PhD Defence: Lactation curve modelling in dairy production Applications at cow and herd level

PhD Defence of Y. Chen


Summary of dissertation

Various metrics have been proposed to evaluate milk production of dairy cows, like cumulative milk production and milk yield per day within a lactation period. These metrics are based on simple calculations on raw milk data. However, they provide an overview of milk production performance without capturing changes in milk production over a lactation period. These changes, or patterns offer more information (e.g., peak yield, peak time, persistency) about the lactation, which are useful for selective breeding, health monitoring, and other applications. Lactation curve models can extrapolate and quantify lactation curves and estimate actual production from incomplete data sets, generating lactation curve characteristics (LCC) to describe the curve in different ways. LCC can serve as a metric to evaluate milk production performance at the cow level and have diverse applications in various dairy research fields. However, some important research topics have received insufficient attention.
This thesis was conducted to explore the application of lactation curve modelling based on data from commercial dairy farms in the Netherlands and Belgium. Applications in cow reproduction performance and herd economic performance were developed. Four objectives were formulated: (1) to predict lactation persistency for day 305 of lactation at different insemination moments, (2) to investigate the association between days post conception and persistency, (3) to summarize cow lactation curves into herd lactation curve characteristics (HLCC) and illustrate a field application of HLCC, and (4) to compare whether HLCC or the herd’s average 305-day milk production is better able to explain herd economic performance.

Start date and time
End date and time
The Academiegebouw (Domplein 29) and digital
PhD candidate
Y. Chen
Lactation curve modelling in dairy production Applications at cow and herd level
PhD supervisor(s)
prof. dr. M. Nielen
dr. ir. W. Steeneveld
dr. ing. M.P.G. Hostens