Literature DB >> 25892693

An assessment of producer precision dairy farming technology use, prepurchase considerations, and usefulness.

M R Borchers1, J M Bewley2.   

Abstract

An online survey to identify producer precision dairy farming technology perception was distributed in March 2013 through web links sent to dairy producers through written publications and e-mail. Responses were collected in May 2013 and 109 surveys were used in statistical analysis. Producers were asked to select parameters monitored by technologies on their farm from a predetermined list and 68.8% of respondents indicated technology use on their dairies (31.2% of producers not using technologies). Daily milk yield (52.3%), cow activity (41.3%), and mastitis (25.7%) were selected most frequently. Producers were also asked to score the same list of parameters on usefulness using a 5-point scale (1=not useful and 5=useful). Producers indicated (mean ± SE) mastitis (4.77±0.47), standing estrus (4.75±0.55), and daily milk yield (4.72±0.62) to be most useful. Producers were asked to score considerations taken before deciding to purchase a precision dairy farming technology from a predetermined list (1=not important and 5=important). Producers indicated benefit-to-cost ratio (4.57±0.66), total investment cost (4.28±0.83), and simplicity and ease of use (4.26±0.75) to be most important when deciding whether to implement a technology. Producers were categorized based on technology use (using technology vs. not using technology) and differed significantly across technology usefulness scores, daily milk yield (using technologies: 4.83±0.07 vs. not using technologies: 4.50±0.10), and standing estrus (using technologies: 4.68±0.06 vs. not using technologies: 4.91±0.09). The same categories were used to evaluate technology use effect on prepurchase technology selection criteria and availability of local support (using technologies: 4.25±0.11 vs. not using technologies: 3.82±0.16) differed significantly. Producer perception of technology remains relatively unknown to manufacturers. Using this data, technology manufacturers may better design and market technologies to producer need.
Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  parameter; precision dairy farming technology; producer perception; survey

Mesh:

Year:  2015        PMID: 25892693     DOI: 10.3168/jds.2014-8963

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


  5 in total

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Journal:  Can Vet J       Date:  2020-10       Impact factor: 1.008

2.  Hyperketonemia Predictions Provide an On-Farm Management Tool with Epidemiological Insights.

Authors:  Ryan S Pralle; Joel D Amdall; Robert H Fourdraine; Garrett R Oetzel; Heather M White
Journal:  Animals (Basel)       Date:  2021-04-30       Impact factor: 2.752

3.  Digital technology adoption in livestock production with a special focus on ruminant farming.

Authors:  T Groher; K Heitkämper; C Umstätter
Journal:  Animal       Date:  2020-06-17       Impact factor: 3.240

4.  Adoption of Precision Technologies by Brazilian Dairy Farms: The Farmer's Perception.

Authors:  Rebeca Silvi; Luiz Gustavo R Pereira; Claudio Antônio V Paiva; Thierry R Tomich; Vanessa A Teixeira; João Paulo Sacramento; Rafael E P Ferreira; Sandra G Coelho; Fernanda S Machado; Mariana M Campos; João Ricardo R Dórea
Journal:  Animals (Basel)       Date:  2021-12-07       Impact factor: 2.752

5.  Short-Term Adaptation of Dairy Cattle Production Parameters to Individualized Changes in Dietary Top Dress.

Authors:  Tanner P Price; Vinícius C Souza; Douglas M Liebe; Mark D Elett; Ty C Davis; Claire B Gleason; Kristy M Daniels; Robin R White
Journal:  Animals (Basel)       Date:  2021-12-10       Impact factor: 2.752

  5 in total

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