Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds.

Assessing the economic importance of traits is crucial for delivering appropriate breeding goals in dairy cattle breeding. The aim of the present study was to calculate economic values (EV) and assign the importance of health traits for three dairy cattle breeds: Lithuanian Black-and-White open population (LBW), Lithuanian Red open population (LR) and Lithuanian Red old genotype (LROG). The EV estimation was carried out using a stochastic bio-economic model SimHerd, which allows the simulation of the expected monetary gain of dairy herds.

Economic value of information from an alert system on physiological imbalance in fresh cows.

Physiological imbalance is an abnormal physiological condition that cannot be directly observed but is assumed to precede subclinical and clinical diseases in the beginning of lactation. Alert systems to detect the physiological imbalance in a cow using Fourier transform mid-infrared spectroscopy in milk have been developed. The objective of this study was to estimate the value of information provided from such system with different indicator accuracies, herd prevalence and prices.

Economic figures in herd health programmes as motivation factors for farmers.

Veterinarians often express frustrations when farmers do not implement their advice, and farmers sometimes shake their heads when they receive veterinary advice which is practically unfeasible. This is the background for the development of a focused 3 page economic report created in cooperation between veterinarians, farmers, advisers and researchers. Based on herd specific key-figures for management, the report presents the short- and long-term economic effects of changes in 15 management areas.

Modelling the economic impact of three lameness causing diseases using herd and cow level evidence.

Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways.

Estimation of probability for the presence of claw and digital skin diseases by combining cow- and herd-level information using a Bayesian network.

Cross sectional data on the prevalence of claw and (inter) digital skin diseases on 4854 Holstein Friesian cows in 50 Danish dairy herds was used in a Bayesian network to create herd specific probability distributions for the presence of lameness causing diseases. Parity and lactation stage are identified as risk factors on cow level, for the prevalence of the three lameness causing diseases digital dermatitits, other infectious diseases and claw horn diseases. Four herd level risk factors have been identified; herd size, the use of footbaths, a grazing strategy and total mixed ration.

The association of hoof lesions at claw trimming with test-day milk yield in Danish Holsteins.

In a cross-sectional study, performed between October 2002 and April 2003 on 55 Danish dairy herds with 6161 predominantly Holstein Friesian cows the prevalence of 9 hoof lesions was determined. All test-day yields (TDY) of kg energy corrected milk (ECM) in the lactation of diagnosis were recorded. For the purpose of including hoof lesions in a decision support model an attempt was made to aggregate the lesions into digital dermatitis (DD), other interdigital diseases (OID, infectious diseases other than DD) and hoof horn diseases (HHD, related to metabolic disorders and trauma).