The economics of optimal health and productivity in the commercial dairy

Cluster analysis of Dairy Herd Improvement data to discover trends in performance characteristics in large Upper Midwest dairy herds

Principal component analysis (PCA) is a variable reduction method used on over-parameterized data sets with a vast number of variables and a limited number of observations, such as Dairy Herd Improvement (DHI) data, to select subsets of variables that describe the largest amount of variance. Cluster analysis (CA) segregates objects, in this case dairy herds, into groups based upon similarity in multiple characteristics simultaneously. This project aimed to apply PCA to discover the subset of most meaningful DHI variables and to discover groupings of dairy herds with similar performance characteristics. Year 2011 DHI data was obtained for 557 Upper Midwest herds with test-day mean ≥200 cows (assumed mostly freestall housed), that remained on test for the entire year. The PCA reduced an initial list of 22 variables to 16. The average distance method of CA grouped farms based on best goodness of fit determined by the minimum cophenetic distance. Six groupings provided the optimal fitting number of clusters. Descriptive statistics for the 16 variables were computed per group. On observations of means, groups 1, 2, and 6 demonstrated the best performances in most variables, including energy-corrected milk, linear somatic cell score (log of somatic cell count), dry period intramammary infection cure rate, new intramammary infection risk, risk of subclinical intramammary infection at first test, age at first calving, days in milk, and Transition Cow Index. Groups 3, 4, and 5 demonstrated the worst mean performances in most the PCA-selected variables, including DIM, age at first calving, risk of subclinical intramammary infection at first test, and dry period intramammary infection cure rate. Groups 4 and 5 also had the worst mean herd performances in energy-corrected milk, Transition Cow Index, linear somatic cell score, and new intramammary infection risk. Further investigation will be conducted to reveal patterns of management associated with herd categorization. The PCA and CA should be used when describing the multivariate performance of dairy herds and whenever working with over-parameterized data sets, such as DHI databases.

Economic assessment of animal health performance

This article describes the fundamental principles of economic assessment of animal health performance in the modem animal production environment. Animal production is a complex system of combined inputs (eg, physical inputs, managerial decision choices) into a production process that produces products valued by society. Perturbations to this system include disease processes and management inefficiencies. Economic valuation of these perturbations must account for the marginal changes in revenues and cost, the time dimensions of occurrence, the inherent risk characteristics of biologic systems, and any opportunity value that exists that allows management to intervene within the process and make economically influencing decisions. It has been recognized that improving animal health can play a major role in achieving efficient and economically rewarding production.

Resynchronization of ovulation and timed insemination in lactating dairy cows

The objective was to compare pregnancy rates to resynchronization and timed AI (TAI) protocols in lactating dairy cows that received GnRH at 23 d and were diagnosed not pregnant at 30 d after the pre-enrollment AI. Nonpregnant cows (624) at ultrasonography on day 30 (study day 0) were classified as diestrus (74.8%), metestrus (5.6%) and without a CL (19.5%). Cows in diestrus were assigned either to the GnRH group (PGF2alpha on day 0, GnRH on day 2 and TAI 16 h later, n = 238) or the estradiol cypionate (ECP) group (PGF2alpha on day 0, ECP on day 1, and TAI 36 h later, n = 229). Cows in metestrus were assigned to the Modified Heatsynch Group (GnRH on day 0, PGF(2alpha) on day 7, ECP on day 8 and TAI on day 9, n = 35). Cows without a CL (n = 122) were classified either as proestrus (10.6%), ovarian cysts (7.5%) or anestrus (1.4%), and assigned to factorial treatments (i.e., use of GnRH versus CIDR) to either the GnRH group (GnRH on day 0, PGF2alpha on day 7, GnRH on day 9 and TAI 16 h later, n = 28), the CIDR group (CIDR insert from days 0 to 7, PGF2alpha on day 7, GnRH on day 9 and TAI 16 h later, n = 34), the GnRH + CIDR group (GnRH on day 0, CIDR insert from days 0 to 7, PGF2alpha on day 7, GnRH on day 9 and TAI 16h later, n = 32), and the control group (PGF2alpha on day 7, GnRH on day 9 and TAI 16 h later, n = 28). For cows without a CL, plasma P4 concentrations were determined on days 0, 7, 10 and 17 and ovarian structures determined on days 0, 7 and 17. Pregnancy rates were evaluated at 30, 55 and 90 d after the resynchronized AI. For cows in diestrus, there were no differences in pregnancy rates on days 30, 55 and 90 for cows in the GnRH (27.5, 26.5 and 24.2%) or ECP (29.1, 25.5 and 24.1%) groups. In addition, there were no differences in pregnancy losses between days 30 and 55 and 55 and 90 between the GnRH (7.0 and 8.6%) and ECP (9.8 and 5.4%) groups. For cows without a CL, GnRH on day 0 increased the proportion of cows with a CL on days 7 and 17 and plasma P4 concentration on day 17 in cows with ovarian cysts but not for cows in proestrus. The CIDR insert increased pregnancy rate in cows with ovarian cysts but reduced pregnancy rate for cows in proestrus.