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

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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Genetic improvement of meat quality traits in pigs

10.31274/rtd-180813-13231 ◽

2004 ◽

Author(s):

Douglas Wyatt Newcom

Keyword(s):

Meat Quality ◽

Genetic Improvement ◽

Quality Traits ◽

Meat Quality Traits

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

Journal of Animal Science and Biotechnology ◽

10.1186/s40104-021-00555-5 ◽

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.

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Prediction of meat quality traits in the abattoir using portable and hand-held near-infrared spectrometers

Meat Science ◽

10.1016/j.meatsci.2019.108017 ◽

2020 ◽

Vol 161 ◽

pp. 108017 ◽

Cited By ~ 10

Author(s):

Simone Savoia ◽

Andrea Albera ◽

Alberto Brugiapaglia ◽

Liliana Di Stasio ◽

Alessandro Ferragina ◽

...

Keyword(s):

Meat Quality ◽

Near Infrared ◽

Quality Traits ◽

Meat Quality Traits

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Guaranteeing Canadian lamb meat quality using near-infrared spectroscopy on intact rack

Canadian Journal of Animal Science ◽

10.1139/cjas-2017-0106 ◽

2018 ◽

Vol 98 (2) ◽

pp. 390-393 ◽

Cited By ~ 2

Author(s):

M. Juárez ◽

A. Horcada ◽

N. Prieto ◽

J.C. Roberts ◽

M.E.R. Dugan ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Meat Quality ◽

Near Infrared Spectroscopy ◽

Prediction Accuracy ◽

Near Infrared ◽

Quality Traits ◽

Meat Quality Traits ◽

Lamb Meat ◽

Predicted Values

Lamb racks from commercial carcasses were scanned using near-infrared spectroscopy. The prediction accuracies (R2) for meat quality traits were assessed. Prediction accuracy ranged between 0.40 and 0.94. When predicted values were used to classify meat based on quality, 88.7%–95.2% of samples were correctly classified as quality guaranteed.

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Genetic and phenotypic characterisation of animal, carcass, and meat quality traits from temperate and tropically adapted beef breeds. 3. Meat quality traits

Australian Journal of Agricultural Research ◽

10.1071/ar02087 ◽

2003 ◽

Vol 54 (2) ◽

pp. 135 ◽

Cited By ~ 50

Author(s):

D. J. Johnston ◽

A. Reverter ◽

D. M. Ferguson ◽

J. M. Thompson ◽

H. M. Burrow

Keyword(s):

Meat Quality ◽

Shear Force ◽

Genetic Correlations ◽

Cooking Loss ◽

Objective Measures ◽

Phenotypic Variance ◽

Quality Traits ◽

Genetic Expression ◽

Meat Quality Traits ◽

Meat Colour

Meat quality measures, including objective measures of tenderness (shear force and compression), were taken on 2 muscles [M. longissimus thoracis et lumborum (LTL) and M. semitendinosus (ST)] from 7566 carcasses from temperate (TEMP) and tropically adapted (TROP) beef cattle breeds. Animals were finished to 1 of 3 market carcass weight end-points (220, 280, or 340 kg) either on pasture or in a feedlot, and in 2 different geographic regions for TROP. Both the phenotypic and genetic expression of the traits were estimated at each market weight and for each finishing regime. Heritabilities and correlations between the traits were estimated for TEMP and TROP separately. Smaller additive variances and heritabilities were observed for temperate breeds compared with tropically adapted breeds for most of the traits studied. For TROP, the heritability of traits measured on the ST muscle [compression (ST_C), shear force (ST_SF), and L* Minolta lightness value (ST_L*)] was 0.27, 0.42, and 0.16, respectively, and for traits measured on the LTL muscle [compression (LTL_C), shear force (LTL_SF), L* Minolta lightness value (LTL_L*), a* Minolta redness value (LTL_a*), cooking loss% (LTL_CL%), and consumer assessed tenderness score (LTL_TEND)] 0.19, 0.30, 0.18, 0.13, 0.20, and 0.31, respectively. For TEMP, the heritability of traits measured on the ST muscle [ST_C, ST_SF, ST_L*, a* Minolta redness value (ST_a*), cooking loss % (ST_CL%)] was 0.12, 0.11, 0.17, 0.13, and 0.15, respectively, and of traits measured on the LTL muscle (LTL_C, LTL_SF, LTL_L, and LTL_TEND) were 0.08, 0.09, 0.17 and 0.18 respectively. Genetic correlations were moderate to high for tenderness measures (shear force and compression) between muscles for the same tenderness measure (e.g. LTL_SF and ST_SF was 0.46 for TROP) and within a muscle for the different measures (e.g. ST_C and ST_SF was 0.83 for TROP). Phenotypic and genetic correlations between LTL_L* and all objective measures of tenderness were negative (e.g. LTL_SF and LTL_L* for TROP was –0.40). The genetic relationship between LTL_SF and LTL_TEND was –0.79 and –0.49 for TROP and TEMP, respectively. Finishing system affected the phenotypic expression of all traits. Pasture-finished, compared with feedlot-finished, animals had higher shear force and compression measures, darker meat colour, and lower sensory tenderness scores for both TEMP and TROP. For TROP, heifers had higher shear force and compression measures, lower sensory tenderness scores, and darker meat colour (lower L* values) than steers. Genetic correlations between markets were generally high and close to unity with the exception of the ST_L*, LTL_L*, ST_C, and ST_SF for TEMP. Geographic region had little effect on the phenotypic and genetic expression of meat quality traits for TROP. Genetic correlations between finishing regimes for all traits were positive and close to unity, with the exception of ST_C and LTL_SF for TEMP, and LTL_L* and LTL_CL% for TROP. Genetic improvement of meat quality traits is a possibility for tropically adapted breeds given the moderate heritabilities, adequate phenotypic variance, generally favourable genetic correlations between traits, and little evidence of genotype by environment interactions.

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The relevance of different near infrared technologies and sample treatments for predicting meat quality traits in commercial beef cuts

Meat Science ◽

10.1016/j.meatsci.2012.09.013 ◽

2013 ◽

Vol 93 (2) ◽

pp. 329-335 ◽

Cited By ~ 22

Author(s):

M. De Marchi ◽

M. Penasa ◽

A. Cecchinato ◽

G. Bittante

Keyword(s):

Meat Quality ◽

Near Infrared ◽

Quality Traits ◽

Meat Quality Traits

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Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers

Canadian Journal of Animal Science ◽

10.4141/cjas-2014-038 ◽

2014 ◽

Vol 94 (4) ◽

pp. 545-556 ◽

Cited By ~ 6

Author(s):

Jennifer L. Aalhus ◽

Óscar López-Campos ◽

Nuria Prieto ◽

Argenis Rodas-González ◽

Michael E. R. Dugan ◽

...

Keyword(s):

Meat Quality ◽

Near Infrared ◽

Economic Value ◽

Database Systems ◽

Quality Traits ◽

Meat Quality Traits ◽

Yield And Quality ◽

On Line ◽

Additional Value ◽

Near Future

Aalhus, J. L., López-Campos, Ó., Prieto, N., Rodas-González, A., Dugan, M. E. R., Uttaro, B. and Juárez, M. 2014. Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers. Can. J. Anim. Sci. 94: 545–556. Beef value is in the eye, mouth or mind of the consumer; however, currently, producers are paid on the basis of carcass grade. In general, affluent consumers are becoming more discerning and are willing to pay for both credence and measureable quality differences. The Canadian grading system for youthful carcasses identifies both lean yield and quality attributes, whereas mature carcasses are broadly categorized. Opportunities exist to improve the prediction of lean meat yield and better identify meat quality characteristics in youthful beef, and to obtain additional value from mature carcasses through muscle profiling. Individual carcass identification along with development of database systems like the Beef InfoXchange System (BIXS) will allow a paradigm shift for the industry as traits of economic value can be easily identified to improve marketing value chains. In the near future, developing technologies (e.g., grade cameras, dual energy X-ray absorptiometry, and spectroscopic methods such as near infrared spectroscopy, Raman spectroscopy and hyperspectral imaging) will be successfully implemented on-line to identify a multitude of carcass and quality traits of growing importance to segments of the consuming population.

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Trait-specific Selection Signature Detection Reveals Novel Loci of Meat Quality in Large White Pigs

Frontiers in Genetics ◽

10.3389/fgene.2021.761252 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yu Shen ◽

Haiyan Wang ◽

Jiahao Xie ◽

Zixuan Wang ◽

Yunlong Ma

Keyword(s):

Candidate Genes ◽

Meat Quality ◽

Genetic Improvement ◽

Genetic Basis ◽

Muscle Development ◽

Fixation Index ◽

Quality Traits ◽

Selection Signatures ◽

Meat Quality Traits ◽

Improvement Programs

In past decades, meat quality traits have been shaped by human-driven selection in the process of genetic improvement programs. Exploring the potential genetic basis of artificial selection and mapping functional candidate genes for economic traits are of great significance in genetic improvement of pigs. In this study, we focus on investigating the genetic basis of five meat quality traits, including intramuscular fat content (IMF), drip loss, water binding capacity, pH at 45 min (pH45min), and ultimate pH (pH24h). Through making phenotypic gradient differential population pairs, Wright’s fixation index (FST) and the cross-population extended haplotype homozogysity (XPEHH) were applied to detect selection signatures for these five traits. Finally, a total of 427 and 307 trait-specific selection signatures were revealed by FST and XPEHH, respectively. Further bioinformatics analysis indicates that some genes, such as USF1, NDUFS2, PIGM, IGSF8, CASQ1, and ACBD6, overlapping with the trait-specific selection signatures are responsible for the phenotypes including fat metabolism and muscle development. Among them, a series of promising trait-specific selection signatures that were detected in the high IMF subpopulation are located in the region of 93544042-95179724bp on SSC4, and the genes harboring in this region are all related to lipids and muscle development. Overall, these candidate genes of meat quality traits identified in this analysis may provide some fundamental information for further exploring the genetic basis of this complex trait.

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