Ben Smink - National Milk Producers Federation

transformed to practical hands-on information. Herd managers get quick short overviews of
attention cows only, including what the potential problem of the cow is and in which part of the
body she is developing the problem. For instance, if we see high fat/protein ratio in combination
with rumination drifting off, the program indicates ketosis. Or, if a cow shows normal milk
production, normal conductivity and color of the milk in combination with high milk
temperature, we know the cow is sick but not very likely caused by mastitis. For a typical
mastitis case high detection rates are shown to be the combination of deviations in milk color,
milk conductivity, quarter yield and quarter dead milk time. (Van der Tol, 2012)
Multiple sensors in combination with the visual observation of naturally behaving cows in the
robot barn enable the herdsman to see the abnormal individual in a much earlier stage. Therefore
the herdsman can prevent the animal from getting sick before she starts loosing production. It is
about being pro-active instead of re-active and about making better decisions to prevent cows
drifting off (instead of making culling decisions after the problem got too severe). All of this
improves constant health and therefore constant production, fertility and longevity results of the
herd.
Is it magic No of course not. If you are not a good cow person this information is not going to
make you a good dairy farmer. At the end of the day the robot is just another way of milking
(and spending your daily life) and not a magic herd management machine. An internal
questionnaire with to the top 25 AMS producers out of the CRV BENELUX registration reports
(DHI records The Netherlands, Belgium and Luxemburg), showed that the most important
success factors are: best cow management practices and best cow comfort circumstances and not
factors like type or age of the AMS barn.
What is in it for the advisor: Precision Dairy Management tools in AMS
On a higher level the dairy producer together with his advisors (nutritionists, veterinarians)
benefit from this wealth of information on herd/pen/individual level to make better decisions on
aspects like: feed rations, dry matter intake, effective fiber in the bunk, output feed truck, dry
cow treatment, dry cow transition management, preventive mastitis treatment, et cetera.
However, the advisor has to realize that the way to consult AMS producers is different. Farmers
have all this information real time every hour of the day. So producers expect from advisors
scenarios instead of evaluations. In the past, decisions were made on a monthly basis and based
on milk sample results, which is similar to a tax paying process: you look at the outcome at the
end of the period, pay your dues and pull a line to prevent this from happening in the future.
Advisory on an AMS herd is more like a GPS navigation process: the farmer is expecting the
advisor to give guidelines for the future which the farmer can select and apply immediately as
the situation unfolds as he works his way through the coming month. As a result advisors will
have to train producers how to use the summarized AMS information and translate that into daily
action decisions. For many senior advisors it is scary to give that responsibility to the farmer: did