Modeling extended lactations of dairy cows

Area of Science:

• Dairy Science
• Mathematical Modeling
• Animal Production

Background:

• Accurate prediction of daily milk yield is essential for effective dairy herd management.
• Mathematical models are widely used to estimate milk production patterns in dairy cows.
• Understanding factors influencing milk yield, such as lactation length and reproductive status, is critical.

Purpose of the Study:

• To compare the predictive accuracy of nine mathematical models for daily milk yields in Costa Rican dairy cows.
• To evaluate model performance in both standard 305-day and extended lactations.
• To assess the impact of lactation length and calving-to-conception interval on milk yield prediction.

Main Methods:

• A dataset of 294,986 daily milk yield records from Costa Rican dairy cows was analyzed.
• Nine distinct mathematical models were fitted and compared using goodness-of-fit statistics.
• Lactations were categorized by parity, length (up to 17 months), and calving-to-conception interval.

Main Results:

• The diphasic model and lactation persistency model demonstrated the best goodness of fit.
• The diphasic model exhibited superior predictive accuracy for milk yield in both standard and extended lactations.
• Calving-to-conception interval negatively impacted milk yield in standard lactations but not in extended ones.

Conclusions:

• The diphasic model provides accurate daily milk yield estimates for dairy cows across standard and extended lactations.
• Further research is needed to interpret model parameters due to observed variations.
• Reproductive status significantly affects milk yield differently in standard versus extended lactations.