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.     

Genetic markers for lactation persistency in primiparous Australian dairy cows

Good performance in extended lactations of dairy cattle may have a beneficial effect on food costs, health, and fertility. Because data for extended lactation performance is scarce, lactation persistency has been suggested as a suitable selection criterion. Persistency phenotypes were calculated in several ways: P1 was yield relative to an approximate peak, P2 was the slope after peak production, and P3 was a measure derived to be phenotypically uncorrelated to yield and calculated as a function of linear regressions on test-day deviations of days in milk. Phenotypes P1, P2, and P3 were calculated for sires as solutions estimated from a random regression model fitted to milk yield. Because total milk yield, calculated as the sum of daily sire solutions, was correlated to P1 and P2 (r = 0.30 and 0.35 for P1 and P2, respectively), P1 and P2 were also adjusted for milk yield (P1adj and P2adj, respectively). To find genomic regions associated with the persistency phenotypes, we used a discovery population of 743 Holstein bulls proven before 2005 and 2 validation data sets of 357 Holstein bulls proven after 2005 and 294 Jersey sires. Two strategies were used to search for genomic regions associated with persistency: 1) persistency solutions were regressed on each single nucleotide polymorphism (SNP) in turn and 2) a genomic selection method (BayesA) was used where all SNP were fitted simultaneously. False discovery rates in the validation data were high (>66% in Holsteins and >77% in Jerseys). However, there were 2 genomic regions on chromosome 6 that validated in both breeds, including a cluster of 6 SNP at around 13.5 to 23.7 Mbp and another cluster of 5 SNP (70.4 to 75.6 Mbp). A third cluster validated in both breeds on chromosome 26 (0.33 to 1.46 Mbp). Validating SNP effects across 2 breeds is unlikely to happen by chance even when false discovery rates within each breed are high. However, marker-assisted selection on these selected SNP may not be the best way to improve this trait because the average variation explained by validated SNP was only 1 to 2%. Genomic selection could be a better alternative. Correlations between genomic breeding values predicted using all SNP simultaneously and estimated breeding values based on progeny test were twice as high as the equivalent correlations between estimated breeding values and parent average. Persistency is a good candidate for genomic selection because the trait is expressed late in lactation.     

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).     

Genetic analysis of persistency in the israeli holstein population by the multitrait animal model

Persistency was defined as the predicted milk production 180 d after peak divided by peak production (in %). Heritability of persistency in a multitrait analysis including parities 1 through 5 increased from 0.16 to 0.27 from first through third parity, and then declined through fifth parity. Genetic correlations for persistency between consecutive parities were all > 0.8. First-parity genetic correlations of the traits included in the Israeli selection index with persistency were all < 0.1, except for fertility and herdlife, which were 0.20 and 0.25; whereas second-parity genetic correlations of persistency with the 3 milk production traits were all > 0.34, and the genetic correlation with fertility was only 0.10. The genetic correlation between second-parity persistency and herdlife was 0.58. Persistency in the Israeli Holstein population was analyzed by the multitrait animal model. The genetic trend since 1985 for the multiparity index was 0.22% persistency/yr, even though there was no direct selection on persistency.     

Modifying the lactation curve to improve lactation milk and persistency

Daily, stage and lactation estimated breeding values (EBV) and the shape of the lactation curve for each cow are controlled by a unique set of random (genetic) regression coefficients under a test day model, thus providing a basis for genetic improvement of these characteristics. Three selection procedures were developed for simultaneous improvement of total lactation milk and persistency: 1) index selection based on daily EBV, 2) index selection based on stage EBV, and 3) index selection based on random regression (RR) coefficients. A numerical example was given to demonstrate the computation of indexes based on stage EBV and based on RR coefficients. A conversion equation was derived to convert between genetic changes in EBV and RR coefficients. Index selection based on daily EBV would require the finding of 305 weighting factors for a lactation period of 305 d, making it impractical to determine the weighting factors on a daily basis. Alternatively, a lactation period was partitioned into a few stages to facilitate the construction of index selection based on stage EBV and index selection based on RR coefficients. These selection procedures make use of the annual genetic gains routinely computed in national genetic evaluations to restrict the genetic gains between different lactation stages to achieve the desired curve. When there is no prior knowledge of annual genetic gains, the proportional restriction of genetic gains between stages may be used. In summary, this study provides a simple means of modifying the lactation curve by manipulating genetic changes in different lactation stages at a pre-specified rate.     

Short communication: Genetic association of variations in the osteopontin gene (SPP1) with lactation persistency in dairy cattle

Improving lactation persistency (LP) in dairy cattle has a beneficial effect on animal health and fertility and herd productivity. A complex trait, LP not only reflects the cow's ability to maintain milk secretion activity after the lactation peak but is also a function of the postcalving development of the mammary gland and, later on, of tissue remodeling as lactation declines. This decline is a consequence of an imbalance between cell proliferation and cell removal. In a previous study, single nucleotide polymorphisms were identified in the osteopontin (OPN) gene, SPP1. Osteopontin is a multifaceted protein that plays an important role in immune regulation and tissue remodeling. Because OPN is involved in involution, it might also have an effect on LP. The objective of the present study was to evaluate whether LP could be influenced by genetic variations in the SPP1 gene. This association with LP was analyzed in the population of 578 bulls characterized in a previous study. The population mean of estimated breeding value (EBV) for LP was 100.95 ± 5.06 units. Allele and genotype association analyses were performed by comparing the frequencies of the different genotypes and alleles with EBV for LP for the respective lactation using logistic regression. The EBV for LP at the first lactation (LP1), second lactation (LP2), and third lactation (LP3) and for overall lactation (OLP) are reported for the genotypes SPP1c.-1301G>A, SPP1c.-1251C>T, SPP1c.-430G>A, and SPP1c.*40A>C. The first single nucleotide polymorphism, SPP1c.-1301G>A, affected LP1, LP2, LP3, and OLP. Analysis of the estimated average allele substitution effects also confirmed that G is a favorable allele for LP, given the gain observed over LP1, LP2, LP3, and OLP. Differences in EBV for LP were observed between animals with different haplotypes at LP1, LP2, LP3, and OLP. Contrast analysis for OLP revealed that mean EBV is greater for block H1 (101.34 ± 0.30) than for animals that do not have H1 (98.20 ± 0.77). The gain with block H1 (GCGA) suggests the presence of the favorable allele G (first position in the block: SPP1c.-1301G). The pleiotropic roles of OPN position it at the crossroads of immune regulation, tissue remodeling, and involution. From a genetic perspective, data from the present study suggest OPN as a candidate gene associated with LP for dairy cows.     

Maximization of lactation milk production without decreasing persistency

This study treats each daily estimated breeding value (EBV) of the lactation as a separate trait to modify the lactation curve on a daily basis. Six selection strategies for improving lactation milk without decreasing persistency were compared: 1) index I_R1, subject to the restriction of equal genetic gains at days in milk (DIM) 60 and 280, 2) I_R2, subject to the restriction of zero gain at DIM 60, 3) desired gains index I_d, designed to increase lactation milk without altering the lactation curve, 4) index I_u, comprising lactation EBV and persistency without standardization, 5) index I_w, consisting of lactation EBV (EBV_L) and persistency with standardization, and 6) conventional selection on EBV_L and used as a basis for comparison. Of the 6 selection strategies compared, I_R2 yielded the greatest persistency, but achieved the smallest response in EBV_L, suggesting that it is impractical to increase persistency by inhibiting change in the peak yield. Index I_u showed the same response in lactation milk as conventional selection on EBV_L, but resulted in the same decreased persistency. Although both I_R1 and I_d achieved constant persistency, the former produced a greater lactation response (669 kg EBV) than the latter (560 kg EBV). Thus, I_R1 is a viable strategy for improving EBV_L while holding persistency constant. None of the 6 selection strategies excelled in both lactation milk and persistency. Index I_w appears to be a reasonable choice for improving both traits, although responses would depend on the relative economic importance of the 2 traits. Differential responses between I_u and I_w emphasize the need to weight the EBV of different traits by the inverse of their standard deviations in index construction when the EBV vary widely in variance. The general formula developed here provides a useful genetic means of modifying the lactation curve by restricting differential genetic gains among different days of the lactation.     

Short communication: best prediction of 305-day lactation yields with regional and seasonal effects

In the United States, lactation yields are calculated using best prediction (BP), a method in which test-day (TD) data are compared with breed- and parity-specific herd lactation curves that do not account for differences among regions of the country or seasons of calving. Complete data from 538,090 lactations of 348,123 Holstein cows with lactation lengths between 250 and 500 d, records made in a single herd, at least 5 reported TD, and twice-daily milking were extracted from the national dairy database and used to construct regional and seasonal lactation curves. Herds were assigned to 1 of 7 regions of the country, individual lactations were assigned to 3-mo seasons of calving, and lactation curves for milk, fat, and protein yields were estimated by parity group for regions, seasons, and seasons within regions. Multiplicative pre-adjustment factors (MF) also were computed. The resulting lactation curves and MF were tested on a validation data set of 891,806 lactations from 400,000 Holstein cows sampled at random from the national dairy database. Mature-equivalent milk, fat, and protein yields were calculated using the standard and adjusted curves and MF, and differences between 305-d mature-equivalent yields were tested for significance. Yields calculated using 50-d intervals from 50 to 250 d in milk (DIM) and using all TD to 500 DIM allowed comparisons of predictions for records in progress (RIP). Differences in mature-equivalent milk ranged from 0 to 51 kg and were slightly larger for first-parity than for later parity cows. Milk and components yields did not differ significantly in any case. Correlations of yields for 50-d intervals with those using all TD were similar across analyses. Yields for RIP were slightly more accurate when adjusted for regional and seasonal differences.     

Efficiency of different selection criteria for persistency and lactation milk yield

A conversion formula was developed to convert the genetic covariance matrices of daily yields and of random regression coefficients between 305-d and 335-d production periods under a random regression test day model. Five selection criteria were compared in terms of genetic improvement in persistency and lactation milk: 1) lactation estimated breeding value (EBVL), 2) P6 = 279Sigma(i=65) (D280 - Di), 3) ratio of daily estimated breeding value (EBV)(r280/65 = D280/D65), 4) ratio of partial lactation EBV (P280/65 = D66 approximately 28/D5 approximately 65), and 5) differential daily EBV (d65-280 = D65 - D280), where Di refers to EBV at days in milk (DIM) i. Fundamental differences among these 5 selection criteria were interpreted conceptually with a graph. Persistency, defined as k = (delta G65 - delta G280)/215, was the average daily rate of decline in selection gain from DIM 65 to 280, which is free from the effect of lactation milk on the rate of decline. Parameter k provides an objective measure of persistency, which increases when k < 0 and decreases when k > 0. Of the 5 selection criteria compared, d65-280 and P6 achieved greater persistency at the expense of genetic gain in lactation milk, whereas selection based on EBVL achieved the highest response in lactation milk, but was coupled with greatest decline in persistency. Selection on P280/65 or r280/65 improved both lactation milk and persistency and, thus, is recommended for simultaneous improvement of these 2 economically important traits. Further study of the relative economic values of persistency and lactation milk in order to combine both traits into an index for selection decision is warranted.     

Genetic improvement of total milk yield and total lactation persistency of the first three lactations in dairy cattle

The objective of this study was to compare 6 selection criteria in terms of 3-parity total milk yield and 9 selection criteria in terms of total net merit (H) comprising 3-parity total milk yield and total lactation persistency. The 6 selection criteria compared were as follows: first-parity milk estimated breeding value (EBV; M1), first 2-parity milk EBV (M2), first 3-parity milk EBV (M3), first-parity eigen index (EI₁), first 2-parity eigen index (EI₂), and first 3-parity eigen index (EI₃). The 9 selection criteria compared in terms of H were M1, M2, M3, EI₁, EI₂, EI₃, and first-parity, first 2-parity, and first 3-parity selection indices (I₁, I₂, and I₃, respectively). In terms of total milk yield, selection on M3 or EI₃ achieved the greatest genetic response, whereas selection on EI₁ produced the largest genetic progress per day. In terms of total net merit, selection on I₃ brought the largest response, whereas selection EI₁ yielded the greatest genetic progress per day. A multiple-lactation random regression test-day model simultaneously yields the EBV of the 3 lactations for all animals included in the analysis even though the younger animals do not have the opportunity to complete the first 3 lactations. It is important to use the first 3 lactation EBV for selection decision rather than only the first lactation EBV in spite of the fact that the first-parity selection criteria achieved a faster genetic progress per day than the 3-parity selection criteria. Under a multiple-lactation random regression animal model analysis, the use of the first 3 lactation EBV for selection decision does not prolong the generation interval as compared with the use of only the first lactation EBV. Thus, it is justified to compare genetic response on a lifetime basis rather than on a per-day basis. The results suggest the use of M3 or EI₃ for genetic improvement of total milk yield and the use of I₃ for genetic improvement of total net merit H. Although this study deals with selection for 3-parity milk production, the same principle applies to selection for lifetime milk production.     

Yields and persistency of lactation in Friesian and Jersey cows milked once daily

Effects of milking cows once daily throughout lactation at high stocking rates (17% more cows/ha than for those milked twice daily) were studied in 2 Friesian and 2 Jersey herds during 3 lactations. Cows were allocated to 2 herds within breed and were milked either once or twice daily, based on age, genetic merit, and previous performance. Cows remained in their original herd and were milked at the same milking frequency during all lactations. Culled cows (20% per year) were replaced by 2-yr-old heifers. Yields of milk, lactose, protein, and fat were measured every 2 wk by commercial herd test. Cubic splines (5 knots) were used to approximate the lactation curve for each cow-yr to provide estimates of performance for each day of lactation. Yields of milk were greater for Friesian and Jersey cows milked twice daily (4,751 ± 89 and 3,067 ± 81 kg/cow) than for cows milked once daily (3,329 ± 80 and 2,431 ± 75 kg/cow), respectively. Cows milked once daily had lesser total and peak yields of milk, lactose, protein, and fat than cows milked twice daily. Friesians had greater total and peak yields than Jerseys. Peak production for all milk components occurred earlier in lactation for cows milked once daily than twice daily (d 24 to 39 vs. 32 to 44). Three measures of persistency of lactation were considered for each cow with 2 measures (Pers1 and Pers2) indicating that cows milked twice daily had better persistency than those milked once daily. Ranking of herds in persistency tended to match the ranking based on total yields. Measures of persistency (Pers1 and Pers2) were positively related to total yield in the Jerseys milked once daily and negatively related to peak yield in the Friesians. The third persistency measure (Pers3) ranked once-daily Jerseys first and twice-daily Friesians last, and was negatively correlated with total yield in the Friesian herds and negatively correlated with peak yield in all herds. For most performance measures, cows milked twice daily had better total yields and persistency than cows milked once daily.     

Economic weights for genetic improvement of lactation persistency and milk yield

This study aimed to establish a criterion for measuring the relative weight of lactation persistency (the ratio of yield at 280 d in milk to peak yield) in restricted selection index for the improvement of net merit comprising 3-parity total yield and total lactation persistency. The restricted selection index was compared with selection based on first-lactation total milk yield (I₁), the first-two-lactation total yield (I₂), and first-three-lactation total yield (I₃). Results show that genetic response in net merit due to selection on restricted selection index could be greater than, equal to, or less than that due to the unrestricted index depending upon the relative weight of lactation persistency and the restriction level imposed. When the relative weight of total lactation persistency is equal to the criterion, the restricted selection index is equal to the selection method compared (I₁, I₂, or I₃). The restricted selection index yielded a greater response when the relative weight of total lactation persistency was above the criterion, but a lower response when it was below the criterion. The criterion varied depending upon the restriction level (c) imposed and the selection criteria compared. A curvilinear relationship (concave curve) exists between the criterion and the restricted level. The criterion increases as the restriction level deviates in either direction from 1.5. Without prior information of the economic weight of lactation persistency, the imposition of the restriction level of 1.5 on lactation persistency would maximize change in net merit. The procedure presented allows for simultaneous modification of multi-parity lactation curves.     

Use of early lactation days open records for genetic evaluation of cow fertility

National genetic evaluations for cow fertility were introduced by the USDA in February, 2003. These evaluations, reported as daughter pregnancy rate, are based on days open. One requirement of the evaluation system is that lactations be at least 250 d in milk (DIM) to be included for analysis. The objective of this research was to develop a predictor of days open, usable in genetic evaluation, to allow for earlier predicted transmitting abilities (PTA), especially for young bulls. The final prediction equation included an overall intercept, the effects of lactation and calving ease score, the linear and quadratic effects of age at calving, and a regression on days open based on last breeding. Data used for estimation were breeding records from 4 dairy records processing centers for the years 1995 through 1998. Genetic correlations were > or =0.91 by d 130, and phenotypic means of predicted days open were in agreement with means for final days open, indicating that the predictions were phenotypically unbiased. Comparison of mean PTA based on actual and predicted days open indicated no bias in PTA, and correlations between PTA were > or =0.92 by d 130. The earlier use of data increased reliability by about 5% for sires between the ages of 4 and 5 yr. The USDA began using predicted days open for records that are at least 130 DIM in national evaluations starting November, 2003.     

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.     

Genome-wide association analysis and pathways enrichment for lactation persistency in Canadian Holstein cattle

Lactation persistency (LP), defined as the rate of declining milk yield after milk peak, is an economically important trait for dairy cattle. Improving LP is considered a good alternative method for increasing overall milk production because it does not cause the negative energy balance and other health issues that cows experience during peak milk production. However, little is known about the biology of LP. A genome-wide association study (GWAS) and pathway enrichment were used to explore the genetic mechanisms underlying LP. The GWAS was performed using a univariate regression mixed linear model on LP data of 3,796 cows and 44,100 single nucleotide polymorphisms (SNP). Eight and 47 SNP were significantly and suggestively associated with LP, respectively. The 2 most important quantitative trait loci regions for LP were (1) a region from 106 to 108 Mb on Bos taurus autosome (BTA) 5, where the most significant SNP (ARS-BFGL-NGS-2399) was located and also formed a linkage disequilibrium block with 3 other SNP; and (2) a region from 29.3 to 31.3 Mb on BTA 20, which contained 3 significant SNP. Based on physical positions, MAN1C1, MAP3K5, HCN1, TSPAN9, MRPS30, TEX14, and CCL28 are potential candidate genes for LP because the significant SNP were located in their intronic regions. Enrichment analyses of a list of 536 genes in 0.5-Mb flanking regions of significant and suggestive SNP indicates that synthesis of milk components, regulation of cell apoptosis processes and insulin, and prolactin signaling pathways are important for LP. Upstream regulators relevant for LP positional candidate genes were prolactin (PRL), peroxisome proliferator-activated receptor gamma (PPARG), and Erb-B2 receptor tyrosine kinase 2 (ERBB2). Several networks related to cellular development, proliferation and death were significantly enriched for LP positional candidate genes. In conclusion, this study detected several SNP, genes, and interesting regions for fine mapping and validation of candidate genes and SNP for potential use in selection for improved LP. This study also provided further insights on the biology of LP which will help to prioritize selected candidate genes for functional validation and application.     

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.     

Use of multivariate analysis to extract latent variables related to level of production and lactation persistency in dairy cattle

Multivariate factor analysis and principal component analysis were used to decompose the correlation matrix of test-day milk yields of 48,374 lactations of 21,721 Italian Simmental cows. Two common latent factors related to level of production in early lactation and lactation persistency, and 2 principal components associated with the whole lactation yield and persistency were obtained. Factor and principal component scores were treated as new quantitative phenotypes related to prominent features of lactation curve shape. Genetic parameters were estimated by univariate and bivariate animal models. Estimates of heritability were moderately low for both latent factors (0.13 for persistency and yield early in lactation). Heritabilities of the principal component related to total lactation yield and 305-d yield were similar (0.19 and 0.20, respectively). Finally, heritability was quite low for the principal component related to lactation persistency (0.07). Repeatabilities between lactations were about 0.27 for both latent factors, around 0.4 for the first principal component and 305-d yield, and 0.11 for the second principal component. Moderate genetic correlation among common factors (0.26) and their high genetic correlation with total lactation yield (>0.60) suggest that selection can be used to change the shape of lactation curve as well as improve yield. Scores of the second principal component can be used to genetically improve persistency while maintaining constant total lactation yield.     

Genetic parameters for health traits and their relationship to different persistency traits in German Holstein dairy cattle

Data from 3,200 Holstein cows from 3 commercial dairy farms in Germany were used to estimate heritabilities and breeding values for liability to udder diseases (UD), fertility diseases (FD), metabolic diseases (MD), and claw and leg diseases (CLD) using single-trait threshold sire models. A total of 92,722 medical treatments recorded from 1998 to 2003 were included in the analysis. Approximate genetic correlations between persistency of milk yield, fat yield, protein yield, and persistency of milk energy yield and liability to the health traits were calculated based on correlations between EBV. Posterior means of heritability of liability ranged from 0.05 to 0.08 for UD, from 0.04 to 0.07 for FD, from 0.08 to 0.12 for MD, and from 0.04 to 0.07 for CLD. Approximate genetic correlations of the disease traits with the persistency traits were favorable, except for MD in all lactations, which were unfavorable, and UD, which were around zero. Highest correlations in the range of 0.13 to 0.46 were found between the different persistency traits and CLD.     

Genetic parameters for milk production and persistency for Danish Holsteins estimated in random regression models using REML

(Co)variance components for milk, fat, and protein yield of 8075 first-parity Danish Holsteins (DH) were estimated in random regression models by REML. For all analyses, the fixed part of the model was held constant, whereas four different functions were applied to model the additive genetic effect and the permanent environment effect. Homogeneous residual variance was assumed throughout lactation. Univariate models were compared using a minimum of -2 ln(restricted likelihood) as the criterion for best fit. Heritabilities as a function of time were calculated from the estimated curve parameters from univariate analyses. Independent of the function applied and the trait in question, heritabilities were lowest in the beginning of the lactation. Heritabilities for persistency of fat yield were slightly higher than heritabilities for persistency of milk and protein yield. Genetic correlations between persistency and 305-d production were higher for protein and milk yield than for fat yield. Bivariate analyses between the production traits were carried out in sire models using the models with the best 3-parameter curve fit in the univariate analyses. Correlations between traits were calculated from covariance components for curve parameters estimated in bivariate analyses. Genetic correlations between milk and protein yield were higher than between milk and fat yield.     

Effects of extended voluntary waiting period from calving until first insemination on body condition,milk yield,and lactation persistency

A 1-yr calving interval (CInt) is usually associated with maximized milk output, due to the calving-related peak in milk yield. Extending CInt could benefit cow health and production efficiency due to fewer transition periods per unit of time. Extending CInt can affect lactation performance by fewer days dry per year, delayed pregnancy effect on milk yield, and greater milk solid yield in late lactation. This study first investigated the effects of 3 different voluntary waiting periods (VWP) from calving until first insemination on body weight, body condition, milk yield, and lactation persistency. Second, individual cow characteristics in early lactation were identified that contributed to milk yield and persistency of cows with different VWP. Holstein-Friesian dairy cows (n = 154) within 1 herd were blocked for parity, calving season, and expected milk yield. Cows were randomly assigned within the blocks to 1 of 3 VWP (50, 125, or 200 d: VWP50, VWP125, or VWP200, respectively) and monitored through 1 complete lactation and the first 6 wk of the subsequent lactation, or until culling. Minimum and mean CInt (384 vs. 452 vs. 501 d for VWP50 vs. VWP125 vs. VWP200) increased with increasing VWP, but maximum CInt was equal for the 3 VWP. Fat- and protein-corrected milk yield (FPCM) was analyzed weekly. Milk yield and FPCM were also expressed per day of CInt, to compare yields of cows with different VWP. Persistency was determined between d 100 and d 200 of the lactation, as well as between d 100 and dry-off. Values are presented as least squares means ± standard error of the mean. During the first 44 wk of lactation, VWP did not affect FPCM yield in both primiparous and multiparous cows. The VWP did not affect milk yield per day of CInt. The VWP did not affect FPCM yield per day of calving interval for primiparous cows. Multiparous cows in VWP125 had FPCM yield per day of CInt similar to that of VWP50. Multiparous cows in VWP200 had lower FPCM yield per day of CInt compared with VWP50 (27.2 vs. 30.4 kg/d). During the last 6 wk before dry-off, cows in VWP125 had lower yield compared with cows in VWP50, which could benefit their udder health in the dry period and after calving. Persistency was better for cows in VWP200 compared with cows in VWP50 (?0.05 vs. ?0.07 kg/d). Body weight was not different among VWP groups. Multiparous cows in VWP200 had a higher body condition score in the last 3 mo before dry-off and the first 6 wk of the next lactation, compared with multiparous cows in VWP125 and VWP50. The VWP could be extended from 50 d to 125 d without an effect on daily yield per day of calving interval. Extending VWP until 200 d for primiparous cows did not affect their daily milk yield, but multiparous cows with a 200-d VWP had a reduced milk yield per day of calving interval and an increased body condition in late lactation and the subsequent lactation, compared with multiparous cows with a 50-d VWP.