Animal Health and Grazing Systems

Goal I. Develop and implement novel electronic clinical case data collection and reporting tools for use in building effective veterinary epidemiology and surveillance programs at the two veterinary diagnostic laboratories in Kentucky. Supporting Objectives. I. Design and implement computer-based forms for electronic data collection that maximize speed, accuracy, completeness, ease-of-use, and conformance with national lexicon and messaging standards. 2. Determine and develop the appropriate electronic technologies to perform real-time collection and storage of clinical case infom1ation on accessions submitted by practicing veterinarians and farmers. 3. Design and develop electronic reporting and alerting systems that will provide near real-time information on risk factors and grazing animal disease events to laboratory clients, the State Veterinarian, and the USDA. Plans to Accomplish Goal 1. The source documents that are used to submit clinical cases to diagnostic laboratories (accession forms) will be assessed by in-house staff and clients and redesigned as necessary to meet the criteria for data collection as set out in the supporting objectives. Detailed specifications will be written for a web-based accessioning, laboratory test result capture, and reporting'alerting system to be developed/applied and implemented at both participating laboratories. This will provide immediate entry level surveillance and epidemiological services. The quality of surveillance data will improve as enzootic levels of diseases and syndromes are ascertained. This information base will provide the data streams to drive analytical engines to provide more sophisticated surveillance output in the form of signals, alerts, and GIS products. Goal 2. To improve the quality, availability and efficiency of forage use in the promotion of livestock health and productivity in Kentucky and other parts of the transition zone grasslands. Supporting Objectives. 1. Determine if tall fescue endophyte infestation in Kentucky pastures can be 'mapped' using an optical scanner and GPS technology during January through March compared to April through July; 2. Compare data obtained in Objective # I with a visual estimate. Plans to Accomplish Goal 2. A multi-spectral sensor with broad spectrum of wavelengths (450-1480 nm) will be utilized to distinguish between tall fescue and Kentucky bluegrass. Indices will be developed, similar to that utilized by an optical sensor ('GreenSeeker') that measures Normalized Difference Vegetation Indices (NDVI) from reflectance of red and far red of leaf tissue. These indices will be utilized to determine and map the cover of tall fescue patches in horse paddocks.