Search

Variances of errors of prediction for sire evaluations which included only first records and for those with records of all lactations were compared for bulls of Ayrshire, Guernsey, Jersey, and Brown Swiss breeds used by artificial insemination with daughters having Dairy Herd Improvement records processed at the New York Dairy Records Processing Laboratory. The model for best linear unbiased prediction included fixed effects of sire group and herd-year-season of freshening and random effects of sires within group, sire-by-herd interaction (to account for environmental correlation among paternal sisters), cow within sire and herd, and residual. Variances of solutions for group effects were generally small relative to variances of prediction errors for sire effects. Using all lactation records, however, reduced variances of group solutions by 7 to 14% for groups of sires used artificially and by 20 to 24% for groups used in natural service. Use of all lactation records decreased the variance of prediction error of the sire solutions so that 15 daughters per sire with all lactations gave accuracy equivalent to 25 daughters using only first records; use of all lactation records with 25 daughters gave accuracy equivalent to 40 daughters with only first records. Genetic progress per year from selection of bulls to sire daughters would be expected to be 10 to 15% greater with use of all lactation records than with use of only first lactation records. The comparable increase from selection of bulls to sire replacement bulls would be 3 to 10%. These theoretical increases must be weighed against possible biases from use of records other than first lactation.

Age-month factors were developed for milk, fat, and protein yields. Records used in the analysis consisted of 769,410 lactation records of Holstein cows freshening in New York and New Jersey from July 1982 through August 1984. The mixed model used to describe the data contained fixed effects due to an overall mean, age-month of calving, herd-year, and random effects due to cow and error terms. There were 26 age groups by 12 mo of freshening for a total of 312 age-month estimates for each of the three yield traits. Results showed a definite age by month interaction with age being more important for younger cows while month effects assumed more importance as the cow matures. Multiplicative age-month correction factors were developed and are presented along with plots of the age-month factors for milk, fat, and protein yield. Factors differed for three yield traits. Fat and protein factors were higher than corresponding factors for milk.

Records on 558,654 Holstein cows in the northeastern United States were used to calculate sire summaries for milk, fat, and stayability for 36, 48, 60, 72, and 84 mo. Predicted Difference Type was obtained from the Holstein-Friesian Association of America. Genetic correlations between production and stayability ranged from .20 to .55 with the lowest genetic correlations with 36- and 48-mo stayability. Genetic correlation between type and stayability were −.11, −.14, −.15, −.11, and −.09 for 36, 48, 60, 72, and 84-mo stayability. Stayabilities at different ages are correlated closely genetically. Sires selected for high first lactation production will have daughters which last longer. Screening bulls on 48-mo stayability would be the most desirable because of high genetic correlations with production and older stayabilities and because bulls can be evaluated at a younger age.

Financial management is critically important for maintaining an efficient and profitable dairy farm enterprise. For good financial management, monthly cash flow planning is a necessity. The most important component in cash flow planning is projecting the income from milk sales. Projection factors were developed to predict for a cow the monthly milk yield for the next 6 mo. Predictions for individual cows then can be summed for the entire herd, and from the forecasted milk price the milk check can be estimated. The data consisted of 204,558 complete Holstein lactations from 1959 to 1969 in 2100 New York herds. Different sets of projection factors were developed for cows in milk at the time of prediction and for cows entering production during the predicted period. Factors were developed considering lactation number (1, 2, 3, and 4 or greater), season of calving (January to April, May to August, September to December) and, for the first three lactations, age at calving (younger and older). The accuracy of these predictions was measured by the correlation between the actual and predicted milk yield by month of prediction. This correlation was highest (.90) for the 1st mo of prediction and decreased as the predicted month was further away, being .52 for the 6th mo of prediction. To be effective in assisting dairy farmers with their cash flow planning activity, the procedure developed should be incorporated in the Dairy Herd Improvement system. Consequently, the farmer will receive a monthly report that includes the predicted milk checks for the next 6 mo.

A 3-year study of 24 commercial dairy herds measured the value of hygiene (teat dipping in 4% chlorine) and dry cow therapy (1million units penicillin, 1gram dihydrostreptomycin) in the reduction of infection and change in milk production. Infection dropped from 28.1% to 7.1% of the quarters. Herds on the mastitis control program produced an average of 477kg of milk per cow more per year for each of the 3 years than the average New York Dairy Herd Improvement herd after adjustment for differences in initial production. A least squares analysis determined factors associated with mastitis that have the greatest effect on milk production. Presence of organisms in the udder caused the greatest decrease in milk production while the genus of organism affected the loss. Quarters infected with Staphylococcus aureus produced approximately 760kg less milk per lactation than uninfected quarters. Quarters harboring other organisms, including some regarded as nonpathogenic, produced more than 500kg of milk less per lactation than uninfected quarters. Quarters infected with more than one pathogen at the same time had an additional decrease in production. Reduction in milk production was most severe when infections began during early lactation. However, infections that lasted less than 40 weeks caused a greater decrease in milk production than those lasting longer.

The data consisted of 204,558 complete Holstein lactations in 2,100 herds compiled by the New York Dairy Records Processing Laboratory from 1959 to 1969. All lactation records had to have a 9th or 10th test day to be complete. The generalized least squares analysis used a model including mean, herd-year, and season-age-stage as fixed effects. The error term included random effects of cow and residual variation. Means for specified stages of lactation for milk and fat were estimated for lactations 1, 2, 3, and 4 or greater which were grouped by age of freshening, two age groups for the first three lactations and cne for fourth and later lactations. Extension factors differed from current United States Department of Agriculture factors. The new factors emphasize the need to consider lactation number, season, and age at freshening in extending lactation records in progress. Extension factors differ for each lactation, especially between the first two and later lactations. To consider season of freshening is important for early stages of lactation. Age is important for factors for earlv stages of lactation but less so as length of lactation increases. Differences due to age also become less important as lactation number increases. Factors for third and later lactations are only slightly affected by age of cow.

Selection procedures which weight equally each test day sample may not be optimum for selection on test days. Monthly test day data from 63,300 records of artificially sired Holsteins with 305-day lactations were from the New York Dairy Records Processing Laboratory. Heritabilities (h 2) were estimated intraherdyear-season from sire components of variance for monthly test day production within lactations 1, 2, 3, 4, and 5 or greater. Heritability of lactation fat percentage decreased from .60 to .40 from first to fifth lactations whereas heritability for 305-day milk yield increased slightly from .25 to .37 with succeeding lactations. Heritabilities for both fat percentage and milk production of monthly test days were lower for early and later tests than for middle monthly tests. Genetic and phenotypie correlations for early and late months with total lactation were less than for middle months. Estimates of genetic gain by selecting on bimonthly or trimonthly test days were almost as great as by selecting on the colapleted 305-day lactation record. Quadramonthly records showed only a slight decrease in relative response as compared to bi- or trimonthly testing. Selecting on part records would not result in any measurable loss of genetic gain in total milk yield or lactation fat test as compared to monthly testing.

Effects of days carried calf, days dry, and weight of first calf heifers were studied using records of Holstein cows processed at the Northeast Dairy Records Processing Laboratory between July 1980 and August 1984. Multiplicative factors were estimated for days carried calf for milk, fat, and protein using a model that adjusted for the age-month and herd-year of freshening. Factors developed show a close relationship between protein and milk with fat factors being smaller. Factors also are smaller than others reported in the literature. First lactation factors differed from second and third lactation factors. Analysis of days dry indicated that optimum number of days dry between lactations 1 and 2, 2 and 3, and 3 and 4 for maximized subsequent yield was 51 to 60 d dry for all lactations. Calculated F values showed greater significance for days dry than age-month of freshening. Optimum freshening weight of a first calf heifer to maximize first lactation milk yield is between 544 and 567 kg. The F values for weight at freshening were more significant than age-month of freshening.