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Forecasting Milking Efficiency of Dairy Cows Milked in an Automatic Milking System Using the Decision Tree Technique.

Authors :
Aerts J
Kolenda M
Piwczyński D
Sitkowska B
Önder H
Source :
Animals : an open access journal from MDPI [Animals (Basel)] 2022 Apr 16; Vol. 12 (8). Date of Electronic Publication: 2022 Apr 16.
Publication Year :
2022

Abstract

In barns equipped with an automatic milking system, the profitability of production depends primarily on the milking efficiency of a cow (ME; kg/min) defined as cow milk yield per minute of box time. This study was carried out on 1823 Polish Holstein−Friesian cows milked by the automatic milking system (AMS) in 20 herds. Selected milking parameters recorded by the AMS were analyzed in the research. The aim of the study was to forecast ME using two statistical techniques (analysis of variance and decision trees). The results of the analysis of variance showed that the average ME was 1.67 kg/min. ME was associated with: year of AMS operation (being the highest in the first year), number of cows per robot (the highest in robots with 61−75 cows), lactation number (highest for multiparas), season of calving (the highest in spring), age at first calving (>36 months), days in milk (151−250 days) and finally, rear quarter to total milk yield ratio (the highest between 51% and 55%). The decision tree predicted that the highest ME (2.01 kg/min) corresponded with cows that produced more than 45 kg of milk per day, were milked less than four times/day, had a short teatcup attachment time (<7.65 s) and were milked in robots that had an occupancy lower than 56 cows.

Details

Language :
English
ISSN :
2076-2615
Volume :
12
Issue :
8
Database :
MEDLINE
Journal :
Animals : an open access journal from MDPI
Publication Type :
Academic Journal
Accession number :
35454286
Full Text :
https://doi.org/10.3390/ani12081040