P = 0.019) than those classified as tough. Acetyl-carnitine (P = 0.026), adenine (P = 0.026), beta-alanine (P = 0.005), fumarate (P = 0.022), glutamine (P = 0.043), and valine (P = 0.030) concentration were higher in tender beef compared with tough beef. The 4 most important compounds differing between tender and tough beef were lactate, glucose, creatine, and glutamine, which may indicate that metabolic pathways such as D-glutamine and D-glutamate metabolism, beta-alanine metabolism, purine metabolism, and tricarboxylic acid cycle affected the tenderness classes. Beta-alanine (r = − 0.45), acetyl-carnitine (r = − 0.40), fumarate (r = − 0.38), valine (r = − 0.34), glucose (r = − 0.32), glutamine (r = − 0.31), and adenine (r = −0.31) were negatively correlated with WBSF values. Metabolite profile in tender beef indicated a greater oxidative metabolism, which promoted modifications in the muscle structure and proteolysis, favoring its tenderization.

MEATabolomics: Muscle and Meat Metabolomics in Domestic Animals

In the past decades, metabolomics has been used to comprehensively understand a variety of food materials for improvement and assessment of food quality. Farm animal skeletal muscles and meat are one of the major targets of metabolomics for the characterization of meat and the exploration of biomarkers in the production system. For identification of potential biomarkers to control meat quality, studies of animal muscles and meat with metabolomics (MEATabolomics) has been conducted in combination with analyses of meat quality traits, focusing on specific factors associated with animal genetic background and sensory scores, or conditions in feeding system and treatments of meat in the processes such as postmortem storage, processing, and hygiene control. Currently, most of MEATabolomics approaches combine separation techniques (gas or liquid chromatography, and capillary electrophoresis)-mass spectrometry (MS) or nuclear magnetic resonance (NMR) approaches with the downstream multivariate analyses, depending on the polarity and/or hydrophobicity of the targeted metabolites. Studies employing these approaches provide useful information to monitor meat quality traits efficiently and to understand the genetic background and production system of animals behind the meat quality. MEATabolomics is expected to improve the knowledge and methodologies in animal breeding and feeding, meat storage and processing, and prediction of meat quality.

Current Advances in Meat Nutritional, Sensory and Physical Quality Improvement

Meat is an important source of proteins, vitamins, minerals and fat, and these nutrients are important for their beneficial effects on human health. In recent years, meat quality has become a more relevant topic for consumers with regard to health and sensory characteristics, and for beef industry stakeholders because it affects their profitability. Therefore, the control of meat quality, including technological, sensory and nutritional quality traits, constitutes an important target for any farm animal production. What those qualities are and how we best evaluate them at the different levels of the continuum from the farm to fork are critical to understanding meat production and consumption patterns. However, despite the efforts of the industrials to control the eating and nutritional quality traits of meat and meat products, there remains a high level of variability, which is one reason for consumer dissatisfaction. This Special Issue focuses on the study of continuum aspects from farm to fork, which would have an impact on the control of the nutritional, sensory and technological aspects of carcass, muscle, meat and meat-product qualities. It groups fourteen original studies and one comprehensive review within five main topics that are (i) production systems and rearing practices, (ii) prediction of meat qualities, (iii) statistical approaches for meat quality prediction/management, (iv) muscle biochemistry and proteomics techniques and (v) consumer acceptability, development and characterisation of meat products.