Projects per year
Accurate monitoring and adequate planning of activities at modern dairy farms are important to improve farm profitability. The aim of this study was to investigate the use of test-day information to support farmers in management of Sicilian dairy herds. To this purpose, a test-day random regression model was developed for the analysis of production data of Sicilian dairy herds. Highest between-herd variation found in the variance components analysis using the test day model showed clear evidence of benefits in using a random regression TD model for management improvement. To identify sources of variation able to explain differences between herds in milk and milk components production herd curves, a field study was conducted in Southern Italy (Ragusa province) where diets and chemical composition of the diet was collected at herd level (every 3 months) and testday milk yield records at individual cow level (every month). Data collection was performed from March 2006 through December 2008 on 40 cooperating farms. Animal breed, feeding system, and total mixed ration chemical composition were identified to influence between-herd variation. At the individual cow level, test day model was further used to investigate the production response to changes in chemical and physical composition of diets in Ragusa province. Starch had the greatest effect on milk, fat, and protein production when crude protein and neutral detergent fiber contents were at a high and low value, respectively. Effects of a nutrition component on production changed when the other nutrients were included in the model, suggesting the confounding response one can have when multiple nutrients are not accounted for.
|Qualification||Doctor of Philosophy|
|Award date||20 Dec 2012|
|Place of Publication||S.l.|
|Publication status||Published - 2012|
- dairy cows
- dairy cattle nutrition