title: Increasing the revenues from automatic milking by using individual variation in milking characteristics.
abstract: The objective of this study was to quantify individual variation in daily milk yield and milking duration in response to the length of the milking interval and to assess the economic potential of using this individual variation to optimize the use of an automated milking system. Random coefficient models were used to describe the individual effects of milking interval on daily milk yield and milking duration. The random coefficient models were fitted on a data set consisting of 4,915 records of normal uninterrupted milkings collected from 311 cows kept in 5 separate herds for 1 wk. The estimated random parameters showed considerable variation between individuals within herds in milk yield and milking duration in response to milking interval. In the actual situation, the herd consisted of 60 cows and the automatic milking system operated at an occupation rate (OR) of 64%. When maximizing daily milk revenues per automated milking system by optimizing individual milking intervals, the average milking interval was reduced from 0.421 d to 0.400 d, the daily milk yield at the herd level was increased from 1,883 to 1,909 kg/d, and milk revenues increased from euro498 to euro507/d. If an OR of 85% could be reached with the same herd size, the optimal milking interval would decrease to 0.238 d, milk yield would increase to 1,997 kg/d, and milk revenues would increase to euro529/d. Consequently, more labor would be required for fetching the cows, and milking duration would increase. Alternatively, an OR of 85% could be achieved by increasing the herd size from 60 to 80 cows without decreasing the milking interval. Milk yield would then increase to 2,535 kg/d and milk revenues would increase to euro673/d. For practical implementation on farms, a dynamic approach is recommended, by which the parameter estimates regarding the effect of interval length on milk yield and the effect of milk yield on milking duration are updated regularly and also the milk production response to concentrate intake is taken into account.
authors.affiliation: Animal Sciences Group, Wageningen University and Research Centre, Lelystad, the Netherlands. geert.andre@wur.nl
authors.forename: G
authors.initials: G
authors.lastname: André
authors.forename: P B M
authors.initials: PB
authors.lastname: Berentsen
authors.forename: B
authors.initials: B
authors.lastname: Engel
authors.forename: C J A M
authors.initials: CJ
authors.lastname: de Koning
authors.forename: A G J M
authors.initials: AG
authors.lastname: Oude Lansink
mesh_terms: D000818:Animals; D002417:Cattle; D003612:Dairying / Q000191:economics* / Q000295:instrumentation / Q000379:methods*; D005260:Female; D007774:Lactation / Q000502:physiology*; D008892:Milk / Q000378:metabolism*; D013223:Statistics as Topic; D013997:Time Factors