Applications of population data analysis in on-farm dairy trials

With appropriate management controls and statistical designs, on-farm trials are an increasingly valuable research tool. On-farm trials can speed up technology adoption, particularly with those studies requiring large numbers of animals. Useful designs include longitudinal (pen vs. pen) trials, in which pen is the experimental unit, and crossover or switchback designs, in which treatments are imposed on a schedule over 1 or more experimental groups. A paired-herd design has been used, in which herds are the experimental units in a crossover trial. Others have published similar studies, including a multisite crossover design that used 35 dairy farms to compare milk responses with a protein source by using individual cow records to evaluate differences in milk production. Recently, statistical process control (SPC) techniques have been used to evaluate management changes by using repeated measures on the farm. Although a drawback to SPC may be the lack of traditional statistics to test differences (i.e., the lack of a control group), standard run rules are used to demonstrate with statistical certainty that a process or variable has changed, or to characterize a seasonal change. With SPC, the inference is limited to the herd or group of animals being monitored. Meta-analysis techniques are powerful tools used to combine results from many similar trials in which the response of interest is either small (i.e., continuous variables) or of low frequency (i.e., discrete variables). Meta-analysis can be used to segment a database so as to validate and compare trial methods or to investigate publication bias. Additional design concerns for reproduction studies include the need for adequate numbers of observations and planning for the lag time between an experimental treatment and response measurement (e.g., confirmation of pregnancy).