Combined use of milk infrared spectra and genotypes can improve prediction of milk fat composition.
J Dairy Sci
; 103(3): 2514-2522, 2020 Mar.
Article
en En
| MEDLINE
| ID: mdl-31882213
ABSTRACT
It has been shown that milk infrared (IR) spectroscopy can be used to predict detailed milk fat composition. In addition, polymorphisms with substantial effects on milk fat composition have been identified. In this study, we investigated the combined use of milk IR spectroscopy and genotypes of dairy cows on the accuracy of predicting milk fat composition. Milk fat composition data based on gas chromatography and milk IR spectra were available for 1,456 Dutch Holstein Friesian cows. In addition, genotypes for the diacylglycerol acyltransferase 1 (DGAT1) K232A and stearoyl-CoA desaturase 1 (SCD1) A293V polymorphisms and a SNP located in an intron of the fatty acid synthase (FASN) gene were available. Adding SCD1 genotypes to the milk IR spectra resulted in a considerable improvement of the prediction accuracy for the unsaturated fatty acids C101, C121, C141 cis-9, and C161 cis-9 and their corresponding unsaturation indices. Adding DGAT1 genotypes to the milk IR spectra resulted in an improvement of the prediction accuracy for C161 cis-9 and C16 index. Adding genotypes of the FASN SNP to the IR spectra did not improve prediction of milk fat composition. This study demonstrated the potential of combining milk IR spectra with genotypic information from 3 polymorphisms to predict milk fat composition. We hypothesize that prediction accuracy of milk fat composition can be further improved by combining milk IR spectra with genomic breeding values.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Espectrofotometría Infrarroja
/
Bovinos
/
Leche
/
Grasas
/
Genotipo
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
J Dairy Sci
Año:
2020
Tipo del documento:
Article
País de afiliación:
Países Bajos