Mastitis and the shape of the lactation curve in Norwegian dairy cows

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.     

Relative Efficiency of Selection Methods for Profit in Dairy Cows

Selection singly on milk yield and calculated profitability traits, selection indexes, and regression indexes were compared for the relative gains in expected profit to 72 mo of age or life time profit. Indexes consisted of five traits of the first lactation: milk, fat percent, days in milk, number of breedings, and age at first calving. The study was on 1806 Holstein cows sired by 404 bulls in 38 California herds. Genetic gain in total profit was 13 to 14% greater when selection was on estimated profit to 41 mo than on milk yield to 305 days in the first lactation. Selection on traits of estimated profit on three bases, to 305 days in first lactation, to end of first lactation, and to 41 mo of age was 2 to 14% more efficient for genetic gain in total profit than selection on corresponding traits of milk yield or selection indexes. Regression indexes were 3 to 19% more efficient than selection indexes for predicting subsequent cumulative profit. In contrast, selection indexes were 6 to 20% more efficient than regression indexes for genetic gain in total profit. Heritabilities for estimated profit and traits of milk yield in the first lactation ranged from .26 to .49 for cows with two or more calvings. Heritabilities for profit to end of first lactation and to 41 mo of age exceeded comparable milk yield traits by 15 to 27%. The economic value of a 1-mo decrease in age at first calving was equivalent to an increase of 138 kg milk yield to the end of the first lactation for gain in total profit to 72 mo of age. Similarly, the genetic effects, or relative selection value, of a 1-mo decrease in age at first calving is valued at approximately 471 kg milk.     

Multitrait estimation of genetic parameters of lactation curves in Holstein heifers

Weekly milk yields of 1022 Holstein heifers from 61 sires were used to derive coefficients of the lactation curves using modified gamma and inverse polynomial functions. The natural logarithm of a modified gamma function was ln(yn) = ln (a) + b ln (n) + cn + u sin (x) + v cos (x), where a, b, c, u, and v are coefficients to be estimated; n is the day of lactation; and x is the day of year. Estimates of a, b, and c were combined to define persistency [-(b + 1) ln c], week of peak yield (b/c), and peak yield [a(b/c)be-b]. The inverse polynomial function was n/yn = A0 + A1n + A2n2, where A0, A1, and A2 are coefficients to be estimated. Variance and covariance components for the coefficients of the lactation curve were estimated by the multitrait restricted maximum likelihood method using canonical transformation. Heritability estimates were ln (a) .11, b .07, c .04 u .01, v .04, A0 .28, A1 .26, A2 .21, persistency .21, week of peak .18, peak yield .23, and 308-d milk yield .41. Genetic correlations indicated that selection for faster rate of increase to peak production would result in higher 308-d milk production, higher peak yield, and greater persistency.     

Genetic relationships between persistency and reproductive performance in first-lactation Canadian holsteins

The main objective of this study was to estimate genetic relationships between lactation persistency and reproductive performance in first lactation. Relationships with day in milk at peak milk yield and estimated 305-d milk yield were also investigated. The data set contained 33,312 first-lactation Canadian Holsteins with first-parity reproductive, persistency, and productive information. Reproductive performance traits included age at first insemination, nonreturn rate at 56 d after first insemination as a virgin heifer and as a first-lactation cow, calving difficulty at first calving and calving interval between first and second calving. Lactation persistency was defined as the Wilmink b parameter for milk yield and was calculated by fitting lactation curves to test day records using a multiple-trait prediction procedure. An 8-trait genetic analysis was performed using the Variance Component Estimation package (VCE 5) via Gibbs sampling to estimate genetic parameters for all traits. Heritabilities of persistency, day in milk at peak milk yield and estimated 305-d milk yield were 0.18, 0.09 and 0.45, respectively. Heritabilities of reproduction were low and ranged from 0.03 to 0.19. The highest heritability was for age at first insemination. Heifer reproductive traits were lowly genetically correlated, whereas cow reproductive traits were moderately correlated. Heifers younger than average when first inseminated and/or conceived successfully at first insemination tended to have a more persistent first lactation. First lactation was more persistent if heifers had difficulty calving (r(g) = 0.43), or conceived successfully at first insemination in first lactation (r(g) = 0.32) or had a longer interval between first and second calving (r(g) = 0.17). Estimates of genetic correlations of reproductive performance with estimated 305-d milk yield were different in magnitude, but similar in sign to those with persistency (0.02 to 0.51).     

Short communication: A positive relationship between the first ovulation postpartum and the increasing ratio of milk yield in the first part of lactation in dairy cows

The aim of the present study was to examine the relationship between characteristics of the lactation curve, on the basis of daily milk yield, and ovulation within 3 wk postpartum as an indicator of early return to luteal activity in dairy cows. Lactation records from 46 lactating Holstein cows between calving and 305 d postpartum were studied. Milk samples were collected twice weekly between d 7 and 100 for later determination of progesterone concentrations. Occurrence of an early first ovulation was determined by an increase in milk progesterone by 3 wk after calving. Milk yield was recorded daily until 305 d postpartum, and average yield was calculated weekly. The lactation curve was characterized by 8 indices on the basis of the weekly average of milk yield as follows: a) first-week milk yield; b) peak milk yield; c) actual 305-d milk yield; d) peak week; e) difference in milk yield between the first week and peak week; f) difference in milk yield between the peak week and last week (43rd week postpartum); g) ratio of increase in milk yield between wk 1 and the week of peak yield; and h) ratio of decline in milk yield between the week of peak yield and the last week. Indices g and h were calculated as linear. The number of cows having ovulated by 3 wk postpartum was 22 (47.8%). The resumption of ovarian cycles with normal luteal phases occurred earlier in ovular cows than in anovular cows (32.0 d vs. 57.1 d). Although total milk yield did not differ between ovular and anovular cows, the ratio of increase in milk yield from the first week to the peak week (index g) in ovular cows was smaller compared with that of anovular cows (1.71 vs. 2.54). In addition, the ratio of increase in milk yield from the first week to the third week postpartum was greater in anovular cows by 3 wk postpartum (ovular = 1.43 ± 0.23 vs. anovular = 2.32 ± 0.29). In conclusion, the present study demonstrates that a greater increasing ratio of milk yield during early lactation may delay resumption of ovarian cycles after parturition. Therefore, this study is the first to demonstrate statistically that a smaller increasing ratio of milk yield (index g) during early lactation may have a beneficial effect on the first ovulation by 3 wk postpartum.     

Short communication: do Holstein lactations of varied lengths have different characteristics?

The calving intervals of Holstein cows in many countries have been increasing in length over recent years. Many reports of lactation characteristics refer only to a standard 305-d lactation. This paper attempts to describe the characteristics of lactations of different lengths using a large database of nationally recorded data. Three different lactation lengths were studied: 305 d (the traditional annual calving interval), 370 d (the current UK national average), and 440 d (equivalent to an 18-mo calving interval). Test-day milk yield; fat, protein, and lactose composition; and somatic cell counts were analyzed. Characteristics of each of 29,838 lactations were calculated using a biological model of lactation and were analyzed to identify which factors affected them. Maximum secretion potential was the only trait not affected by lactation length. Day of peak yield, peak yield, persistency, and total milk yield all increased with lactation length, whereas relative cell death rate and the rate of milk increase in early lactation both decreased as lactation length increased. For most weeks of lactation, the 3 lactation-length groups differed from each other in most traits, following the order of their lengths; for example, milk yield was always higher for lactations of 440 d and lower for those of 305 d. The post-peak trends in all traits were found to continue in longer lactations. Thus, daily milk production and lactose percentage continued to decrease as lactations became longer, whereas fat percentage, protein percentage, and somatic cell count continued to increase. Pregnancy was found to affect all traits, leading to an accentuation of these trends in late lactation. However, the effect of pregnancy depended on the yield at about the fourth month of pregnancy. Lactations of 305, 370, and 440 d all had different characteristics and not solely due to increasing length.     

Development of an optimal index to improve lactation yield and persistency with the least selection intensity

It is important to have improvement in both lactation milk yield and persistency. Modification of the lactation curve requires severe restrictions on selection criteria designed to simultaneously improve both milk yield and persistency. As a result, manipulating the lactation curve for improved persistency requires higher selection intensity than unrestricted selection based on 305-d estimated breeding value (EBV). Our study showed that for a given restriction imposed on both milk EBV and persistency, it is possible to derive different indexes to achieve this selection constraint with different degrees of selection intensity. Of the class of indexes that meets the same restriction, it is preferable to choose the index that requires the least selection intensity because it is easier to achieve the selection goal with the use of an index that requires a lower selection intensity than a higher selection intensity. An optimal index based on random regression (RR) coefficients was developed to achieve the prespecified stage genetic gains with the lowest selection intensity. A conversion equation was derived to convert the selection index based on RR coefficients to the selection index based on stage EBV with the lowest selection intensity. A numerical example is provided to demonstrate the procedures developed compared with conventional selection based on 305-d milk EBV.     

Investigating the effect of temporal,geographic, and management factors on US Holstein lactation curve parameters

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.     

Bayesian analysis of lactation curves of Holstein-Friesian cattle using a nonlinear model

A Bayesian procedure was developed for fitting Wood's incomplete Gamma function to test-day milk records of Spanish Holstein Friesian cattle. Each parameter of Wood's function was considered as a dependent variable in a submodel that accounted for systematic effects and genetic relationships among animals. Marginal posterior distributions of model parameters were obtained using Gibbs sampling. Variables of economic interest, such as 305-d yield, persistency, peak yield, and days in milk at peak day were predicted as functions of Wood's function curve parameters. Heritability estimates were 0.26, 0.32, and 0.19 for parameters of Wood's function and 0.26, 0.14, 0.26, and 0.05 for 305-d yield, persistency, peak yield, and days in milk at peak yield. These estimates indicate that it is possible to modify the shape of the lactation curve through genetic selection. Genetic correlations between parameters of Wood's curve and the aforementioned functions of these parameters suggest that selection for 305-d milk yield would result in higher and later peak yield, but only a slight improvement in persistency is expected.     

Genetic evaluations for measures of the milk-flow curve in the Italian Brown Swiss population

The objective of this study was to estimate heritabilities and genetic correlations between milk-release parameters, somatic cell score, milk yield, and udder functional traits in the Italian Brown Swiss population. Data were available from 37,511 cows over a span of 12 yr (1997-2008) from 1,592 herds. Milking flows were recorded for each individual once during lactation. Three different analyses were performed to estimate variance components for all the traits of interest. The first analysis included single control data milk yield, somatic cell score, maximum milk flow, average milk flow, time of plateau, decreasing time, and total milking time, whereas the second analysis included milk-release parameters as well as total udder score, udder depth, and 305-d milk yield and somatic cell score as dependent variables. The third analysis included total milking time, 305-d milk yield and somatic cell score, total udder score, udder depth, and ratios of maximum milk flow over total milking time (R1), time of plateau (R2), and decreasing time (R3) to estimate the relationship between the shape of the milk-release curves and important milking traits. Results from the first and second analysis found similar heritabilities for milkability traits ranging from 0.05 to 0.41 with genetic correlations between production traits and flow traits ranging from low to moderate values. Positive genetic correlations were found among production, somatic cell score, and milkability traits. The third analysis showed that R1 had the greatest heritability of the ratio traits (0.37) with large genetic correlations with R2 and R3, a low correlation with 305-d somatic cell score, and no correlation with 305-d milk yield. Estimated responses to selection over 5 generations were also calculated using different indexes, which included either flow or ratio traits. The results of this study show that it is possible to use information collected through portable flowmeters to improve milkability traits. Using a set of variables or traits to describe the overall release of milk can be an advantageous selection strategy to decrease management costs while maintaining milk production.     

Effect of lactation number, year, and season of initiation of lactation on milk yield of cows hormonally induced into lactation and treated with recombinant bovine somatotropin

Records representing data from 1,500 barren Holstein cows over an 8-yr period from a large commercial dairy farm in northern Mexico were analyzed to determine the effects of lactation number and season and year of initiation of lactation on milk production of cows induced hormonally into lactation and treated with recombinant bovine somatotropin (rbST) throughout lactation. Peak and 305-d milk yields were also assessed as predictors of total milk yield in cows induced into lactation. A significant quadratic relationship was found between 305-d milk yield and number of lactation [7,607 ± 145 and 9,548 ± 181 kg for first- and ≥6-lactation cows, respectively; mean ± standard error of the mean (SEM)] with the highest production occurring in the fifth lactation. Total milk yields of cows with ≤2 lactations were approximately 4,500 kg less than milk yields of adult cows (the overall average ± standard milk yield was 13,544 ± 5,491 kg per lactation and the average lactation length was 454 ± 154 d). Moreover, 305-d milk production was depressed in cows induced into lactation in spring (8,804 ± 153 kg; mean ± SEM) and summer (8,724 ± 163 kg) than in fall (9,079 ± 151 kg) and winter (9,085 ± 143 kg). Partial regression coefficients for 305-d milk yield and peak milk yield indicated an increment of 157 kg of milk per lactation per 1-kg increase in peak milk yield (r² = 0.69). Neither peak milk yield (r² = 0.18) nor 305-d milk yield (r² = 0.29) was accurate for predicting total milk yield per lactation. Year, parity, and season effects had significant influence on milk yield of cows induced into lactation and treated with rbST throughout lactation, and peak milk yield can assist in the prediction of 305-d milk yield but not total milk yield. This study also showed that hormonal induction of lactation in barren high-yielding cows is a reliable, practical, and affordable technique in countries where rbST treatment and prolonged steroid administration of dairy cows are legally permitted.     

Genetic parameters derived from using a biological model of lactation on records of commercial dairy cows

The object of this study was to investigate the genetics of lactation curve parameters derived from a biological model of lactation and the relationships among them. This biological model fitted 2 logistic curves to mimic the initial increase in milk secretory cell numbers in early lactation and the progression of apoptosis in late lactation. Records from 82,255 Holstein-Friesian heifers from commercial dairy herds in the United Kingdom, recorded from 1994 to 2003, were analyzed. The heritabilities of 2 lactation curve parameters, maximum secretion potential and relative cell death rate, were 0.27 and 0.08 respectively. Maximum secretion potential was highly genetically correlated with peak yield (0.99), and relative cell death rate was highly correlated with persistency of lactation (0.84). Heritability values for the traits analyzed showed a characteristic pattern. Total milk yield traits, maximum secretion potential, and peak yield had similar and moderate heritabilities (∼0.3). Traits associated with late lactation had lower heritability values (∼0.1), whereas day of peak yield and early lactation traits had little genetic variation. The permanent environmental variance of the various traits ranged from 0.08 to 0.26 of the phenotypic variance. Parameters from the 2 logistic curves were not highly correlated, suggesting that selection programs could be devised to exploit genetic variation in both aspects of lactation independently.     

Genetic evaluation of lactation persistency for five breeds of dairy cattle

Cows with high lactation persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of lactation persistency is calculated as a function of trait-specific standard lactation curves and linear regressions of test-day deviations on days in milk. Because regression coefficients are deviations from a tipping point selected to make yield and lactation persistency phenotypically uncorrelated it should be possible to use 305-d actual yield and lactation persistency to predict yield for lactations with later endpoints. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of lactation persistency of milk (PM), fat (PF), protein (PP), and somatic cell score (PSCS) in breeds other than Holstein, and to demonstrate the calculation of prediction equations for 400-d actual milk yield. Data included lactations from Ayrshire, Brown Swiss, Guernsey (GU), Jersey (JE), and Milking Shorthorn (MS) cows calving since 1997. The number of sires evaluated ranged from 86 (MS) to 3,192 (JE), and mean sire estimated breeding value for PM ranged from 0.001 (Ayrshire) to 0.10 (Brown Swiss); mean estimated breeding value for PSCS ranged from −0.01 (MS) to −0.043 (JE). Heritabilities were generally highest for PM (0.09 to 0.15) and lowest for PSCS (0.03 to 0.06), with PF and PP having intermediate values (0.07 to 0.13). Repeatabilities varied considerably between breeds, ranging from 0.08 (PSCS in GU, JE, and MS) to 0.28 (PM in GU). Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable (negative), indicating that increasing lactation persistency of yield traits is associated with decreases in lactation persistency of SCS, as expected. Genetic correlations among yield and lactation persistency were low to moderate and ranged from −0.55 (PP in GU) to 0.40 (PP in MS). Prediction equations for 400-d milk yield were calculated for each breed by regression of both 305-d yield and 305-d yield and lactation persistency on 400-d yield. Goodness-of-fit was very good for both models, but the addition of lactation persistency to the model significantly improved fit in all cases. Routine genetic evaluations for lactation persistency, as well as the development of prediction equations for several lactation end-points, may provide producers with tools to better manage their herds.     

Early lactation production,health, and welfare characteristics of cows selected for extended lactation

Some cows are able to achieve relatively high milk yields during extended lactations beyond 305 d in milk, and farmers may be able to use this potential by selecting the most suitable cows for an extended lactation. However, the decision to postpone insemination has to rely on information available in early lactation. The main objectives of this study were, therefore, to assess the association between the information available in early lactation and the relative milk production of cows on extended lactation, and to investigate if this information can be used to differentiate time of first insemination between cows. Data came from 4 Danish private herds practicing extended lactation in which some cows are selected to have a delayed time of planned first insemination. Average herd size varied from 93 to 157 cows, and milk yield varied from 7,842 to 12,315 kg of energy-corrected milk (ECM) per cow per year across herds. The analysis was based on 422 completed extended lactations (427 ± 87 d), and each lactation was assigned to 1 of 3 (low, medium, and high) milk performance groups (MPG) within parity group within herd based on a standardized lactation yield. For cows in the high MPG, peak ECM yield, and ECM yield at dry off were significantly greater, the relative reduction in milk yield between 60 and 305 d in milk was significantly smaller, and a smaller proportion had a body condition score (scale: 1–5) at dry off of 3.5 or greater compared with cows in low MPG. Previous lactation days in milk at peak ECM yield and ECM yield at dry off were higher, the relative reduction in milk yield between 60 and 305 d in milk was smaller, and the number of inseminations per conception was higher for multiparous cows in high MPG compared with low. Current lactation ECM yield at second and third milk recording were greater for cows in high MPG compared with low. A principal component analysis indicated that variables related to fertility, diseases, and milk yield explained most of the total variation between primiparous cows, whereas variables related to milk yield, fertility, and days in milk at peak yield were the most dominating for multiparous cows. Our study indicated that milk yields in previous lactation and at second and third milk recording correlate well with milk production potential, and therefore, may be promising indicators when selecting the most suitable cows for extended lactation.     

Associations between feed efficiency and aspects of lactation curves in primiparous Holstein dairy cattle

Genetic selection for improved feed efficiency in dairy cattle has received renewed attention over the last decade to address the needs of a growing global population. As milk yield is a critical component of feed efficiency metrics in dairy animals, our objective was to evaluate the associations between feed efficiency in primiparous Holstein cattle and parameters of a mathematical model describing individual lactation curves. The Dijkstra lactation curve model was fit to individual lactation records from 34 Holstein heifers with previously estimated measures of feed efficiency. We found that the optimal fit of the Dijkstra model was achieved using daily milk yield records up to 21 d in milk to capture the rise to peak milk yield and using monthly dairy herd improvement records for the remainder of lactation to accurately characterize lactation persistency. In the period of lactation before peak milk yield, improved feed efficiency was associated with a faster increase in daily milk yield over a shorter period of time at the expense of increased mobilization of body reserves; this serves to reinforce the concept that dairy cattle are primarily capital breeders versus income breeders. Feed efficiency in the period following peak lactation, as measured by gross feed efficiency, return over feed costs, and net energy efficiency of lactation, was positively associated with higher peak milk yield. The findings in early lactation suggest that estimates of feed efficiency could be improved by evaluating feed efficiency relative to conception, rather than parturition and lactation, to better account for the energy stored and released from body reserves in capital breeding.     

Phenotypic relationships of common health disorders in dairy cows to lactation persistency estimated from daily milk weights

The objective of this study was to investigate the phenotypic relationship between common health disorders in dairy cows and lactation persistency, uncorrelated with 305-d yield. The relationships with peak yield and days in milk (DIM) at peak were also studied. Daily milk weights and treatment incidence records of 991 Holstein lactations from experimental dairy herds at Virginia Tech and Pennsylvania State University were used. Persistency was calculated as a function of daily yield deviations from standard lactation curves, developed separately for first (FL) and later lactations (LL), and deviations of DIM around reference dates: 128 for FL and 125 for LL. Days in milk at peak and peak yield were computed for each lactation by using Wood's function. The disease traits studied were mastitis (MAST) only during the first 100 d (MAST1), only after 100 DIM (MAST2), both before and after 100 DIM (MAST12), and at any stage of lactation (MAST1/2), as well as metritis, displaced abomasums, lameness, and metabolic diseases. Each disease was defined as a binary trait, distinguishing between lactations with at least one incidence (1) and lactations with no incidences (0). The relationships of diseases to persistency, DIM at peak, and peak yield were investigated separately for FL and LL for all disease traits except MAST12, which was investigated across parities. The relationships of persistency to probability of the diseases in the same lactation and in the next lactation were examined using odds ratios from a logistic regression model. Metritis and displaced abomasums in FL and LL were associated with significantly higher persistencies. Metabolic diseases and MAST1 in LL were significantly related to higher persistencies. The relationships of MAST2 in both FL and LL, and MAST12 across parities were significant but negative. Cows affected by MAST tended to have less persistent lactations. Most of the diseases had a significant impact on DIM at peak in LL. In LL, metritis, metabolic diseases, and displaced abomasums tended to significantly delay DIM at peak. Mastitis only after 100 DIM was associated with significantly earlier DIM at peak in LL. Increasing persistency was associated with low MAST2 and MAST1/2 in primiparous cows. None of the diseases studied was significantly related to persistency of the previous lactation.     

Relationships among milk yield,body condition,cow weight,and reproduction in spring-calved Holstein-Friesians

Relationships among milk production, body condition score (BCS), body weight (BW), and reproduction were studied using logistic regression on data from 6433 spring-calving Holstein-Friesian dairy cows in 74 commercial herds. Multivariate models were adjusted for herd, breeding value for milk yield, proportion of Holstein-Friesian genes, lactation number, calving period, and degree of calving assistance. Significant associations between reproductive measures and components of energy balance were identified. Higher 200-d milk protein content and higher protein-to-fat ratio at start of breeding were associated with increased likelihood of submission for breeding in the first 21 d of the breeding season (SR21). High 100-d cumulative milk yield as a proportion of estimated 305-d milk yield (low persistency) was associated with a lower likelihood of pregnancy to first service (PREG1), whereas cows reaching peak milk yields earlier tended to have higher PREG1. Cows that reached nadir milk protein content relatively late in lactation had lower PREG1. Milk yield at first service and 305-d milk protein content were positively associated with the likelihood of pregnancy after 42 d of breeding (PR42). Higher 305-d milk lactose content was associated with increased PREG1 and PR42. Mean BCS at 60 to 100 d of lactation was positively associated with both SR21 and PR42, whereas nadir BCS was positively associated with PREG1. Cows with precalving BCS > 3.0 that also lost > 0.5 BCS unit by first service had lower PR42. More BW gain for 90 d after start of breeding was associated with higher SR21 and PREG1; more BW gain for 90 d after first service was associated with higher PR42. Milk protein and lactose content, BCS, and BW changes are important tools to identify cows at risk of poor reproduction.     

Relationships between milk yield and somatic cell score in Canadian Holsteins from simultaneous and recursive random regression models

Multiple-trait random regression animal models with simultaneous and recursive links between phenotypes for milk yield and somatic cell score (SCS) on the same test day were fitted to Canadian Holstein data. All models included fixed herd test-day effects and fixed regressions within region-age at calving-season of calving classes, and animal additive genetic and permanent environmental regressions with random coefficients. Regressions were Legendre polynomials of order 4 on a scale from 5 to 305 d in milk (DIM). Bayesian methods via Gibbs sampling were used for the estimation of model parameters. Heterogeneity of structural coefficients was modeled across (the first 3 lactations) and within (4 DIM intervals) lactation. Model comparisons in terms of Bayes factors indicated the superiority of simultaneous models over the standard multiple-trait model and recursive parameterizations. A moderate heterogeneous (both across- and within-lactation) negative effect of SCS on milk yield (from −0.36 for 116 to 265 DIM in lactation 1 to −0.81 for 5 to 45 DIM in lactation 3) and a smaller positive reciprocal effect of SCS on milk yield (from 0.007 for 5 to 45 DIM in lactation 2 to 0.023 for 46 to 115 DIM in lactation 3) were estimated in the most plausible specification. No noticeable differences among models were detected for genetic and environmental variances and genetic parameters for the first 2 regression coefficients. The curves of genetic and permanent environmental variances, heritabilities, and genetic and phenotypic correlations between milk yield and SCS on a daily basis were different for different models. Rankings of bulls and cows for 305-d milk yield, average daily SCS, and milk lactation persistency remained the same among models. No apparent benefits are expected from fitting causal phenotypic relationships between milk yield and SCS on the same test day in the random regression test-day model for genetic evaluation purposes.