Literature DB >> 32618028

Forecasting the milk yield of cows on farms equipped with automatic milking system with the use of decision trees.

Dariusz Piwczyński1, Beata Sitkowska1, Magdalena Kolenda1, Marcin Brzozowski1, Joanna Aerts2, Pamela M Schork3.   

Abstract

The purpose of this paper was to utilize the decision trees technique to determine the factors responsible for high monthly milk yield in Polish Holstein-Friesian cows from 27 herds equipped with milking robots. The applied statistical method-the decision tree technique-showed that the most important factors responsible for monthly milk yield of dairy cows using robots were, in descending order of importance: milking frequency, lactation number, month of milking, and type of lying stall. At the same time, it has been ascertained that the highest monthly milk yield (47.24 kg) can be expected from multiparous cows kept in barns with a deep bedding that were milked more frequently than three times per day. On the other hand, the lowest milk production (13.56 kg) was observed among dairy cows milked less frequently than two times a day, with an average number of milked quarters lower than 3.97. The application of the decision trees technique allows a breeder to select appropriate levels of environmental factors and parameters that will help to ensure maximized milk production.
© 2020 Japanese Society of Animal Science.

Entities:  

Keywords:  automatic milking system; cows; decision trees; milk yield

Mesh:

Year:  2020        PMID: 32618028     DOI: 10.1111/asj.13414

Source DB:  PubMed          Journal:  Anim Sci J        ISSN: 1344-3941            Impact factor:   1.749


  2 in total

1.  Random Forest Modelling of Milk Yield of Dairy Cows under Heat Stress Conditions.

Authors:  Marco Bovo; Miki Agrusti; Stefano Benni; Daniele Torreggiani; Patrizia Tassinari
Journal:  Animals (Basel)       Date:  2021-04-30       Impact factor: 2.752

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

Authors:  Joanna Aerts; Magdalena Kolenda; Dariusz Piwczyński; Beata Sitkowska; Hasan Önder
Journal:  Animals (Basel)       Date:  2022-04-16       Impact factor: 2.752

  2 in total

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