Literature DB >> 33012822

Factors associated with the adoption of technologies by the Canadian dairy industry.

Murray D Jelinski1, David F Kelton1, Chris Luby1, Cheryl Waldner1.   

Abstract

Data generated from Statistics Canada's 2016 Census of Agriculture and Census of Population were used to describe the adoption of 8 technologies by the Canadian dairy industry: computer/laptop, smartphone/tablet, auto-steering, auto-feeding, auto-environment, robotic milking, global positioning systems (GPS), and geographical information systems (GIS). Logistic regression was used to analyze the adoption of each technology by geographical region, operators' gender, operators' age, herd size, and number of operators per farm. Gender and age were marginally related to the level of adoption of each technology, whereas the number of operators per dairy farm and farm size were associated with increased adoption of most technologies. Quebec had the smallest average farm size, but the highest levels of adoption for 5 of 8 technologies. Copyright and/or publishing rights held by the Canadian Veterinary Medical Association.

Mesh:

Year:  2020        PMID: 33012822      PMCID: PMC7488376     

Source DB:  PubMed          Journal:  Can Vet J        ISSN: 0008-5286            Impact factor:   1.008


  20 in total

Review 1.  Recent advancement in biosensors technology for animal and livestock health management.

Authors:  Suresh Neethirajan; Satish K Tuteja; Sheng-Tung Huang; David Kelton
Journal:  Biosens Bioelectron       Date:  2017-07-08       Impact factor: 10.618

2.  The Canadian National Dairy Study 2015-Adoption of milking practices in Canadian dairy herds.

Authors:  E Belage; S Dufour; C Bauman; A Jones-Bitton; D F Kelton
Journal:  J Dairy Sci       Date:  2017-03-16       Impact factor: 4.034

Review 3.  Invited review: A perspective on the future of genomic selection in dairy cattle.

Authors:  J I Weller; E Ezra; M Ron
Journal:  J Dairy Sci       Date:  2017-08-23       Impact factor: 4.034

4.  Update on demographics of the Canadian Dairy Industry for the period 2011 to 2016.

Authors:  Christopher D Luby; Cheryl Waldner; Murray D Jelinski
Journal:  Can Vet J       Date:  2020-01       Impact factor: 1.008

5.  Dairy farmers with larger herd sizes adopt more precision dairy technologies.

Authors:  J I Gargiulo; C R Eastwood; S C Garcia; N A Lyons
Journal:  J Dairy Sci       Date:  2018-03-07       Impact factor: 4.034

6.  Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows.

Authors:  L M Mayo; W J Silvia; D L Ray; B W Jones; A E Stone; I C Tsai; J D Clark; J M Bewley; G Heersche
Journal:  J Dairy Sci       Date:  2019-01-26       Impact factor: 4.034

7.  Adoption of technology and management practices by Canadian cow-calf producers.

Authors:  Murray Jelinski; Reynold Bergen; Brenna Grant; Cheryl Waldner
Journal:  Can Vet J       Date:  2019-03       Impact factor: 1.008

Review 8.  A 100-Year Review: Reproductive technologies in dairy science.

Authors:  S G Moore; J F Hasler
Journal:  J Dairy Sci       Date:  2017-12       Impact factor: 4.034

Review 9.  A 100-Year Review: Metabolic health indicators and management of dairy cattle.

Authors:  T R Overton; J A A McArt; D V Nydam
Journal:  J Dairy Sci       Date:  2017-12       Impact factor: 4.034

Review 10.  Invited review: Big Data in precision dairy farming.

Authors:  C Lokhorst; R M de Mol; C Kamphuis
Journal:  Animal       Date:  2019-01-11       Impact factor: 3.240

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