RESUMO
Electrical conductivity of milk is an indirect method for diagnosis of mastitis that can be used as criterion of selection in breeding programs, to obtain more resistant animals to infection. Data from 9,302 records of electrical conductivity from the morning milking (ECM), 13,070 milk yield records (MY) and 11,560 records of milking time (MT), of 1,129 first lactation Holstein cows, calving from 2001 to 2011, were used in statistical analysis. Data of eight herds of Southeast region of Brazil were obtained by the WESTFALIA® electronic milking machines, with Dairyplan management system. Two analysis were performed: a multitrait, including MY, MT and ECM, and an unitrait, considering only test-day morning electrical conductivity. The model included additive genetic, permanent environmental and residual effects as random. Additionally, contemporary groups (CG), the age of cow at calving (AGC) and days in milk (DIM) (linear and quadratic regression) were included as fixed effects. The CG was composed by herd, year and month of test. DIM classes were formed with weekly intervals, constituting a total of 42 classes. The variance components were estimated by Restricted Maximum Likelihood Method (REML), using the Wombat software. The average and standard deviation of ECM were 4.80 mS cm-1 and 0.54 mS cm-1, respectively. The heritability estimates by multitrait model and their standa
O artigo não apresenta resumo em português.
RESUMO
The crossbreeding practice between specialized dairy breeds is an usual method for dairy producers and recently the Holstein x Jersey crosses has continuously increased in some regions of Brazil. Motivating factors of this practice include an interest in improving the milk solids content, somatic cell count (SCC), fertility, longevity and calving ease, in addition to reduce the problems of consanguinity. The aim of this paper was to evaluate the milk components and milk yield of Holstein x Jersey crosses. Data set comprised 59,331 monthly records of 6,429 pure Holstein (H) and Jersey (J) and ½ H x ½ J crossed cows calving from 1992 to 2010. The traits analyzed were test-day milk yields (MT), somatic cell score (SCS) and percentages of fat (%F) and protein (%P). Since the SCC is not normal distributed it was converted to a logarithmic scale in SCS, using the following equation, SCS = log2 (SCC/100) + 3. The variables MT, SCS, %F and %P were analyzed as dependent variables by least square method using GLM procedure. There were considered linear models containing the effects of breed (H, J and ½ H x ½ J or F1), herd, year and month of test as classificatory variables. Age at calving (AC) and days in milk (DM) were included as covariates (linear and quadratic effects) for all traits. The test-day milk yield was included as covariate for SCS model, %F and %P. All variables included
O artigo não apresenta resumo em português.
RESUMO
The crossbreeding practice between specialized dairy breeds is an usual method for dairy producers and recently the Holstein x Jersey crosses has continuously increased in some regions of Brazil. Motivating factors of this practice include an interest in improving the milk solids content, somatic cell count (SCC), fertility, longevity and calving ease, in addition to reduce the problems of consanguinity. The aim of this paper was to evaluate the milk components and milk yield of Holstein x Jersey crosses. Data set comprised 59,331 monthly records of 6,429 pure Holstein (H) and Jersey (J) and ½ H x ½ J crossed cows calving from 1992 to 2010. The traits analyzed were test-day milk yields (MT), somatic cell score (SCS) and percentages of fat (%F) and protein (%P). Since the SCC is not normal distributed it was converted to a logarithmic scale in SCS, using the following equation, SCS = log2 (SCC/100) + 3. The variables MT, SCS, %F and %P were analyzed as dependent variables by least square method using GLM procedure. There were considered linear models containing the effects of breed (H, J and ½ H x ½ J or F1), herd, year and month of test as classificatory variables. Age at calving (AC) and days in milk (DM) were included as covariates (linear and quadratic effects) for all traits. The test-day milk yield was included as covariate for SCS model, %F and %P. All variables included
O artigo não apresenta resumo em português.
RESUMO
Electrical conductivity of milk is an indirect method for diagnosis of mastitis that can be used as criterion of selection in breeding programs, to obtain more resistant animals to infection. Data from 9,302 records of electrical conductivity from the morning milking (ECM), 13,070 milk yield records (MY) and 11,560 records of milking time (MT), of 1,129 first lactation Holstein cows, calving from 2001 to 2011, were used in statistical analysis. Data of eight herds of Southeast region of Brazil were obtained by the WESTFALIA® electronic milking machines, with Dairyplan management system. Two analysis were performed: a multitrait, including MY, MT and ECM, and an unitrait, considering only test-day morning electrical conductivity. The model included additive genetic, permanent environmental and residual effects as random. Additionally, contemporary groups (CG), the age of cow at calving (AGC) and days in milk (DIM) (linear and quadratic regression) were included as fixed effects. The CG was composed by herd, year and month of test. DIM classes were formed with weekly intervals, constituting a total of 42 classes. The variance components were estimated by Restricted Maximum Likelihood Method (REML), using the Wombat software. The average and standard deviation of ECM were 4.80 mS cm-1 and 0.54 mS cm-1, respectively. The heritability estimates by multitrait model and their standa
O artigo não apresenta resumo em português.