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Stochastic modelling of dairy herds
based on real production data to support management decision
Souad
Menasra
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A
stochastic simulation model of a dairy farm was developed to allow
investigation of the effects of varying management decision in dairy herd.
The primary purpose of this model is to quantify the economic effect of
different calving season with respect to production and reproductive
performance. The revenues and costs of dairy cows with different calving
season were calculated. The feed costs were calculated from consumption of
forage (silage or grass) and concentrate, which were estimated from the
energy requirements. Furthermore, the course of replacement price, calf
revenue and the financial loss associated with, involuntary culling was
considered.
The economic value of fertility was estimated by using the model, the gross
margin of an increase in fertility in the herd was then estimated to the
difference of respective average of service and conception rates in the
herd. The estimated result was high taken into account the consequences of a
change in fertility, i.e. on culling rate, and on costs. The gross margin of
10% absolute change in service and 5% in conception rates was estimated to
be between £50 and £90 per cow per year. These values increased when the
average fertility level increased. Improving both conception and service
rates provides opportunities for management control of reproduction and
profitability in a dairy herd.
The model was also used to examine the economic consequences of relaxing
fertility culling in an all-year calving herd. To quantify the economic
effects of different culling policies with respect to reproductive failure.
The expected gross margin of the cow as an annuity equivalent under various
culling strategies an estimate of the value of longevity was obtained.
Increased longevity by 11 parity added about £100 per cow per year in gross
margin.
Model validation was conducted using data from NMR; the validation was based
on comparison between the model and two contrasting real herds. The real
herds were chosen by looking at KPIs within the Herd Companion tool. The
comparison of actual and simulated data indicated that the model did
simulate the response of input variables setting. The validation procedures
have demonstrated that the model can produce realistic simulation of
different herd’s fertility performance.