Estimates Of Lactation Yields Research Articles

Genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows

Lactation yield estimates standardized to common lactation lengths of 270-d or 305-d equivalents are commonly used in management decision support tools and dairy cow genetic evaluations. The use of such measurements to quantify the (genetic) merit of individual cows fails to penalize cows that do not reach the standardized lactation length, or indeed reward cows that lactate for more than the standardized lactation length. The objective of the present study was to quantify the genetic and nongenetic factors associated with lactation length in seasonal-calving, pasture-based dairy cows. A total of 616,350 lactation length records from 285,598 Irish cows were used. Linear mixed models were used to quantify the associations between lactation length and calving month, parity, age at calving, previous dry period length, calving difficulty score, heterosis, recombination loss, breed, and herd size, as well as to estimate the genetic and residual variance components of lactation length. The median lactation length in the edited data set was 288 d, with 27% of cows achieving lactations of at least 305 d. Relative to cows calving in January, the lactations of cow calving in February, March, or April was, on average, 4.2, 12.7, and 21.9 d shorter, respectively. The lactation length of a first parity cow was, on average, 7.8, 8.6, and 8.4 d shorter than that of second, third, and fourth parity cows, respectively. Norwegian Red and Montbéliarde cows had, on average, a 4.7- and 1.6-d shorter lactation than Holstein-Friesian cows, respectively. The heritability estimate, coefficient of genetic variation, and repeatability estimate of lactation length were 0.02, 1.2%, and 0.04, respectively. Based on the genetic standard deviation for lactation length estimated in the present study (3.3 d), cows ranked in the top 20% for genetic merit for lactation length would be expected to have lactations 9.2 d longer than cows in the bottom 20%, demonstrating exploitable genetic variability. Given the vast array of genetic and nongenetic factors associated with lactation length, an approach which combines improved management practices and selective breeding may be an efficient and effective strategy to lengthen lactations.

Lactation yield: Interval level comparison of milk records for genetic improvement in Friesian vs Arsi crossbred cows in the highlands of south eastern Ethiopia

Milk recording intervals was studied by analysing 1220 lactation records of Friesian x Arsi crossbred cows kept in south eastern highlands of Ethiopia. Milk Recording Intervals (MRI) comparison was made at 15, 30 and 45 day's length. Accuracy was measured in terms of percentage difference between actual and estimated yield, Root Mean Square Error (RMSE) and coefficient of determination (R2). The study revealed that 15, 30 and 45-day MRI can estimate lactation yield accurately to extent of less than five percent error. Lactation yield estimated by 15-day MRI was marginally more accurate with higher R2 (99.6%) and lower RMSE (34.8) values compared to 30 and 45-day MRI. Simple regression analysis indicated that yield of 9th period (121-135 days) in 15-day; the 5th period (121-150 days) in 30-day and the 3rd period (91-135) in 45-day time interval provided reliable estimate of 305-day yield. The step-wise regression analysis showed that combination of more than three records did not result in increasing the accuracy of estimates. Thus 30 and 45-day MRI can be used in the estimation of lactation yield in Friesian x Arsi crossbred cows.Keywords: Accuracy, Lactation yield, Interval comparison, Test day

Preweaning milk replacer intake and effects on long-term productivity of dairy calves

The preweaning management of dairy calves over the last 30 yr has focused on mortality, early weaning, and rumen development. Recent studies suggest that nutrient intake from milk or milk replacer during the preweaning period alters the phenotypic expression for milk yield. The objective of this study was to investigate the relationship between nutrient intake from milk replacer and pre- and postweaning growth rate with lactation performance in the Cornell dairy herd and a commercial dairy farm. The analysis was conducted using traditional 305-d first-lactation milk yield and residual lactation yield estimates from a test-day model (TDM) to analyze the lactation records over multiple lactations. The overall objective of the calf nutrition program in both herds was to double the birth weight of calves by weaning through increased milk replacer and starter intake. First-lactation 305-d milk yield and residuals from the TDM were generated from 1,244 and 624 heifers from the Cornell herd and from the commercial farm, respectively. The TDM was used to generate lactation residuals after accounting for the effects of test day, calving season, days in milk, days pregnant, lactation number, and year. In addition, lactation residuals were generated for cattle with multiple lactations to determine if the effect of preweaning nutrition could be associated with lifetime milk yield. Factors such as preweaning average daily gain (ADG), energy intake from milk replacer as a multiple of maintenance, and other growth outcomes and management variables were regressed on TDM milk yield data. In the Cornell herd, preweaning ADG, ranged from 0.10 to 1.58kg, and was significantly correlated with first-lactation yield; for every 1kg of preweaning ADG, heifers, on average, produced 850kg more milk during their first lactation and 235kg more milk for every Mcal of metabolizable energy intake above maintenance. In the commercial herd, for every 1kg of preweaning ADG, milk yield increased by 1,113kg in the first lactation and further, every 1kg of prepubertal ADG was associated with a 3,281kg increase in first-lactation milk yield. Among the 2 herds, preweaning ADG accounted for 22% of the variation in first-lactation milk yield as analyzed with the TDM. These results indicate that increased growth rate before weaning results in some form of epigenetic programming that is yet to be understood, but has positive effects on lactation milk yield. This analysis identifies nutrition and management of the preweaned calf as major environmental factors influencing the expression of the genetic capacity of the animal for milk yield.

Suitability of simplified methods for monthly and twice-monthly milk recording, and new prediction factors for the alternate a.m./p.m. method in dairy ewes under a low-input production system

Sicilo-Sarde dairy flock test-day data were analysed (1) to check predicting ability of ten milk recording procedures, based on information from a single monthly or bimonthly milking and (2) to look for the best pair of factors for predicting daily milk yield from either morning or afternoon milkings for the alternate testing method (AT). Prior to analyses, data were adjusted for variation factors with known significant effect. Number of test-day observations was 4755 from 458 lactations of 288 ewes. Losses of precision associated with simplified methods were evaluated by comparing estimated lactation yields with those observed both in a reference plan, where the two daily milkings were recorded at 2-weekly intervals and in the official A4 milk recording (monthly recording of the two daily milkings). Ranking of simplified plans based on their accuracy was still the same under either monthly or twice-monthly frequency. Estimates of lactation yields showed more lack of precision when the usual monthly designs were compared with twice-monthly sampling of both a.m. and p.m. milkings. Losses of precision ranged from 5.1%, for the A4 plan, to 14.6%. Thus, milk production should be estimated from both mikings when their measurement is economically feasible. When only one milking is weighed, designs based on-or beginning with-the a.m. milking were more accurate. There was no evidence of improvement in sampling accuracy by adjustment for milking interval or production level. For practical and economic reasons, the design alternating a.m. and p.m. milkings, without adjustment, is suggested for ovine milk recording. In such a case, new factors for estimating daily production from the measured milking (1.7, 2.3) should be used rather than the factors currently in use (2, 2) because they improved the loss of precision by more than 13% in a monthly recording system.

Major Advances in Genetic Evaluation Techniques

The past quarter-century in genetic evaluation of dairy cattle has been marked by evolution in methodology and computer capacity, expansion in the array of evaluated traits, and globalization. Animal models replaced sire and sire-maternal grandsire models and, more recently, application of Bayesian theory has become standard. Individual test-day observations have been used more effectively in estimation of lactation yield or directly as input to evaluation models. Computer speed and storage are less limiting in choosing procedures. The increased capabilities have supported evaluation of additional traits that affect the net profitability of dairy cows. The importance of traits other than yield has increased, in a few cases due to an antagonistic relationship with yield. National evaluations combined internationally provide evaluations for bulls from all participating countries on each of the national scales, facilitating choices from among many more bulls. Selection within countries has increased inbreeding and the use of similar genetics across countries reduces the previously available outcross population. Concern about inbreeding has prompted changes in evaluation methodology and mating practices, and has promoted interest in crossbreeding. In just the past decade, distribution of genetic evaluations has gone from mailed paper or computer tapes for a limited audience to publicly accessible, request-driven distribution via the Internet. Among the distributed information is a choice of economic indices that combine an increasing array of traits into numbers reflecting breeding goals under different milk-pricing conditions. Considerable progress in genomics and the mapping of the bovine genome have identified markers for some deleterious recessive genes, but broader benefits of marker-assisted selection are still in the future. A possible exception is the proprietary use of DNA testing by semen producers to select among potential progeny test bulls. The collection and analysis of industry-wide data to evaluate genetic merit will continue to be the most important tool for genetic progress into the foreseeable future.

Losses of precision associated with simplified designs of milk recording for dairy ewes.

Simplified designs of milk yield recording based on the yield of a single monthly milking, adjusted or not for interval between milkings and for production level, were simulated and evaluated for 3173 ewe-test-day records belonging to 155 lactations of Churra dairy ewes. Losses of precision associated with simplified methods were evaluated by comparing estimated lactation yields with those observed both in a reference plan, where the two daily milkings were recorded at weekly intervals, and in the official A4 milk recording (monthly records of the two daily milkings). Estimates of lactation yields were less precise when the usual monthly designs were compared with a weekly sampling of both a.m. and p.m. milkings. The losses of precision were high at 9.4-36.2% including the A4 plan. The yield from only the milking period was more predictable than milk yield from the whole lactation (suckling and milking periods) and should consequently be adopted in dairy ewes. All options with one daily milking every month were more accurate when the corresponding plan was based on, or began with, the a.m. milking (loss of precision 14.9-15.8%). There was no evidence of improvement in sampling accuracy by adjusting for the preceding interval between milkings or production level. For practical and economic reasons, the design alternating a.m. and p.m. milkings every month, without adjustment, is suggested for ovine milk recording.

Possibility of reducing milk recording and sampling in Holstein dairy cattle of Iran

The Iranian Animal Breeding Center (IABC) is currently milk recording and sampling three time per test-day(8 hours interval) approximately once every month. Milk samples are analyzed for fat and protein contents. There are some difficulties for having precise milk samples in some farms especially for three times sampling per day, and the costs of three times recording and sampling is also a problem. Estimation of lactation yield for milk, fat and protein yield is done based on test-day records and samples and the accuracy of there estimates depend on the precision of test day records especially milk sampling. The results of milk content are not satisfactory for farmer and specialist in the current milk recording system. Some researches have been done to reduce milk recording and sampling per test day (1, 2). In addition potential benefits of reducing milk recording and sampling are that more herds can be supervised and recorded per month. The objective of this research was to consider the possibility of reducing milk recording and sampling in herds with three times milking per test-day in industrial Holstein farms.

Comparison of test interval and best prediction methods for estimation of lactation yield from monthly, a.m.-p.m., and trimonthly testing.

A method with best prediction properties that condenses information from all test days into measures of lactation yield and persistency has been proposed as a possible replacement for the test interval method and projection factors. The proposed method uses previously established correlations between individual test days and includes inversion of a matrix for each lactation. Milk weights that were representative of monthly, a.m.-p.m., and trimonthly test plans were examined to compare the accuracy of best prediction and test interval methods for estimating lactation yield. Individual milk weights or daily yields of 658 Canadian cows in 17 herds were selected to correspond to test intervals for 100,000 US cows. For a.m.-p.m. testing, the initial milk weight that was credited was selected randomly from the a.m. or p.m. milking and was alternated thereafter. Trimonthly credits were from one of the first three designated test day weights, selected randomly, and each third designated test weight thereafter. Correlations between 305-d actual lactation yield and lactation estimates by the test interval method were 0.97, 0.96, and 0.93 for monthly, a.m.-p.m., and trimonthly testing, respectively. Corresponding correlations for the best prediction method were 0.97, 0.97, and 0.93. Standard deviations of differences between estimated and 305-d actual yields for monthly, a.m.-p.m., and trimonthly testing were 373, 400, and 546 kg, respectively, for best prediction regressed on herd mean, which was a reduction in estimation error of 4, 6, and 10% over the test interval method. The advantage of best prediction was moderate if two milk weights were recorded monthly and was larger if testing was less frequent. Advantages also were found for fat and protein yields estimated by multitrait best prediction for records with reduced component sampling.

183. Errors involved in the estimation of the lactation yield of protein according to the intervals between sampling

Variations in protein yield of a cow are due to changes both in her yield of milk and in the percentage of protein in her milk. If it were possible to have, for each day of lactation, figures for the yield of milk and its percentage of protein, the estimation of lactation yield of protein would be easy, but in practice this is not possible since the determination of protein in milk is a long and laborious process.