scholarly journals PSIV-37 Development of a genomic selection strategy to include meat quality traits in turkeys (Meleagris gallopavo).

2018 ◽  
Vol 96 (suppl_3) ◽  
pp. 133-134
Author(s):  
R Vanderhout ◽  
B Wood ◽  
S Barbut ◽  
C Baes
Keyword(s):  
Genomic Selection ◽  
Meat Quality ◽  
Meleagris Gallopavo ◽  
Selection Strategy ◽  
Quality Traits ◽  
Meat Quality Traits

scholarly journals Genomic Approaches Reveal Pleiotropic Effects in Crossbred Beef Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Fernanda M. Rezende ◽  
Eduardo Rodriguez ◽  
Joel D. Leal-Gutiérrez ◽  
Mauricio A. Elzo ◽  
Dwain D. Johnson ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Genomic Selection ◽  
Meat Quality ◽  
Additive Genetic Variance ◽  
Cytoskeletal Proteins ◽  
Pleiotropic Effects ◽  
Genome Wide Association Studies ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Genomic Regions

Carcass and meat quality are two important attributes for the beef industry because they drive profitability and consumer demand. These traits are of even greater importance in crossbred cattle used in subtropical and tropical regions for their superior adaptability because they tend to underperform compared to their purebred counterparts. Many of these traits are challenging and expensive to measure and unavailable until late in life or after the animal is harvested, hence unrealistic to improve through traditional phenotypic selection, but perfect candidates for genomic selection. Before genomic selection can be implemented in crossbred populations, it is important to explore if pleiotropic effects exist between carcass and meat quality traits. Therefore, the objective of this study was to identify genomic regions with pleiotropic effects on carcass and meat quality traits in a multibreed Angus–Brahman population that included purebred and crossbred animals. Data included phenotypes for 10 carcass and meat quality traits from 2,384 steers, of which 1,038 were genotyped with the GGP Bovine F-250. Single-trait genome-wide association studies were first used to investigate the relevance of direct additive genetic effects on each carcass, sensory and visual meat quality traits. A second analysis for each trait included all other phenotypes as covariates to correct for direct causal effects from identified genomic regions with pure direct effects on the trait under analysis. Five genomic windows on chromosomes BTA5, BTA7, BTA18, and BTA29 explained more than 1% of additive genetic variance of two or more traits. Moreover, three suggestive pleiotropic regions were identified on BTA10 and BTA19. The 317 genes uncovered in pleiotropic regions included anchoring and cytoskeletal proteins, key players in cell growth, muscle development, lipid metabolism and fat deposition, and important factors in muscle proteolysis. A functional analysis of these genes revealed GO terms directly related to carcass quality, meat quality, and tenderness in beef cattle, including calcium-related processes, cell signaling, and modulation of cell–cell adhesion. These results contribute with novel information about the complex genetic architecture and pleiotropic effects of carcass and meat quality traits in crossbred beef cattle.

Genomic selection for meat quality traits in Pekin duck

2021 ◽  
Author(s):  
F. Zhang ◽  
F. Zhu ◽  
F.‐X. Yang ◽  
J.‐P. Hao ◽  
Z.‐C. Hou
Keyword(s):  
Genomic Selection ◽  
Meat Quality ◽  
Pekin Duck ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Selection For

scholarly journals Berücksichtigung der Fleischqualität bei der Selektion innerhalb Linien beim Schwein – eine Studie

2001 ◽  
Vol 44 (5) ◽  
pp. 531-546
Author(s):  
J. Krieter ◽  
E. Tholen
Keyword(s):  
Meat Quality ◽  
Selection Index ◽  
Economic Value ◽  
Population Level ◽  
Intramuscular Fat ◽  
Selection Strategy ◽  
Quality Traits ◽  
Population Mean ◽  
Meat Quality Traits ◽  
The Relationship

Abstract. Title of the paper: Selection for meat quality within pure bred lines in swine – a study The main criticism of the operators at the present final products concern the variance in valuable cuts and meat quality traits and the absence of any favourable attributes. The paper reviews traits which can be used to determine pig meat quality in terms of methods, genetic parameters, economic importance and selection response (index, QTL). Heritability estimates of meat quality traits from the literature and own analyses show low or moderate values. In halothane negative populations heritabilities are diminished which is also true for the correlations between meat quality and carcass traits. The relationship among intramuscular fat and sensoric attributes is in general low so the role of intramuscular fat for sensoric aspects should not be overestimated. The economic values for most quality depend on the population level and the monetary evaluation. Due to the optimum values for most quality traits the relationship between population mean and valuation is nonlinear. Using different hypothetical payment system the economic value for IMF is calculated. The results show that only in the situation where the population mean is close to the optimum of 2.5 % a high economic value for IMF can be justified. Finally improving meat quality by selection index and QTL-information is discussed. The future selection strategy should focus on halothan negative lines (using MHS-information) due to the minimization of meat failure and reduction of variance in carcass and meat quality traits. At present the inclusion of further traits (e.g. intramuscular fat) is not indicated. Requirements for special market segments can performed using complementary levels of different breeds.

Genomic selection for meat quality traits in Nelore cattle

Meat Science ◽  
2019 ◽  
Vol 148 ◽  
pp. 32-37 ◽  
Author(s):  
Ana Fabrícia Braga Magalhães ◽  
Flavio Schramm Schenkel ◽  
Diogo Anastácio Garcia ◽  
Daniel Gustavo Mansan Gordo ◽  
Rafael Lara Tonussi ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Meat Quality ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Selection For ◽  
Nelore Cattle

Association analysis between CMYA5 gene and meat quality traits in Hunan black pig

2013 ◽  
Vol 38 (1) ◽  
pp. 64-68
Author(s):  
Ji ZHU ◽  
Jian LIU ◽  
Jian-bang SUN ◽  
Shi-liu YANG ◽  
Jing-ru LI ◽  
...  
Keyword(s):  
Meat Quality ◽  
Association Analysis ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
I Gene

scholarly journals Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Simone Savoia ◽  
Andrea Albera ◽  
Alberto Brugiapaglia ◽  
Liliana Di Stasio ◽  
Alessio Cecchinato ◽  
...  
Keyword(s):  
Meat Quality ◽  
Near Infrared ◽  
External Validation ◽  
Genetic Correlations ◽  
Genetic Selection ◽  
Quality Traits ◽  
Eye Muscle ◽  
Meat Quality Traits ◽  
Color Traits ◽  
Selection Of

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.

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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera
Keyword(s):  
Meat Quality ◽  
Genetic Improvement ◽  
Near Infrared ◽  
Infrared Region ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Infrared Spectral ◽  
Portable Spectrometers ◽  
Absorbance Spectra

AbstractSpectroscopic 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.

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