Test-day fat to protein ratio as an indicator trait for sub-clinical ...

More documents

Recommendations

Info

Proportion of TD records from cows infected with putative, sub-clinical mastitis was 0.66 in DIM from 5 to 15 (Figure 4), decreasing to 0.19 in DIM from 36 to 45 and staying relatively constant at this level, dropping to 0.13 at the end of lactation (Figure 4). Posterior standard deviations for mixing proportions were 0.02 for the first DIM interval and around 0.01 for the remaining intervals. Average differences between IM+ and IM- groups and estimates of residual variances by DIM interval are in Figures 5 – 7 for milk, F:P and SCS, respectively. Cows infected with mastitis were characterized by smaller daily milk yield (up to 5 kg on DIM from 5 to 15), larger F:P (up to 0.13 on DIM from 26 to 35) and larger SCS (up to 1.3 on DIM from 16 to 25). Differences between mean values for mixture distributions were relatively uniform in DIM intervals for milk and SCS. The effect of putative mastitis on F:P different parts of lactation followed, in general, the shape of lactation curve for milk yield. Estimates of residual variances differed substantially between mixture components for all traits (Figures 5 – 7). Residual variances for records from healthy cows were smaller and more uniform across lactation than corresponding values for mastitic cows. General shapes of the variance curves for IM+ categories were similar to lactation curves for milk yield. Residual correlations between F:P and SCS in IM- category were all positive and small (250) was characterized by slightly negative genetic correlations between F:P and SCS. Daily correlations for the PE effect among traits were small and mostly negative (Figure 11). Milk and F:P were slightly positively correlated at the beginning of lactation (DIM
DISCUSSION Changes in SCS and milk yield are well known indicators of mammary infection in dairy cattle. Clinical mastitis is relatively easy to detect, as the milk or udder is abnormal and systemic signs of a disease are present. In contrast, sub-clinical mastitis is an infection that occurs without obvious clinical signs such as abnormal milk, udder swelling or tenderness, and fever. Somatic cells consist mainly of immune cells that enter the udder. When infection of the udder occurs, the number of immune cells increases rapidly, as the immune system attempts to overcome the infection. Simultaneously, milk yield decreases as the animal is under the stress of coping with infection. Once the infection has been cleared, the SCC levels and the milk yield gradually return to normal levels. Early lactation is associated with an energy deficit in a high producing dairy cow. Feed intake does not compensate energy losses associated with milk production and a cow enters a negative energy balance. An energy deficit leads to an increase fat synthesis in the udder, and inadequate intake of carbohydrates can cause an insufficient protein synthesis by ruminal bacteria resulting in a decrease of milk protein content (Butthereit et al. 2010; after Gürtler and Schweigert, 2005). Thus F:P may be an easy tool to differentiate between cows that can or cannot cope with the challenges of an early lactation. The mixture model for milk, F:P and SCS used in this study was an extension of a two trait specification for milk and SCS applied to the same data by Jamrozik and Schaeffer (2010). In addition to adding one more trait, the lactation length was split into more intervals in the current study (30 vs. 4) allowing for more precise inferences, especially at the beginning of lactation. Estimated mixing proportions were similar between these studies with the exception of the extreme parts of lactation (the first and last DIM intervals in the more dense partition). The pattern of distributions for milk and SCS between mixture components was also in good agreement for both applications. Sub-clinical mastitis is not a precisely defined trait. Diagnoses are subjective; they are mostly based on the pre-assumed threshold level of SCS. In addition, an elevated SCS does not necessarily mean the occurrence of mammary infection. Estimates of incidence rates of sub-clinical mastitis are therefore rare and not precise. Other applications of mixture models for SCS in dairy cattle indicated proportions of records from infected cows ranged from 5% for the US Holsteins (Boettcher et al. 2007) to 30% for the Danish Holsteins (Madsen et al. 2008). Simulation study of Ødegård et al. (2003) indicated relatively low sensitivity (probability of correct classification of IM+ records) of the single-trait two-component mixture model, ranging from 0.53 to 0.94. A little higher specificity (probability of correct classification of IM- records) varied from 0.87 to 0.98, depending on the simulation scenario and the assumptions of the fitted model. Boettcher et al. (2005) verified classification properties of the finite mixture model applied to SCS of Italian goats with bacteriological information on the mammary gland infection status. The mixture model was able to classify correctly 60 and 48% of the healthy and infected records, respectively. This was, as the authors concluded, slightly higher than would be expected from random classification, but not enough for useful mastitis diagnosis. Further studies seem to be needed. Fat to protein ratio has received relatively less attention in genetic studies of dairy cattle. Estimates of genetic parameters for this trait are scarce. Vos and Groen (1998) estimated heritability of protein to fat ratio as high as 0.79 for Dutch Holstein Black and 5
Page 1 and 2: Test-day fat to protein ratio as an
Page 3: where Ri= (Ii - Mzi) Ri0 + Mzi Ri
Page 7 and 8: Jamrozik J., Schaeffer L.R. (2010)
Page 9 and 10: Figure 4: Proportion (P) of records
Page 11 and 12: Figure 8: Residual correlation amon

Test-day fat to protein ratio as an indicator trait for sub-clinical ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?