Beef Tenderness Prediction by a Combination of Statistical Methods: Chemometrics and Supervised Learning to Manage Integrative Farm-To-Meat Continuum Data

Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China

Forty-one apple samples from 7 geographical regions and 3 botanical origins in China were investigated. A total of 29 volatile compounds have been identified by flash GC E-nose. They are 17 esters, 5 alcohols, 3 aldehydes, 1 ketone, and 3 others. A principal component analysis was employed to study the relationship between varieties and volatiles. A partial least squares discriminant analysis (PLS-DA), stepwise linear discriminant analysis (SLDA), and decision tree (DT) are used to discriminate apples from 4 geographical regions (34 apple samples) and 3 botanical origins (36 apple samples). The most influential markers identified by PLS-DA are 2-hexadecanone, methyl decanoate, tetradecanal, 1,8-cineole, hexyl 2-butenoate, (Z)-2-octenal, methyl 2-methylbutanoate, ethyl butyrate, dimethyl trisulfide, methyl formate, ethanol, S(-)2-methyl-1-butanol, ethyl acetate, pentyl acetate, butyl butanoate, butyl acetate, and ethyl octanoate. From the present work, SLDA reveals the best discrimination results in geographical regions and botanical origins, which are 88.2% and 88.9%, respectively. Although machine learning DT is attempted to classify apple samples, the results are not satisfactory.

Ultrasound as a Potential Technology to Improve the Quality of Meat Produced from a Mexican Autochthonous Bovine Breed

The objective of this study was to evaluate the effect of high-intensity ultrasound (HIU) on the physicochemical and textural properties of meat from Rararumi Criollo, a Mexican autochthonous bovine breed. After slaughter, Longissimus dorsi and Triceps brachii muscles were separated from carcasses, cut into 2.5 cm slices and treated with HIU, except the control group, which was not sonicated. After treatment, samples were vacuum-sealed and stored at 4 °C for 0, 3, 6, 9, 12 and 15 d. HIU increased (p < 0.05) the luminosity and yellowness (b*) of meat. Higher b* (p < 0.05) was observed in L. dorsi than in T. brachii muscles. No effect (p > 0.05) of HIU was detected on drip loss, pH, the water holding capacity and the total collagen of meat. The shear force of HIU-treated meat was lower (p < 0.05) than control samples, indicating a tenderizing effect. There were differences between muscles. L. dorsi was more tender (p < 0.05), and it had higher pH and WHC values than T. brachii. Overall, HIU is a potential method for tenderizing Raramuri Criollo cattle meat without negative impacts on other quality characteristics. HIU is an emerging technology that could add value to indigenous breeds and provide a new opportunity for the growing meat market.

Dark-cutting beef: A brief review and an integromics meta-analysis at the proteome level to decipher the underlying pathways

Comprehensive characterization of the post-mortem muscle proteome defines a fundamental goal in meat proteomics. During the last decade, proteomics tools have been applied in the field of foodomics to help decipher factors underpinning meat quality variations and to enlighten us, through data-driven methods, on the underlying mechanisms leading to meat quality defects such as dark-cutting meat known also as dark, firm and dry (DFD) meat. In cattle, several proteomics studies have focused on the extent to which changes in the post-mortem muscle proteome relate to dark-cutting beef development. The present data-mining study firstly reviews proteomics studies which investigated dark-cutting beef, and secondly, gathers the protein biomarkers that differ between dark-cutting versus beef with normal-pH in a unique repertoire. A list of 130 proteins from eight eligible studies was curated and mined through bioinformatics for Gene Ontology annotations, molecular pathways enrichments, secretome analysis and biological pathways comparisons to normal beef color from a previous meta-analysis. The major biological pathways underpinning dark-cutting beef at the proteome level have been described and deeply discussed in this integromics study.

Myosin sensitivity to thermal denaturation explains differences in water loss and shrinkage during cooking in muscles of distinct fibre types

The effect of thermal protein denaturation on the structure and quality of muscles of different fibre types is not well understood. Unaged masseter (100% type I fibres) and cutaneous trunci (93% type II fibres) muscles (N = 10) were assessed for their characteristics, protein denaturation, cooking loss, Warner- Bratzler shear force (WBSF) and shrinkage after heating at 50 °C - 85 °C with a rate of 5 °C/ min. Raw masseter had a higher pH, collagen and water content, shorter sarcomere, comparable fibre diameter, and shorter and wider fragments upon homogenization, than cutaneous trunci. In cutaneous trunci, at 55 °C - 60 °C, the lower transition temperature of myosin and the greater cumulative enthalpy resulted in greater cooking loss in muscle cuboids, and greater transverse, longitudinal and volume shrinkage in fibres and fibre fragments, than in masseter. Protein denaturation explained 71% variability in fibre fragment volume and 58% in cooking loss of both muscles, as well as 47% variability in WBSF of masseter.

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.

Molecular signatures of beef tenderness: Underlying mechanisms based on integromics of protein biomarkers from multi-platform proteomics studies

Over the last two decades, proteomics have been employed to decipher the underlying factors contributing to variation in the quality of muscle foods, including beef tenderness. One such approach is the application of high-throughput protein analytical platforms in the identification of meat quality biomarkers. To broaden our understanding about the biological mechanisms underpinning meat tenderization across a large number of studies, an integromics study was performed to review the current status of protein biomarker discovery targeting beef tenderness. This meta-analysis is the first to gather and propose a comprehensive list of 124 putative protein biomarkers derived from 28 independent proteomics-based experiments, from which 33 robust candidates were identified worthy of evaluation using targeted or untargeted data-independent acquisition proteomic methods. We further provide an overview of the interconnectedness of the main biological pathways impacting tenderness determination after multistep analyses including Gene Ontology annotations, pathway and process enrichment and literature mining, and specifically discuss the major proteins and pathways most often reported in proteomics research.

Protein Array-Based Approach to Evaluate Biomarkers of Beef Tenderness and Marbling in Cows: Understanding of the Underlying Mechanisms and Prediction

This study evaluated the potential of a panel of 20 protein biomarkers, quantified by Reverse Phase Protein Array (RPPA), to explain and predict two important meat quality traits, these being beef tenderness assessed by Warner-Bratzler shear force (WBSF) and the intramuscular fat (IMF) content (also termed marbling), in a large database of 188 Protected Designation of Origin (PDO) Maine-Anjou cows. Thus, the main objective was to move forward in the progression of biomarker-discovery for beef qualities by evaluating, at the same time for the two quality traits, a list of candidate proteins so far identified by proteomics and belonging to five interconnected biological pathways: (i) energy metabolic enzymes, (ii) heat shock proteins (HSPs), (iii) oxidative stress, (iv) structural proteins and (v) cell death and protein binding. Therefore, three statistical approaches were applied, these being Pearson correlations, unsupervised learning for the clustering of WBSF and IMF into quality classes, and Partial Least Squares regressions (PLS-R) to relate the phenotypes with the 20 biomarkers. Irrespective of the statistical method and quality trait, seven biomarkers were related with both WBSF and IMF, including three small HSPs (CRYAB, HSP20 and HSP27), two metabolic enzymes from the oxidative pathway (MDH1: Malate dehydrogenase and ALDH1A1: Retinal dehydrogenase 1), the structural protein MYH1 (Myosin heavy chain-IIx) and the multifunctional protein FHL1 (four and a half LIM domains 1). Further, three more proteins were retained for tenderness whatever the statistical method, among which two were structural proteins (MYL1: Myosin light chain 1/3 and TNNT1: Troponin T, slow skeletal muscle) and one was glycolytic enzyme (ENO3: β-enolase 3). For IMF, two proteins were, in this trial, specific for marbling whatever the statistical method: TRIM72 (Tripartite motif protein 72, negative) and PRDX6 (Peroxiredoxin 6, positive). From the 20 proteins, this trial allowed us to qualify 10 and 9 proteins respectively as strongly related with beef tenderness and marbling in PDO Maine-Anjou cows.

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.