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PubMed2006

Effects of suckling intensity on milk yield and piglet growth from lactation-enhanced gilts.

The effects of suckling intensity on milk yield and piglet growth were determined when lactation capacity of the sow was enhanced through overexpression of a mammary-specific transgene, bovine alpha-lactalbumin. Lactational response to increased suckling stimulation was determined by fostering litters of the same age (d 1) or 7 d older (d 7) than the day of lactation to sows nontransgenic (control) or transgenic (TG) for bovine alpha-lactalbumin. Twenty first-parity gilts were allocated to 4 treatments dependent on gilt genotype and age of litter fostered (control d 1, control d 7, TG d 1, and TG d 7). Litters were standardized to 10 piglets within 24 h postpartum, and nonbirth piglets were fostered to gilts with an equal litter BW within age groups at 36 h postpartum. Milk yield was determined by the weigh-suckle-weigh method on d 6, 9, 12, 15, and 18 of lactation. Mean daily milk yield was greater (P = 0.031) for TG gilts compared with control gilts and tended to be greater (P = 0.056) for all gilts with d-7 piglets compared with those with d-1 piglets. Daily milk yield of TG d 7 gilts increased rapidly to peak at d 9 and was greater than milk yield of all control gilts at d 9 (P < 0.01), 12 (P < 0.02), and 15 (P < 0.02). Mean daily milk yield of TG d 7 gilts was 2.1 kg greater (P = 0.002) than for control d 7 gilts and 2.0 kg greater (P = 0.004) than for TG d 1 gilts. Daily milk yield of control d 1 gilts was not different from that of TG d 1 gilts (P = 0.49) or control d 7 gilts (P = 0.63). Piglet BW gain between d 3 and 6 was greater (P < 0.01) in the TG d 7 group than for all other groups and was greater (P < 0.05) than the control groups between d 6 and 9. No difference was found when comparing accumulated BW gain of the piglets between the day of age at foster (d 1 vs. 7; P = 0.606) or between the control d 1 and control d 7 groups (P = 0.759). Accumulated BW gain of piglets suckling TG d 7 gilts from d 3 through 9 was greater (P < 0.02) than that of the other groups and continued to be greater (P < 0.05) than that of either of the control groups through d 15. However, by d 15, accumulated BW gain of piglets suckling TG d 1 gilts was no longer different (P = 0.40) from that of the TG d 7 group and was greater (P < 0.05) than that of the control d 1 group. The enhanced lactation potential of these TG gilts synergized with suckling intensity to stimulate increased milk production during early lactation, resulting in increased piglet growth.

Animals↗
PubMed2000

Effect of herd environment on the genetic and phenotypic relationships among milk yield, conception rate, and somatic cell score in Holstein cattle.

A total of 248,230 primiparous records of Holstein cows calving from 1987 to 1994 (daughters of 588 sires in 3042 herds) was used to evaluate potential genotype by environment interactions among mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service. Herds were classified into low and high environmental groups using three different criteria: standard deviation of herd mature equivalent milk yield, a combination of herd mature equivalent milk yield mean and standard deviation, and the herd mean of body weight at first calving divided by age at first calving. Genetic parameters were modeled by using multiple-trait linear mixed models and were fitted using the multiple-trait derivative-free software. Heritabilities for mature equivalent milk yield, lactation mean somatic cell score, and conception rate at first service were 0.221, 0.106, and 0.015 in low environment herds and 0.300, 0.093, and 0.009 in high environment herds, respectively. Genetic (and phenotypic) correlations between mature equivalent milk yield and lactation mean somatic cell score, mature equivalent milk yield and conception rate at first service, and lactation mean somatic cell score and conception rate at first service were 0.277, -0.417, and -0.209, (-0.049, -0.180, and -0.040) and 0.173, -0.318, and -0.144, (-0.087, -0.166, and -0.035) in low and high environment herds, respectively. The genetic correlations between pairs of traits were consistently smaller in high environment herds, suggesting that differences in management between the two environment levels lessened the antagonistic genetic association between the traits studied. A long-range plan for low environment herds should focus on improving the level of management, which would greatly reduce the unfavorable correlated changes in lactation mean somatic cell score and conception rate at first service associated with the genetic improvement of mature equivalent milk yield.

Animals↗
PubMed2002

Genetic parameters of dairy character, protein yield, clinical mastitis, and other diseases in the Danish Holstein cattle.

The primary aim of this study was to estimate genetic correlations between dairy character, protein yield, clinical mastitis, and other diseases. Data consisted of first lactation records of Danish Holstein cows calving from 1990 to 1999. After editing, the data included records on 934,639 cows, of which 101,853 were assessed for dairy character, 472,421 for diseases, and 834,993 for protein yield. The disease traits were defined as binary traits in the period from 10 d before to 50 d after calving for clinical mastitis, and from 10 d before to 100 d after calving for diseases other than mastitis. Data were analyzed with a linear sire model using the method of AI-REML. Heritabilities were estimated to be 0.265 for protein yield, 0.261 for dairy character, 0.035 for clinical mastitis, and 0.020 for diseases other than mastitis. Estimates of genetic correlations between protein yield and dairy character, protein yield and clinical mastitis, and protein yield and diseases other than mastitis were 0.38, 0.33, and 0.14. Between the two disease traits, the genetic correlation was 0.24. The genetic correlation between dairy character and clinical mastitis was 0.24. Between dairy character and diseases other than mastitis the genetic correlation was 0.41. Thus, cows with high score for dairy character were more prone to diseases. The genetic correlation between dairy character and the disease traits, when both traits were adjusted for protein yield, was 0.13 for clinical mastitis and 0.39 for diseases other than mastitis. These findings suggest that, dairy character should be given a negative rather than a positive weight in the breeding goal.

Animals↗
PubMed2002

Estimating daily fat yield from a single milking on test day for herds with a robotic milking system.

The objective of this study was to estimate the daily fat yield and fat percentage from one sampled milking per cow per test day in an automatic milking system herd, when the milking times and milk yields of all individual milkings are recorded by the automatic milking system. Multiple regression models were used to estimate the 24-h fat percentage when only one milking is sampled for components and milk yields and milking times are known for all milkings in the 24-h period before the sampled milking. In total, 10,697 cow test day records, from 595 herd tests at 91 Dutch herds milked with an automatic milking system, were used. The best model to predict 24-h fat percentage included fat percentage, protein percentage, milk yield and milking interval of the sampled milking, milk yield, and milking interval of the preceding milking, and the interaction between milking interval and the ratio of fat and protein percentage of the sampled milking. This model gave a standard deviation of the prediction error (SE) for 24-h fat percentage of 0.321 and a correlation between the predicted and actual 24-h fat percentage of 0.910. For the 24-h fat yield, we found SE = 90 g and correlation = 0.967. This precision is slightly better than that of present a.m.-p.m. testing schemes. Extra attention must be paid to correctly matching the sample jars and the milkings. Furthermore, milkings with an interval of less than 4 h must be excluded from sampling as well as milkings that are interrupted or that follow an interrupted milking. Under these restrictions (correct matching, interval of at least 4 h, and no interrupted milking), one sampled milking suffices to get a satisfactory estimate for the test-day fat yield.

Animals↗
PubMed2002

Investigations on milk flow and milk yield from teats with milk flow disorders.

The objective of this study was to investigate peak milk flow, average milk flow, and milk yield in teats with milk flow disorders. A total of 100 hard milking teats were studied in 97 cows. Teats with milk flow disorders were examined endoscopically. Quarter milk flow and quarter milk yield were examined with four Lactocorders attached to a quarter milking machine. Peak milk flow, average milk flow, and milk yield were measured in all teats of the udder before treatment of the affected teat, as well as 1 and 6 mo later. Teats with milk flow disorders were compared to all other teats of the same udder. Before treatment, peak milk flow from affected teats was 20%, average milk flow 14%, and milk yield 53% of the control teats, adjusted for other significant explanatory variables. Milk flow and milk yield increased after surgical treatment of the affected teats. Six months after treatment peak milk flow was 79%, average milk flow 76%, milk yield was 71% compared with control teats. We conclude from these findings that teat endoscopy and measuring quarter milk flow and milk yield with Lactocorders are useful tools for examining teats with milk flow disorders.

Animals↗
PubMed2002

Genetic parameters and responses of linear type, yield traits, and somatic cell scores to divergent selection for predicted transmitting ability for type in Holsteins.

The objective was to examine the direct and correlated responses of linear type, yield traits, and somatic cell scores (SCS) to divergent selection for predicted transmitting ability for type (PTAT) in Holsteins, while maintaining selection for yield traits across lines. For four generations, one-half of the University of Nebraska research Holstein herd was bred to Holstein sires with PTAT > 1.50 and the other half to sires with PTAT < 1.25, with nearly equal predicted transmitting abilities for yield traits for both groups. Estimates of genetic and residual correlations and heritabilities were obtained from REML estimates of (co)variance components. Model for type traits included fixed effect of date cows were classified, effects of age in days at freshening, and stage of lactation at classification. Year-season when cows freshened was fixed effect in model for yield and SCS. Animal genetic and residual effects were random. Final score, milk, fat, and protein yields, and SCS had heritability estimates of 0.38, 0.13,0.22, 0.09, and 0.38, respectively. Heritability estimates for type traits ranged from 0.04 to 0.52. Estimates of genetic correlations of final score with SCS and milk, fat, and protein yields were -0.64, 0.01, -0.18, and 0.06, respectively. Estimates of genetic correlations among linear type traits ranged from -0.77 to 1.00. Means of estimated breeding values for final score, stature, strength, body depth, fore udder attachment, rear udder height and width, udder cleft, udder depth, and front teat placement were significantly different between lines in the third generation. Milk, fat, and protein yields were not significantly different between lines in third generation, whereas SCS was significantly different. Estimate of genetic correlation between final score and SCS suggest that selection on PTAT would result in a change for SCS. In this study, divergent selection on PTAT of sires had a significant effect on udder and body traits, but little or no effect on feet and leg traits.

Animals↗
PubMed2003

Search for pleiotropic QTL on chromosome BTA6 affecting yield traits of milk production.

The primary aim of this study was to investigate whether previous findings of similar quantitative trait loci (QTL) positions for correlated yield traits are due to a pleiotropic QTL. We applied a multitrait variance component based QTL mapping method to a dataset involving five granddaughter families from the German Holstein dairy cattle population. The marker map contained 16 microsatellite markers, distributed across chromosome BTA6. A chromosomewise significance threshold was used, because BTA6 is known to harbor QTL for several milk traits. To evaluate the results from the multivariate, across-family analysis, we also conducted single-family analyses using the least squares method of QTL estimation. The results provided two significant QTL findings at 49 and 64 cM for milk yield in different families and putative QTL at 68 cM for fat yield and at 71 cM for protein yield in another family. The results for fat and protein yield were confirmed by a univariate, across-family variance components analysis. The multivariate analysis of three bivariate trait combinations resulted in a significant pleiotropic QTL finding at 68 cM for fat yield and protein yield, bracketed by markers TGLA37 and FBN13. The estimates of variance contribution due to this QTL were 23% and 25%, respectively.

Analysis of Variance↗
PubMed2003

Effects of once versus twice daily milking throughout lactation on milk yield and milk composition in dairy goats.

The effects of once (1X) vs. twice (2X) daily milking throughout lactation on milk yield, milk composition, somatic cell count (SCC), and udder health were studied in 32 Murciano-Granadina dairy goats. Goats were assigned at wk 2 of lactation to two treatment groups; once daily milking at 0900 (1X, n = 17), or twice daily milking at 0900 and 1700 (2X, n = 15). Milk yield was recorded weekly until wk 28, and milk composition and SCC were evaluated for each individual udder half at each milking at wk 2 and 4 of lactation and then, monthly until the end of the experiment. Once daily milking resulted in an 18% reduction in the yield of 4% fat-corrected milk compared to twice daily milking (1.61 vs. 1.95 L/d, respectively). This reduction was more marked from wk 2 to 12 than in mid and late lactation. Response to milking frequency also varied according to parity number where goats of less than four parities suffered more milk yield losses during 1X than older goats. Milk of 1X goats contained higher percentages of total solids (13.6 vs. 12.9%), fat (5.10 vs. 4.62%) and casein (2.57 vs. 2.35%) than milk of 2X goats, but milk protein percentage did not differ between treatments (3.28 vs. 3.20%). Yields of total solids, fat, protein and casein tended to be higher for 2X than 1X. Milk SCC did not differ between treatments. We conclude that application of once daily milking in Murciano-Granadina dairy goats moderately reduced milk yield without negative effects on milk composition and udder health. Losses in milk yield would be reduced if 1X is practiced during mid- or late lactation and in older goats. An increase in labor productivity and a higher farmer's standard of living is also expected.

Animals↗
PubMed2004

Relationship of test-day somatic cell score with test-day and lactation milk yields.

To determine the relationship of test-day (TD) somatic cell score (SCS) to TD and lactation milk yields, 1,320,590 records from Holstein first and second calvings from 1995 through 2002 were examined. All lactations had recorded yield and SCS for at least the first 4 TD. Least square analyses were conducted for yields on TD 2 through 10 within herd and cow. The model included regressions on current TD SCS and mean SCS of all previous TD with separate estimates by parity; effects for parity and calving year were included as well as regression on days in milk on TD 1. Corresponding analyses were conducted without regression on current SCS. An analysis of lactation yield was performed with a similar model and regression on all TD SCS. The SCS was highest most often on TD 1 for parity 1 (22.5%) and on TD 10 for parity 2 (18.5%). Regression of TD milk yield on mean of previous TD SCS was highest during the latter half of lactation (maximum of -0.346 kg/SCS unit on TD 9) for parity 1 and during TD through 7 (maximum of -0.366 kg/SCS unit on TD 4) for parity 2. Regression of TD yield on current TD SCS tended to be larger for later lactation. Regression of lactation yield on TD SCS was negative and important for TD 1 through 6 for parity 1 and for all TD for parity 2. To minimize milk loss, mastitis control is most important immediately pre- and postcalving for parity 1 and throughout lactation for parity 2.

Animals↗
PubMed2004

Using activity and milk yield as predictors of fresh cow disorders.

The objective was to determine whether daily walking activity and milk yields could be used as predictors of metabolic and digestive disorders early in lactation. Data were collected from 1996 through 1999 from 1445 dairy cows in 3 Florida herds. Walking activity, milk yield, and other measures were collected from a computerized dairy management system. Mixed models analysis was used for data on cows before their first detected estrus, as identified by difference in activity. Healthy cows were defined as those without any metabolic or digestive disorder during the prebreeding stage, whereas a sick cow had an occurrence of those disorders at any time during the prebreeding stage. Metabolic disorders were ketosis, retained placenta, and milk fever. Digestive disorders included displaced abomasum, indigestion, reduced feed intake, traumatic gastritis, acidosis, and bloat. Data from cows with known cases of ketosis, left displaced abomasum, and digestive disorders were analyzed to determine changes in activity and milk yield before those specific disorders were clinically diagnosed. Although walking activity was generally lower among sick cows, cows with ketosis, left displaced abomasum, and digestive disorders had higher than average activity 8, 9, and 8 d, respectively, before each diagnosed disorder. Daily milk yields of sick cows were approximately 15 kg/d less than milk yields of healthy cows. Milk yields were lower by 6, 7, and 5 d, respectively, before diagnoses of ketosis, left displaced abomasum, and digestive disorders. Cows with ketosis, left displaced abomasum, and general digestive disorders could possibly be detected about 5 to 6 d earlier than clinical diagnoses based on changes in daily walking activity and milk yield.

Abomasum↗
PubMed2004

Genotype x environment interaction for yield and somatic cell score with automatic and conventional milking systems.

The objective of this study was to quantify genotype by environment interaction (G x E) between automatic milking systems (AMS) and conventional milking systems (CMS) for test-day milk, fat, and protein yield and for test-day somatic cell score (SCS) in The Netherlands. The G x E was studied in 2 ways: 1) between AMS farms and CMS farms in the same period and 2) within farms comparing the period before introduction of AMS with the period after introduction of AMS. For both sub-objectives, a separate data set was generated. Test-day records were used to be more flexible with respect to the introduction date of AMS. Multivariate, fixed regression, test-day sire models were used to estimate variance components. Genetic correlations between AMS farms and CMS farms in the same period were 0.93, >0.99, 0.98, and 0.79 for test-day milk yield, fat yield, protein yield, and SCS, respectively. Genetic correlations within farms between the period before and after introduction of AMS were lower for production traits and higher for SCS: 0.89, 0.91, 0.87, and >0.99, respectively, for test-day milk yield, fat yield, protein yield, and SCS. Heterogeneity of variance was observed between AMS and CMS in both data sets. Especially the residual variance increased with automatic milking. As a consequence, the heritability tended to be lower for automatic milking. It was concluded that effects of G x E are small between AMS and CMS. Therefore, AMS farms can select sires accurately based on national rankings.

Analysis of Variance↗
PubMed2005

A meta-analysis on the relationship between intake of nutrients and body weight with milk volume and milk protein yield in dairy cows.

Previously observed strong relationships between dry matter (DM) intake and milk yield in dairy cows were the basis for this meta-analysis aimed to determine the influence of intake of specific dietary nutrients on milk yield and milk protein yield in Holstein dairy cows. Diets (563) from feeding trials published in the Journal of Dairy Science were evaluated for nutrient composition using 2 diet evaluation programs. Intake of nutrients was estimated based on DM intake and program-derived diet composition. Data were analyzed with and without the effect of stage of lactation. Models based on intake of nutrients improved prediction of milk yield and milk protein yield compared with DM intake alone. Intake of net energy of lactation was the dominant variable in milk yield prediction models derived from both diet evaluation models. Milk protein yield models also improved prediction over the DM intake model. These models were dominated by ruminally undegradable protein intake and included a number of energy-related intake variables. In most models, incorporating stage of lactation improved the model fit.

Animal Nutritional Physiological Phenomena↗
PubMed2005

Effects of week of lactation and genetic selection for milk yield on milk fatty acid composition in Holstein cows.

Control (CL) and select line (SL) dairy cows (n = 22) managed identically but differing in milk yield (>4100 kg/305 d) were used to determine differences in milk fatty acid profile as lactation progressed. Milk yield was recorded daily and milk samples were collected during wk 1, 4, 8, 12, and 16 postpartum for milk composition analysis. Milk samples from wk 1, 8, and 16 were also analyzed for fatty acid composition. Select-line cows produced more milk (44.4 vs. 31.2 kg/d) and milk components than CL cows during the 16-wk period. There was no difference in rate of milk yield increase, but peak milk yield for SL cows was greater and occurred later in lactation. There were no differences in milk SCC or milk fat, protein, or lactose content. Selection for milk yield did not affect the content of most individual milk fatty acids; however, compared with CL, SL cows had a reduced Delta(9)-desaturase system and tended to produce milk with lower monounsaturated fatty acid content. Selection for milk yield did not affect milk fatty acid origin but the percentage of de novo fatty acids increased and preformed fatty acids decreased as lactation progressed. Milk fat trans-11 18:1 and cis-9,trans-11 conjugated linoleic acid increased with progressing lactation (10.7 vs. 14.1 and 3.1 vs. 5.4 mg/g, or 31 and 76%, respectively) and were correlated strongly among wk 1, 8, and 16 of lactation. Temporal changes in the Delta(9)-desaturase system occurred during lactation but these changes were not correlated with milk fat cis-9,trans-11 conjugated linoleic acid content. Results indicate prolonged genetic selection for milk yield had little effect on milk fatty acid composition, but milk fatty acid profiles varied markedly by week of lactation.

Animals↗
PubMed2006

A structural equation model for describing relationships between somatic cell score and milk yield in first-lactation dairy cows.

Relationships between production and diseases may involve recursive or simultaneous effects between traits. Four structural equation models (SEqM) for somatic cell score and milk yield, with varying specifications for the effects relating the 2 traits, were compared. Data consisted of repeated records of milk yield and somatic cell score of 33,453 first-lactation daughters of 245 Norwegian Red sires that had their first progeny test in 1991 and 1992. All models included random effects of the sire and of the cow and were fitted using the LISREL software. The Bayesian information criterion clearly favored a model with a recursive effect from somatic cell score on milk yield over the 3 other models fitted (absence of recursive effects; an effect from milk yield on somatic cell score; simultaneity of effects between the 2 traits). This provides evidence that the negative association between milk yield and somatic cell score is more likely due to an effect of infection (measured indirectly by the somatic cell score) on production than to a dilution effect. Estimates indicated that a mastitis event would reduce milk yield in the following 15 d by about 900 g/d. The estimated genetic (co)variances did not change sizably when the specification of recursive or simultaneous effects was varied. However, estimates of the phenotypic covariance were altered when a recursive effect from somatic cell score on milk yield was included in the model.

Age Factors↗
PubMed2007

Genetic parameters for yield traits of cows treated or not treated with bovine somatotropin.

The objective of this study was to estimate genetic correlations between yield traits of cows treated with bovine somatotropin (bST) and the same yield traits of untreated cows. Lactation records from registered Holstein cows were divided by parity into 3 data sets: 1, 2, and 3 through 5. Approximately 10% of the records in each data set were from cows treated with bST. The numbers of records of treated and untreated cows in the data sets were 4,337 and 48,765; 3,730 and 37,796; and 3,645 and 33,957. Two-trait animal models (records for cows treated or not treated) were used to estimate genetic parameters for milk production traits and somatic cell score (SCS). Estimates of heritability for milk yield for records of treated and untreated cows for the 3 data sets were 0.13, 0.16, and 0.09, and 0.18, 0.18, and 0.14, respectively, with estimates of repeatability of 0.50 and 0.41 for data set 3. Estimates of heritability for fat yield for records of treated and untreated cows were 0.31, 0.16, and 0.12, and 0.27, 0.21, and 0.16. Estimates of repeatability were 0.50 and 0.43 for data set 3. Heritability estimates for protein yield for records of treated and untreated cows were 0.13, 0.17, and 0.12, and 0.20, 0.23, and 0.16, with estimates of repeatability of 0.52 and 0.47. Estimates of heritability for SCS for treated and untreated cows were 0.08, 0.15, and 0.13, and 0.11, 0.13, and 0.13 with repeatability estimates of 0.52 and 0.45. Estimates of genetic correlations between milk yields with and without bST treatment in lactations 1, 2, and 3 to 5 were all 0.99. Estimates of genetic correlations for fat and protein yields were 0.96 for all data sets. Estimates for SCS were 0.99. Estimates of genetic correlations between records of treated and untreated cows were large enough to conclude that records of treated and untreated cows could be considered to be one trait, with treatment as a fixed effect to account for differences in means.

Animals↗
PubMed1983

Variances, repeatabilities, and age adjustments of yield and fertility in dairy cattle.

Breeding receipts from artificial insemination were matched with records of milk yield from northeastern United States. Nine measures of yield and 10 measures of fertility were investigated. A completely random model with herd-year-season, sire, and interaction of sire by herd-year-season was applied by parity; interaction of sire by herd-year-season was not important except possibly for fertility of virgin heifers. Sires accounted for 6 to 7% of yield variation and herd-year-seasons accounted for about 45%. Measures of fertility had small sire variances, and herd-year-season variance was much smaller than for yield. Effects of age within parity were significant for yield from ordinary least-squares analysis. Age adjustment factors were obtained for measures of yield. Repeatabilities of first- and second-parity yield ranged from .40 to .61 whereas repeatabilities of fertility were .03 to .13. Repeatabilities of virgin heifer and first-parity fertility were .01 to .03, suggesting heifer and cow fertility may not be related.

Age Factors↗
PubMed1983

Yield and fertility relationships in dairy cattle.

Measures of yield and fertility were obtained from breeding receipts of artificial insemination and records of test-day yield. Estimates of heritability were by Henderson Method 3, maximum likelihood, and restricted maximum likelihood. Heritabilities for measures of yield varied, but most were within the range of earlier estimates. Measures of fertility had heritabilities from 0 to .03. Alternative upper bounds were placed on days open, number of services, and service period, and always the measure with the lesser bound had higher heritability for first parity. Measures of yield for early stages of lactation had slight positive phenotypic correlations with fertility whereas those for measures of cumulative yield later in lactation increased in relation to effect of gestation. Genetic correlations of first-parity yield and most measures of fertility were positive and less influenced by stage of lactation than phenotypic correlations. Antagonism moderated for second parity. Most genetic correlations were not significantly different from zero for third parity. Considerable genetic antagonism of yield and fertility may be of limited consequence because estimates of genetic variance of fertility were near zero.

Animals↗
PubMed1985

Effects of days open on annualized milk yields in current and following lactations.

Length of open period affected annualized yield [(total lactation yield/calving interval) 365]. Yield was maximum with more days open for low, as opposed to high, peak production and for primiparous, as opposed to multiparous, cows. Interactions with days open were not found for mean herd production or cow production relative to the herd mean. Number of days open for maximum yield was similar for milk, fat, and economically fat-corrected milk [.67 kg milk + 10 kg fat]. Correction factors were derived by smoothed least square means of days open classes. Additive adjustment factors were more appropriate than multiplicative adjustment factors. Records adjusted for days open were not able to predict the following lactation yield significantly better than unadjusted records. Cumulative yield of current and following annualized lactations, including the contribution of the calf expressed in units of milk production, was greatest at 117 and 98 days open for primiparous and multiparous cows. For cows with high peak production maximum yield was with 12 to 14 fewer days open than for cows with moderate peak. Conception prior to 2 mo postpartum had an adverse effect on cumulative yield.

Animals↗