Influence of Post Mortem Muscle Activity on Turkey Meat Quality

Meat quality of turkeys after reproductive period depending on genotype and sex

With the increasing demand for animal protein, and poultry meat being the most consumed meat in the world, it was decided to perform a genotype- and gender-specific analysis of turkey meat quality. The study was conducted on 48 breast and 48 leg muscles of the two leading genotypes of reproductive turkeys B.U.T. 6 and Hybrid Converter (12 females and 12 males each) after reproductive period. Physicochemical analysis (acidity, electroconductivity, thermal leakage, color L*,a*,b*), basic chemical composition (protein, collagen, water, fat), and micro- and macronutrient content of pectoral muscle and leg muscle were performed. In addition, texture and structure analysis of the pectoralis major muscle was performed. Hybrid Converter's pectoral muscles had significantly (P < 0.05) higher fat, water, and iron content compared to B.U.T. 6 pectoral muscles. In comparison, the leg muscles of Hybrid Converter turkeys had a higher content of fat, collagen, sodium and phosphorus, and a lower content of protein, manganese and calcium compared to the analyzed features of the leg muscles of B.U.T. 6. Higher acidity (pH24) of pectoral and leg muscles and electro conductivity and horizontal fiber diameter of pectoral muscles were shown in B.U.T. 6 turkeys, while electrical conductivity and yellowness (b*) of leg muscles were higher in Hybrid Converter turkeys. In contrast, the pectoral muscles of males were characterized by significantly (P < 0.05) higher pH levels, protein and copper content, and lower water, collagen, potassium, phosphorus, sodium, calcium, thermal loss, and the parameter L*and a*. In contrast, the leg muscles of males were characterized by lower water, collagen, potassium, phosphorus, sodium, calcium, zinc, thermal leakage, and the color parameters a*, b*, and higher fat, chromium, copper, pH, and electrical conductivity. The sex of the birds also affected the texture (Warner-Bratzler shear force, chewiness, gumminess, cohesiveness, sum of elastic moduli) and structure (fiber cross-sectional area, fiber perimeter, vertical fiber diameter, horizontal fiber diameter) characteristics which were higher in males with the exception of sum of elastic moduli. Based on the above information, it can be concluded that the genotype of turkeys largely affects the basic chemical composition, acidity reaction, electrical conductivity, and content of some micro and macro elements of pectoral and leg muscles. The texture, texture, color, and thermal leakage characteristics of the above muscles were not affected by genotype except by the color b* leg muscles and horizontal fiber diameter. On the other hand, a greater effect of gender was observed, especially on the analyzed texture and structure characteristics of the pectoral muscle.

Transcriptomic and metabolomic-based revelation of the effect of fresh corn extract on meat quality of Jingyuan chicken

To investigate the effect of fresh corn extract (FCE) on chicken meat quality, 135-day-old Jingyuan chicken hens were fed diets containing different doses of FCE (CON, 0.3% FCE, 0.6% FCE and 0.9% FCE) until 180 day-old in this study. Meat performance measurements showed that the 0.6% FCE group of Jingyuan chickens had higher intramuscular fat (IMF), pressing loss (PL), amino acid and fatty acid contents (P < 0.05). Their breasts were collected for transcriptomic and metabolomic analyses (n=8), and 210 Differentially expressed genes (DEGs) and 29 Differentially expressed genes (DEMs) were obtained. Gene Ontology (GO) analyses of DEGs indicate multiple entries involved in IMF synthesis such as skeletal system development and cellular response to amino acid stimulation. Kyoto Encyclopedia of Genes and Genomes (GSEA-KEGG) analysis identified sphingolipid_metabolism and multiple genes affecting IMF deposition including SPHK1, CERS1, CERS6, GLB1L, SGMS2, UGT8, and UGCG. KEGG and metabolite correlation analyses of DEMs identified Aspartate, PI 38:5; PI(18:1/20:4), PI 36:3; PI(18:1/18:2), PI 36:2; PI(18:0/18:2), and PI 34:1; PI(16:0/18:1) as the likely major influences on IMF deposition in the DEMs. Correlation analysis revealed that shear force (SF) was significantly and positively correlated with Aspartate and CERS6; PL was significantly and positively correlated with SPHK1 and UGCG (P < 0.05). IMF was significantly and positively correlated with PI 34:1; PI (16:0/18:1), SPHK1 and UGCG; and flesh colour yellowness b* was significantly and positively correlated with SGMS2 (P < 0.05). The above results indicate that feeding a basal diet containing 0.6% FCE can improve the meat quality of Jingyuan chicken, which provides a theoretical basis for improving the meat quality of Jingyuan chicken.

Data-Mining Methodology to Improve the Scientific Production Quality in Turkey Meat and Carcass Characterization Studies

The present research aims to describe how turkey meat and carcass quality traits define the interest of the scientific community through the quality standards of journals in which studies are published. To this end, an analysis of 92 research documents addressing the study of turkey carcass and meat quality over the last 57 years was performed. Meat and carcass quality attributes were dependent variables and included traits related to carcass dressing, muscle fiber, pH, colorimetry, water-holding capacity, texture, and chemical composition. The independent variables comprised publication quality traits, including journal indexation, database, journal impact factor (JIF), quartile, publication area, and JIF percentage. For each dependent variable, a data-mining chi-squared automatic interaction detection (CHAID) decision tree was developed. Carcass or piece yield was the only variable that did not show an impact on the publication quality. Moreover, color and pH measurements taken at 72 h postmortem showed a negative impact on publication interest. On the other hand, variables including water-retaining attributes, colorimetry, pH, chemical composition, and shear force traits stood out among the quality-enhancing variables due to their low inclusion in papers, while high standards improved power.

Discriminant canonical analysis as a tool for genotype traceability testing based on turkey meat and carcass traits

The present study aims to develop a statistical tool for turkey breed traceability testing based on meat and carcass quality characteristics. To this end, a comprehensive meta-analysis was performed, collecting data from a total of 75 studies approaching meat and carcass attributes of 37 turkey strains and landraces since the late 1960s. A total of 22 meat and carcass traits were considered variables, grouped in the following clusters: carcass dressing traits, muscle fiber properties, pH, colorimetry, water-capacity traits, texture-related attributes, and nutritional composition of the meat. Once the multicollinearity analysis allowed the deletion of redundant variables, cold carcass weight, slaughter weight, muscle fiber diameter, sex-female, carcass/piece weight, meat redness, ashes, pH24, meat lightness, moisture, fat, and water-holding capacity showed explanatory properties in the discriminating analysis (p < 0.05). In addition, strong positive and negative correlations were found among those variables studied. Carcass traits were positively associated, particularly slaughter weight and cold carcass weight (+0.561). Among meat physical traits, pH showed positive correlations with drip loss (+0.490) and pH24 (+0.327), and water-holding capacity was positively associated with cholesterol (+0.434) and negatively associated with collagen (-0.398). According to nutritional traits, fat and ash showed a strong correlation (+0.595), and both were negatively associated with moisture (-0.375 and -0.498, respectively). Strong negative correlations were found as well between meat protein and fat (-0.460) and between collagen and cholesterol (-0.654). Finally, the Mahalanobis distance suggested a clustering pattern based on meat and carcass characteristics that report information about interbreeding and variety proximity. This study establishes a departure point in the development of a tool for breed traceability guaranteeing aimed at enhancing distinguished, local breed-based turkey meat.

Study of Meat and Carcass Quality-Related Traits in Turkey Populations through Discriminant Canonical Analysis

The present research aimed to determine the main differences in meat and carcass quality traits among turkey genotypes worldwide and describe the clustering patterns through the use of a discriminant canonical analysis (DCA). To achieve this goal, a comprehensive meta-analysis of 75 documents discussing carcass and meat characteristics in the turkey species was performed. Meat and carcass attributes of nine different turkey populations were collected and grouped in terms of the following clusters: carcass dressing traits, muscle fiber properties, pH, color-related traits, water-retaining characteristics, texture-related traits, and meat chemical composition. The Bayesian ANOVA analysis reported that the majority of variables statistically differed (p < 0.05), and the multicollinearity analysis revealed the absence of redundancy problems among variables (VIF < 5). The DCA reported that cold carcass weight, slaughter weight, sex-male, carcass/piece weight, and the protein and fat composition of meat were the traits explaining variability among different turkey genotypes (Wilks' lambda: 0.488, 0.590, 0.905, 0.906, 0.937, and 0.944, respectively). The combination of traits in the first three dimensions explained 94.93% variability among groups. Mahalanobis distances cladogram-grouped populations following a cluster pattern and suggest its applicability as indicative of a turkey genotype's traceability.

Describing the relationships among meat quality traits in domestic turkey (Meleagris gallopavo) populations

The presence of meat quality defects is increasing in the turkey industry. While the main strategy for mitigating these issues is through improved housing, management, and slaughter conditions, it may be possible to incorporate meat quality into a turkey breeding strategy with the intent to improve meat quality. Before this can occur, it is important to describe the current state of turkey meat quality as well as the correlations among the different meat quality traits and important production traits. The main objective of the present study was to provide a descriptive analysis of 8 different meat quality traits for turkey breast meat from 3 different purebred lines (A, B, and C), and their correlation with a selection of production traits. Using a total of 7,781 images, the breast meat (N = 590–3,892 birds depending on trait) was evaluated at 24 h postmortem for color (L*, a*, b*), pH, and physiochemical characteristics (drip loss, cooking loss, shear force). Descriptive statistics (mean and standard deviation) and Pearson correlations were computed to describe the relationships among traits within each genetic line. A one-factor ANOVA and post hoc t-test were conducted for each trait and between each of the genetic lines. We found significant differences between genetic lines for some color traits (L* and a*), pH_initial, drip loss, and cooking loss. The lightest line in weight (line B) had meat that was the lightest (L*) in color. The heaviest line (line C) had meat that was less red (a*) with a higher pH_initial and greater cooking loss. Unfavorable correlations between production traits and meat quality were also found for each of the genetic lines where increases in production (e.g., body weight, growth rate) resulted in meat that was lighter and redder in color and in some cases (line B and C), with an increased moisture loss. The results of this study provide an important benchmark for turkey meat quality in purebred lines and provide an updated account of the relationships between key production traits and meat quality. Although the magnitude of these correlations is low, their cumulative effect on meat quality can be more significant especially with continued selection pressure on growth and yield.