Use of herd solutions from a random regression test-day model for diagnostic dairy herd management.
In a random regression test-day model, environmental effects in addition to individual animal factors can be included and analyzed. Moreover, instead of herd-year classification of the management groups, the herd-test-day classification within the model better accounts for month-to-month short-term environmental variation in production and somatic cell count (SCC) traits. The herd management levels of milk yield (milk deviation from whole-country mean, kilograms/day), protein and fat concentration (protein and fat deviation, %), and SCC (SCC deviation, 1,000 cells/mL) are used in the dairy herd management Web application "Maitoisa" (in English, "Milky"). This management tool helps to recognize several management problems. For recognition of systematic patterns and single unusual test-days, a monthly time-trend analysis was developed to smooth the random fluctuations and display the yearly production pattern. In addition to analyzing single test-day deviations from the mean, modeled herd solutions assist users in identifying repeated phenomena and enable the forecasting of the management pattern for the subsequent year. The solutions are displayed either as tables or graphs plotted by calendar months. In addition to management effects of the farmer's own herd, he or she can request country or region percentiles to be displayed in the graphs. The Web service has been offered to farmers and dairy advisors since 2001, and it has proved to be a powerful tool for herd monitoring and planning.
Koivula
M
M
MTT Agrifood Research Finland, Biotechnology and Food Research, Biometrical Genetics, Jokioinen, Finland. minna.koivula@mtt.fi
Nousiainen
J I
JI
Nousiainen
J
J
Mäntysaari
E A
EA
D000818:Animals; D002417:Cattle; D003612:Dairying / Q000379:methods*; D004467:Economics; D005260:Female; D005387:Finland; D020407:Internet; D008331:Management Information Systems; D015233:Models, Statistical; D012044:Regression Analysis; D013997:Time Factors