Estimation of Genetic Parameters for Peak Yield, Yield and Persistency Traits in Murciano-Granadina Goats Using Multi-Traits Models

This paper studies parameters of a lactation curve such as peak yield (PY) and persistency (P), which do not conform to the usual selection criteria in the Murciano-Granadina (MG) breed, but are considered to be an alternative to benefit animal welfare without reducing production. Using 315,663 prod...

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Published in:Animals (Basel) Vol. 9; no. 7; p. 411
Main Authors: Miranda, Judith C, León, José M, Pieramati, Camillo, Gómez, Mayra M, Valdés, Jesús, Barba, Cecilio
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 01-07-2019
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Summary:This paper studies parameters of a lactation curve such as peak yield (PY) and persistency (P), which do not conform to the usual selection criteria in the Murciano-Granadina (MG) breed, but are considered to be an alternative to benefit animal welfare without reducing production. Using 315,663 production records (of 122,883 animals) over a period of 24 years (1990-2014), genetic parameters were estimated with uni-, bi- and multivariate analysis using multiple trait derivative free restricted maximum likelihood (MTDFREML). The heritability (h )/repeatability (r ) of PY, yield (Y) and P was estimated as 0.13/0.19, 0.16/0.25 and 0.08/0.09 with the uni-trait and h of bi- and multi-traits analysis ranging from 0.16 to 0.17 of Y, while that of PY and Y remained constant. Genetic correlations were high between PY-Y (0.94 ± 0.011) but low between PY-P (-0.16 ± 0.054 to -0.17 ± 0.054) and between Y-P (-0.06 ± 0.058 to -0.05 ± 0.058). Estimates of h /r were low to intermediate. The selection for Y-PY or both can be implemented given the genetic correlation between these traits. PY-P and Y-P showed low to negligible correlation values indicating that if these traits are implemented in the early stages of evaluation, they would not be to the detriment of PY-Y. The combination of estimated breeding values (EBVs) for all traits would be a good criterion for selection.
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ISSN:2076-2615
2076-2615
DOI:10.3390/ani9070411