Literature DB >> 14740859

Automatic milking systems, farm size, and milk production.

C A Rotz1, C U Coiner, K J Soder.   

Abstract

Automatic milking systems (AMS) offer relief from the demanding routine of milking. Although many AMS are in use in Europe and a few are used in the United States, the potential benefit for American farms is uncertain. A farm-simulation model was used to determine the long-term, whole-farm effect of implementing AMS on farm sizes of 30 to 270 cows. Highest farm net return to management and unpaid factors was when AMS were used at maximal milking capacity. Adding stalls to increase milking frequency and possibly increase production generally did not improve net return. Compared with new traditional milking systems, the greatest potential economic benefit was a single-stall AMS on a farm size of 60 cows at a moderate milk production level (8600 kg/cow). On other farm sizes using single-stall type robotic units, losses in annual net return of 0 dollars to 300 dollars/cow were projected, with the greatest losses on larger farms and at high milk production (10,900 kg/cow). Systems with one robot serving multiple stalls provided a greater net return than single-stall systems, and this net return was competitive with traditional parlors for 50- to 130-cow farm sizes. The potential benefit of AMS was improved by 100 dollars/cow per year if the AMS increased production an additional 5%. A 20% reduction in initial equipment cost or doubling milking labor cost also improved annual net return of an AMS by up to 100 dollars/cow. Annual net return was reduced by 110 dollars/cow, though, if the economic life of the AMS was reduced by 3 yr for a more rapid depreciation than that normally used with traditional milking systems. Thus, under current assumptions, the economic return for an AMS was similar to that of new parlor systems on smaller farms when the milking capacity of the AMS was well matched to herd size and milk production level.

Entities:  

Mesh:

Year:  2003        PMID: 14740859     DOI: 10.3168/jds.S0022-0302(03)74032-6

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  4 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

Review 3.  Developing 'Smart' Dairy Farming Responsive to Farmers and Consumer-Citizens: A Review.

Authors:  Maeve Mary Henchion; Áine Regan; Marion Beecher; Áine MackenWalsh
Journal:  Animals (Basel)       Date:  2022-02-02       Impact factor: 2.752

4.  Relationships between Selected Physiological Factors and Milking Parameters for Cows Using a Milking Robot.

Authors:  Marian Kuczaj; Anna Mucha; Alicja Kowalczyk; Ryszard Mordak; Ewa Czerniawska-Piątkowska
Journal:  Animals (Basel)       Date:  2020-11-07       Impact factor: 2.752

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.