A producer assessment of precision dairy farming technology use, usefulness, and pre-purchase considerations

Abstract Text: A survey to identify producer perception of precision dairy farming technologies was distributed in March 2013 through written publications and email. Responses were collected in May 2013 (n = 109) and statistical analysis was performed using SAS (SAS Institute, Inc. Cary, NC). Herd size, producer age, and role on the farm were collected and analyzed but significant differences were not found (P > 0.05). Producers were asked to indicate parameters currently monitored on their farm from a predetermined list and producers most often selected daily milk yield (52.3%), cow activity (41.3%), and not applicable (producers not currently implementing technologies; 1.2%). Producers were asked to rank the same list on usefulness using a 5-point Likert Scale (1: not useful and 5: being useful). Least-squares means were calculated using the GLM procedure of SAS and producers indicated (mean ± SE) mastitis (4.77 ± 0.47), standing heat (4.75 ± 0.55), and daily milk yield (4.72 ± 0.62) to be most useful. Pre-purchase technology selection criteria were ranked using a Likert Scale (1: not important and 5: important) by producers and 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) were found most important. Producers were categorized into United States or an other countries category based upon their farm location. Significant differences (P < 0.05) were identified between country and the adoption of technologies monitoring: animal position and location, body weight, cow activity, daily milk yield, lying and standing time, mastitis, milk components, rumen activity, and rumination with other countries being higher in all cases. Producers were categorized based upon technology use (using technology vs. not using technology) and least-squares means were calculated across technology usefulness with daily milk yield (using technologies: 4.83 ± 0.07, vs. not using technologies: 4.50 ± 0.10) and standing heat (using technologies: 4.68 ± 0.06, vs. not using technologies: 4.91 ± 0.09) differing significantly (P < 0.05). Least-squares means were calculated for technology use categories on producer pre-purchase considerations and availability of local support (using technologies: 4.25 ± 0.11, vs. not using technologies: 3.82 ± 0.16) differing significantly (P < 0.05). Using this data, technology manufacturers can better design and market technologies for producer needs.

Keywords: producer perception, survey, precision dairy farming technologies