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Published on: December 16, 2015
Factors that influence the test day milk yield and composition
F G Silva1, L F Brito, R A Torres
1Departamento de Zootecnia, Universidade Federal de Viçosa, Viçosa, MG, Brasil. felipe.melhoramento@hotmail.com
Seasonal variations and goat age significantly impact milk production and composition. Understanding these factors is crucial for optimizing dairy goat management and breeding strategies.
Area of Science:
- Animal Science
- Dairy Science
- Goat Production
Background:
- Accurate assessment of dairy goat performance requires understanding factors influencing milk yield and composition.
- Previous studies have identified various influences, but breed-specific and seasonal effects warrant further investigation.
Purpose of the Study:
- To investigate factors affecting test day milk yield (TDMY) and milk constituents (protein, fat, lactose, total dry extract) in Alpine and Saanen goats.
- To analyze the influence of season, age at kidding, kidding order, and genetic grouping on milk production traits.
Main Methods:
- Utilized 110,732 weekly milk production records and 19,271 monthly milk constituent records from 1997-2010.
- Applied data filtering criteria including kidding order, number of kids, milk control year, genetic grouping, and lactation duration.
- Considered goats aged >300 days at calving and <6 years at control.
Main Results:
- Milk production was higher during the dry season compared to the rainy season.
- Test day milk yield (TDMY) increased with goat age at kidding but decreased with higher kidding order.
- Genetic grouping did not consistently influence all traits across both breeds; influencing factors varied between Alpine and Saanen breeds.
Conclusions:
- Seasonal effects and age at kidding are significant drivers of milk production and composition in dairy goats.
- Breed-specific analysis of influencing factors is essential for developing effective herd management and evaluation models.
- Understanding these variables is critical for optimizing dairy goat breeding programs and improving overall farm productivity.
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