By Bewley, J. M. and Borchers, M. R., Journal of Dairy Science, 2015
Research Paper Web Link / URL:
http://www.sciencedirect.com/science/article/pii/S0022030215002490
http://www.sciencedirect.com/science/article/pii/S0022030215002490
Description
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.
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.
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