scholarly journals Effect of in ovo administration of different synbiotics on carcass and meat quality traits in broiler chickens

2019 ◽  
Vol 98 (1) ◽  
pp. 464-472 ◽  
Author(s):  
S. Tavaniello ◽  
R. Mucci ◽  
K. Stadnicka ◽  
O. Acaye ◽  
M. Bednarczyk ◽  
...  
Keyword(s):  
Meat Quality ◽  
Broiler Chickens ◽  
Quality Traits ◽  
In Ovo ◽  
Meat Quality Traits

scholarly journals Effect of galactooligosaccharides delivered in ovo on meat quality traits of broiler chickens exposed to heat stress

2020 ◽  
Vol 99 (1) ◽  
pp. 612-619 ◽  
Author(s):  
S. Tavaniello ◽  
A. Slawinska ◽  
D. Prioriello ◽  
V. Petrecca ◽  
M. Bertocchi ◽  
...  
Keyword(s):  
Heat Stress ◽  
Meat Quality ◽  
Broiler Chickens ◽  
Quality Traits ◽  
In Ovo ◽  
Meat Quality Traits

scholarly journals Mapping QTL for white striping in relation to breast muscle yield and meat quality traits in broiler chickens

BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Eva Pampouille ◽  
Cécile Berri ◽  
Simon Boitard ◽  
Christelle Hennequet-Antier ◽  
Stéphane A. Beauclercq ◽  
...  
Keyword(s):  
Meat Quality ◽  
Broiler Chickens ◽  
Breast Muscle ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Mapping Qtl ◽  
White Striping

scholarly journals The Influence of the Season and Market Class of Broiler Chickens on Breast Meat Quality Traits

2007 ◽  
Vol 86 (5) ◽  
pp. 959-963 ◽  
Author(s):  
M. Bianchi ◽  
M. Petracci ◽  
F. Sirri ◽  
E. Folegatti ◽  
A. Franchini ◽  
...  
Keyword(s):  
Meat Quality ◽  
Broiler Chickens ◽  
Quality Traits ◽  
Breast Meat ◽  
Meat Quality Traits ◽  
Market Class

scholarly journals Effect of Dietary-Liquid Resveratrol on Growth Performance, Meat Quality Traits, and Ileum Morphology of Broiler Chickens under Moderate Heat Stress

2016 ◽  
Vol 43 (1) ◽  
pp. 21-29
Author(s):  
Young-Joo Yi ◽  
Jaehong Yoo ◽  
S. Wickramasuriya Samiru ◽  
Eunjoo Kim ◽  
Bonjin Koo ◽  
...  
Keyword(s):  
Heat Stress ◽  
Growth Performance ◽  
Meat Quality ◽  
Broiler Chickens ◽  
Quality Traits ◽  
Meat Quality Traits

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.

Sign in / Sign up

Export Citation Format

Share Document