Milk Production and Somatic Cell Count in Michigan Dairy Herds PAUL C. BARTLETT Department of Large Animal Clinical Sciences Michigan Stale University East lansing 48824 GAY Y. MILLER Ohio Stale University Columbus 43210 CLYDE R. ANDERSON Michigan Dairy Herd Improvement Association Box 23153
lansing 48909 JOHN H. KIRK Auburn University Auburn, AL 36849
ABSTRACT
The established association between milk production and sec in dairy cattle is increasingly used to estimate lost production due to mastitis. Such cost estimates are used to make decisions regarding cost effective mastitis prevention and control. It is therefore important to verify the relationship between sec and milk production using data from different areas of the country and by using different analytical methodology. Our study used the 1985 to 1986 Michigan DIDA data base and analyzed daily milk production records rather than lactation summary records as used in the past. One advantage to our approach was that it did not give equal weight to all lactations, regardless of their duration. Also, it enabled inclusion of cows that had incomplete lactations caused by culling, or had other reasons for removal from the herd. A statistical model was constructed to predict milk production OIl the basis of herd, cow within herd, stage in lactation, month of calving, lactation, and sec. The data base contained 397,172 milk
Received February I, 1989. Accepted May 14, 1990. 1990 ] Dairy Sci 73:2794-2800
test records obtained from Michigan DIDA from 504 Holstein herds in Michigan's lower peninsula. Our fmal model predicted 78% of the variation in milk production. Prediction of milk loss for each herd was highly correlated (r = .98) with the prediction model adopted by most DIDA organizations. Our model predicted that the mean herd lost a mean of 1.17 kg of milkIcow per d associated with sec. (Key words: mastitis, model, economics) INTRODUCTION
Michigan DHIA has adopted use of the sec linear score because of its nonnal distribution and relationship with lost milk production. The most widely recognized and accepted relationship between sec and lost milk production is based upon research at the University of Wisconsin (2, 8). Because important management decisions regarding cost effective prevention and control of mastitis are based on this relationship, it is prudent to confirm this relationship with different analytical techniques for different geographical areas and management systems. Several different approaches have been used to measure the causal relationship between sec and milk production. One approach uses the opposite quarter of the same cow for com2794
MILK PRODUcnON AND SOMATIC CELL COUNT
parison with an infected quarter (4, 7, 13). This approach has been criticized because of the possibility of compensatory increased milk production in healthy quarters in response to decreased milk. production in a locally infected quarter. Also, such studies are frequently unable to include cattle with more than one infected quarter. In addition, large dairy data bases, such as those found at the DHIA processing centers, do not have data identifying a quarter that is infected or quantities of milk produced for each quarter. Another approach has been to model production on a cow basis, with milk. production (dependent variable) as a function of see and several independent variables (5, 8, 11, 12). This is the approach used in this study. The objective of this study was to determine the relationship between milk production and see in Michigan and to compare our fmdings to those of others who have studied this relationship in other parts of the US.
2795
with subsequent categories increasing by 30 d increments until the 10th category, which included any milk. test obtained at >270 d postcalving. Lactation number was transformed to a dichotomous variable, with "I" for all first lactations and "2" for all subsequent lactations. The sec (in units of 100,000 cells/ml) obtained from DHIA was transformed by adding 1 to see then taking the natural logarithm of this sum. The estimated mean score (1.5) was then subtracted so that the new variable (LNSeC) would be approximately balanced around a mean of zero to reduce the amount of polynomial correlation between the linear, quadratic and cubic forms of the same variable (1). Actual daily milk. was used as the dependent variable. The model (Model A) was as follows:
=
lansing 48909 JOHN H. KIRK Auburn University Auburn, AL 36849
ABSTRACT
The established association between milk production and sec in dairy cattle is increasingly used to estimate lost production due to mastitis. Such cost estimates are used to make decisions regarding cost effective mastitis prevention and control. It is therefore important to verify the relationship between sec and milk production using data from different areas of the country and by using different analytical methodology. Our study used the 1985 to 1986 Michigan DIDA data base and analyzed daily milk production records rather than lactation summary records as used in the past. One advantage to our approach was that it did not give equal weight to all lactations, regardless of their duration. Also, it enabled inclusion of cows that had incomplete lactations caused by culling, or had other reasons for removal from the herd. A statistical model was constructed to predict milk production OIl the basis of herd, cow within herd, stage in lactation, month of calving, lactation, and sec. The data base contained 397,172 milk
Received February I, 1989. Accepted May 14, 1990. 1990 ] Dairy Sci 73:2794-2800
test records obtained from Michigan DIDA from 504 Holstein herds in Michigan's lower peninsula. Our fmal model predicted 78% of the variation in milk production. Prediction of milk loss for each herd was highly correlated (r = .98) with the prediction model adopted by most DIDA organizations. Our model predicted that the mean herd lost a mean of 1.17 kg of milkIcow per d associated with sec. (Key words: mastitis, model, economics) INTRODUCTION
Michigan DHIA has adopted use of the sec linear score because of its nonnal distribution and relationship with lost milk production. The most widely recognized and accepted relationship between sec and lost milk production is based upon research at the University of Wisconsin (2, 8). Because important management decisions regarding cost effective prevention and control of mastitis are based on this relationship, it is prudent to confirm this relationship with different analytical techniques for different geographical areas and management systems. Several different approaches have been used to measure the causal relationship between sec and milk production. One approach uses the opposite quarter of the same cow for com2794
MILK PRODUcnON AND SOMATIC CELL COUNT
parison with an infected quarter (4, 7, 13). This approach has been criticized because of the possibility of compensatory increased milk production in healthy quarters in response to decreased milk. production in a locally infected quarter. Also, such studies are frequently unable to include cattle with more than one infected quarter. In addition, large dairy data bases, such as those found at the DHIA processing centers, do not have data identifying a quarter that is infected or quantities of milk produced for each quarter. Another approach has been to model production on a cow basis, with milk. production (dependent variable) as a function of see and several independent variables (5, 8, 11, 12). This is the approach used in this study. The objective of this study was to determine the relationship between milk production and see in Michigan and to compare our fmdings to those of others who have studied this relationship in other parts of the US.
2795
with subsequent categories increasing by 30 d increments until the 10th category, which included any milk. test obtained at >270 d postcalving. Lactation number was transformed to a dichotomous variable, with "I" for all first lactations and "2" for all subsequent lactations. The sec (in units of 100,000 cells/ml) obtained from DHIA was transformed by adding 1 to see then taking the natural logarithm of this sum. The estimated mean score (1.5) was then subtracted so that the new variable (LNSeC) would be approximately balanced around a mean of zero to reduce the amount of polynomial correlation between the linear, quadratic and cubic forms of the same variable (1). Actual daily milk. was used as the dependent variable. The model (Model A) was as follows:
=
