Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8kg, 20.6kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.     

Influence of negative energy balance on cyclicity and fertility in the high producing dairy cow

The peripartum period is of critical importance to subsequent health and fertility. Most cows enter a state of negative energy balance (NEB) associated with many metabolic changes which have carry over effects on the resumption and normality of estrous cyclicity and the success of subsequent inseminations. A dataset on 500 lactations explored the relationships between metabolic traits measured before and after calving with fertility. Stepwise multiple regression analysis showed that longer calving to conception intervals were associated with altered profiles of IGF-I, urea and body condition score. These relationships between metabolic profiles and fertility differed between first lactation cows (which are still growing but produce less milk) and mature animals. Early postpartum the liver undergoes extensive biochemical and morphological modifications to adapt to NEB, the uterus is extensively remodeled and must clear bacterial infections, and the ovary must resume ovulatory cycles. RNA isolated from liver and uterine tissues harvested 2 weeks postpartum from cows in mild (MNEB) and severe (SNEB) energy balance was used to screen the Affymetrix 23K bovine microarray. In liver, SNEB resulted in differential expression of key genes involved in lipid catabolism, gluconeogenesis, and the synthesis and stability of IGF-I. This was accompanied by reduced systemic concentrations of IGF-I which is likely to impact on ovarian function and early embryo development. Within endometrium, cows in SNEB showed histological evidence for higher levels of inflammation and the microarray analysis identified groups of differentially expressed genes involved in tissue remodeling and immune response. This may delay uterine repair after calving, likely contributing to the observed reduction in fertility.     

Genetic parameters for endocrine and traditional fertility traits,hyperketonemia and milk yield in dairy cattle

High-yielding cows may suffer from negative energy balance during early lactation, which can lead to ketosis and delayed ability of returning to cyclicity after calving. Fast recovery after calving is essential when breeding for improved fertility. Traditionally used fertility traits, such as the interval from calving to first insemination (CFI), have low heritabilities and are highly influenced by management decisions. Herd Navigator™ management program samples and analyses milk progesterone and β-hydroxybutyrate (BHB) automatically during milking. In this study, the genetic parameters of endocrine fertility traits (measured from milk progesterone) and hyperketonemia (measured from milk BHB) in early lactation were evaluated and compared with traditional fertility traits (CFI, interval from calving to the last insemination and interval from first to last insemination) and the milk yield in red dairy cattle herds in Finland. Data included observations from 14 farms from 2014 to 2017. Data were analyzed with linear animal models using DMU software and analyses were done for first parity cows. Heritability estimates for traditional fertility traits were low and varied between 0.03 and 0.07. Estimated heritabilities for endocrine fertility traits (interval from calving to the first heat (CFH) and commencement of luteal activity (C-LA)) were higher than for traditional fertility traits (0.19 to 0.33). Five slightly different hyperketonemia traits divided into two or three classes were studied. Linear model heritability estimates for hyperketonemia traits were low, however, when the threshold model was used for binary traits the estimates became slightly higher (0.07 to 0.15). Genetic correlation between CFH and C-LA for first parity cows was high (0.97) as expected since traits are quite similar. Moderate genetic correlations (0.47 to 0.52) were found between the endocrine fertility traits and early lactation milk yield. Results suggest that the data on endocrine fertility traits measured by automatic systems is a promising tool for improving fertility, specifically when more data is available. For hyperketonemia traits, dividing values into three classes instead of two seemed to work better. Based on the current study and previous studies, where higher heritabilities have been found for milk BHB traits than for clinical ketosis, milk BHB traits are a promising indicator trait for resistance to ketosis and should be studied more. It is important that this kind of data from automatic devices is made available to recording and breeding organizations in the future.     

Genetic and phenotypic correlations among feed efficiency,production and selected conformation traits in dairy cows

The difficulties and costs of measuring individual feed intake in dairy cattle are the primary factors limiting the genetic study of feed intake and utilisation, and hence the potential of their subsequent industry-wide applications. However, indirect selection based on heritable, easily measurable, and genetically correlated traits, such as conformation traits, may be an alternative approach to improve feed efficiency. The aim of this study was to estimate genetic and phenotypic correlations among feed intake, production, and feed efficiency traits (particularly residual feed intake; RFI) with routinely recorded conformation traits. A total of 496 repeated records from 260 Holstein dairy cows in different lactations (260, 159 and 77 from first, second and third lactation, respectively) were considered in this study. Individual daily feed intake and monthly BW and body condition scores of these animals were recorded from 5 to 305 days in milk within each lactation from June 2007 to July 2013. Milk yield and composition data of all animals within each lactation were retrieved, and the first lactation conformation traits for primiparous animals were extracted from databases. Individual RFI over 301 days was estimated using linear regression of total 301 days actual energy intake on a total of 301 days estimated traits of metabolic BW, milk production energy requirement, and empty BW change. Pair-wise bivariate animal models were used to estimate genetic and phenotypic parameters among the studied traits. Estimated heritabilities of total intake and production traits ranged from 0.27±0.07 for lactation actual energy intake to 0.45±0.08 for average body condition score over 301 days of the lactation period. RFI showed a moderate heritability estimate (0.20±0.03) and non-significant phenotypic and genetic correlations with lactation 3.5 % fat-corrected milk and average BW over lactation. Among the conformation traits, dairy strength, stature, rear attachment width, chest width and pin width had significant (P<0.05) moderate to strong genetic correlations with RFI. Combinations of these conformation traits could be used as RFI indicators in the dairy genetic improvement programmes to increase the accuracy of the genetic evaluation of feed intake and utilisation included in the index.     

Genetic relationship of discrete-time survival with fertility and production in dairy cattle using bivariate models

Bivariate analyses of functional longevity in dairy cattle measured as survival to next lactation (SURV) with milk yield and fertility traits were carried out. A sequential threshold-linear censored model was implemented for the analyses of SURV. Records on 96 642 lactations from 41 170 cows were used to estimate genetic parameters, using animal models, for longevity, 305 d-standardized milk production (MY305), days open (DO) and number of inseminations to conception (INS) in the Spanish Holstein population; 31% and 30% of lactations were censored for DO and INS, respectively. Heritability estimates for SURV and MY305 were 0.11 and 0.27 respectively; while heritability estimates for fertility traits were lower (0.07 for DO and 0.03 for INS). Antagonist genetic correlations were estimated between SURV and fertility (-0.78 and -0.54 for DO and INS, respectively) or production (-0.53 for MY305), suggesting reduced functional longevity with impaired fertility and increased milk production. Longer days open seems to affect survival more than increased INS. Also, high productive cows were more problematic, less functional and more liable to being culled. The results suggest that the sequential threshold model is a method that might be considered at evaluating genetic relationship between discrete-time survival and other traits, due to its flexibility.     

Body condition score of Nellore beef cows: a heritable measure to improve the selection of reproductive and maternal traits

Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.     

Genetic parameters for lameness,mastitis and dagginess in a multi-breed sheep population

The objective of the present study was to quantify the extent of genetic variation in three health-related traits namely dagginess, lameness and mastitis, in an Irish sheep population. Each of the health traits investigated pose substantial welfare implications as well as considerable economic costs to producers. Data were also available on four body-related traits, namely body condition score (BCS), live weight, muscle depth and fat depth. Animals were categorised as lambs (<365 days old) or ewes (⩾365 days old) and were analysed both separately and combined. After edits, 39 315 records from 264 flocks between the years 2009 and 2015 inclusive were analysed. Variance components were estimated using animal linear mixed models. Fixed effects included contemporary group, represented as a three-way interaction between flock, date of inspection and animal type (i.e. lamb, yearling ewe (i.e. females ⩾365 days but <730 days old that have not yet had a recorded lambing) or ewe), animal breed proportion, coefficients of heterosis and recombination, animal gender (lambs only), animal parity (ewes only; lambs were assigned a separate ‘parity’) and the difference in age of the animal from the median of the respective parity/age group. An additive genetic effect and residual effect were both fitted as random terms with maternal genetic and non-genetic components also considered for traits of the lambs. The direct heritability of dagginess was similar across age groups (0.14 to 0.15), whereas the direct heritability of lameness ranged from 0.06 (ewes) to 0.12 (lambs). The direct heritability of mastitis was 0.04. For dagginess, 13% of the phenotypic variation was explained by dam litter, whereas the maternal heritability of dagginess was 0.05. The genetic correlation between ewe and lamb dagginess was 0.38; the correlation between ewe and lamb lameness was close to zero but was associated with a large standard error. Direct genetic correlations were evident between dagginess and BCS in ewes and between lameness and BCS in lambs. The present study has demonstrated that ample genetic variation exists for all three health traits investigated indicating that genetic improvement is indeed possible.     

Genetic correlations between energy status indicator traits and female fertility in primiparous Nordic Red Dairy cattle

Inclusion of feed efficiency traits into the dairy cattle breeding programmes will require considering early lactation energy status to avoid deterioration in health and fertility of dairy cows. In this regard, energy status indicator (ESI) traits, for example, blood metabolites or milk fatty acids (FAs), are of interest. These indicators can be predicted from routine milk samples by mid-IR reflectance spectroscopy (MIR). In this study, we estimated genetic variation in ESI traits and their genetic correlation with female fertility in early lactation. The data consisted of 37 424 primiparous Nordic Red Dairy cows with milk test-day records between 8 and 91 days in milk (DIM). Routine test-day milk samples were analysed by MIR using previously developed calibration equations for blood plasma non-esterified FA (NEFA), milk FAs, milk beta-hydroxybutyrate (BHB) and milk acetone concentrations. Six ESI traits were considered and included: plasma NEFA concentration (mmol/l) either predicted by multiple linear regression including DIM, milk fat to protein ratio (FPR) and FAs C10:0, C14:0, C18:1 cis-9, C14:0 * C18:1 cis-9 (NEFA_FA) or directly from milk MIR spectra (NEFA_MIR), C18:1 cis-9 (g/100 ml milk), FPR, BHB (mmol/l milk) and acetone (mmol/l milk). The interval from calving to first insemination (ICF) was considered as the fertility trait. Data were analysed using linear mixed models. Heritability estimates varied during the first three lactation months from 0.13 to 0.19, 0.10 to 0.17, 0.09 to 0.14, 0.07 to 0.10, 0.13 to 0.17 and 0.13 to 0.18 for NEFA_MIR, NEFA_FA, C18:1 cis-9, FPR, milk BHB and acetone, respectively. Genetic correlations between all ESI traits and ICF were from 0.18 to 0.40 in the first lactation period (8 to 35 DIM), in general somewhat lower (0.03 to 0.43) in the second period (36 to 63 DIM) and decreased clearly (−0.02 to 0.19) in the third period (64 to 91 DIM). Our results indicate that genetic variation in energy status of cows in early lactation can be determined using MIR-predicted indicators. In addition, the markedly lower genetic correlation between ESI traits and fertility in the third lactation month indicated that energy status should be determined from the first test-day milk samples during the first 2 months of lactation.     

Short communication: Differences in genetic merit for visually-assessed body condition score materialises as phenotypic differences in tactile-based body condition score in commercial dairy cows

Body condition score (BCS) is a known risk factor for cow health and well-being. Many different BCS scales and systems for assessment exist;while the scales used for assessing BCS vary, differences in how BCS is assessed (i.e., visual versus visual plus tactile) and the extent of training and experience of the assessor (i.e., professional linear classifiers versus producers) also contributes to the underlying variability. Registered dairy cows globally are routinely assessed for linear type traits which describe biological extremes in the morphological attributes; BCS and a correlated trait angularity are within this suite of traits assessed. These linear-type data are used to generate estimates of genetic merit (predicted transmitting ability), but how these estimates manifest themselves as phenotypic differences when assessed by producers on commercial multiparous cows has never been quantified. To evaluate this, 58 440 phenotypic BCS records from 48 823 lactations in 38 608 cows were used. Associations were undertaken using linear mixed models relating phenotypic BCS to genetic merit after accounting for nuisance factors. Differences in genetic merit for either BCS or angularity (assessed visually by professionals on a 1 to 9 scale just once during lactation in primiparous registered cows) translated to phenotypic difference in BCS (assessed by producers using both tactile and visual assessment on a 1 to 5 scale across lactation in commercial dairy cows). The partial correlation between test phenotypic BCS and genetic merit for either BCS or angularity was 0.13 and  0.10, respectively. Based on the model coefficients estimated in the present study, the mean expected difference in phenotypic BCS on a 1 to 5 scale between the top and bottom 10% on genetic merit for BCS or angularity was 0.28 and 0.31 units, respectively. Results from the present study clearly provide confidence that genetic merit for BCS or angularity based on a single visual assessment in primiparous cows is useful to breed for cows of better body condition, irrespective of stage of lactation or parity.     

Genetic parameters for feed intake,litter weight,body condition and rebreeding success in primiparous Norwegian Landrace sows

The aim of this study was to estimate genetic parameters for feed intake recorded as farmers’ perception of young sows’ appetite for the first 3 weeks of lactation (APP) and feed intake recorded for one day in the 3rd week of lactation (FEED), litter weight (LW) at 3 weeks, sow body condition at weaning (BC) and the following five reproduction traits: weaning-to-service interval of 1 to 7 days (WSI7), weaning-to-service interval of 1 to 50 days (WSI50), delayed service or not (DELAYED), pregnant on first service or not (PREGNANT) and litter size in 2nd parity (NBT2). The analyses included data on 4606 Norwegian Landrace 1st-parity sows and their litters. The Gibbs sampling method was used. The traits DELAYED and PREGNANT were analysed as threshold traits and APP, FEED, LW, BC, WSI7, WSI50 and NBT2 were analysed as linear traits. The heritability estimates for APP and FEED were low (<0.1), whereas the estimates for DELAYED and PREGNANT were rather high (0.4 and 0.3). The heritability estimate for BC was 0.2. The genetic correlations confirmed the complexity of breeding for sow performance; selection for heavy 1st litters may lead to lower body condition at weaning, which in turn leads to lower reproductive performance and smaller litters in 2nd parity. Selection for higher sow feed intake would improve body condition, but the simple way of measuring feed intake tested in this study (APP and FEED) cannot be recommended because of the low heritability obtained for these traits.     

Genetic parameters of a biological lactation model: early lactation and secretion rate traits of dairy heifers

Early lactation parameters are difficult to estimate from commercial dairy records due to the small number of records available before the peak of production. A biological model of lactation was used with weekly milk records from a single Holstein herd to estimate these early lactation parameters and the secretion rate of milk from the average cell throughout lactation. A genetic analysis of the lactation curve parameters, calculated curve characteristics and secretion rate traits was undertaken. Early lactation traits were found to have little genetic variation and effectively zero heritability. Secretion rate traits for milk, protein, lactose and water were all moderately heritable and highly genetically correlated (>0.87) but fat secretion rate had lower genetic correlations with the other secretion rates. A similar pattern of correlations was seen between total lactation yield traits for fat, protein, lactose and water. The genetic correlations between the lactation curve traits and the secretion rate traits were calculated. Total milk yield, peak yield and maximum secretion potential were all highly correlated with milk, lactose and water secretion rates but less so with fat and protein secretion rates. In particular, fat secretion rate had a moderate to low genetic correlation with these lactation curve traits. Persistency of lactation was highly correlated with fat and protein secretion rates, more persistent lactations being associated with lower rates of secretion of these milk components. Similar levels of heritability were found, where trait genetic parameters were directly equivalent to those derived from the same dataset by random regression methods. However, by using a biological model of lactation to analyse lactation traits new insights into the biology of lactation are possible and ways to select cows on a range of lactation traits may be achieved.     

Merging and characterising phenotypic data on conventional and rare traits from dairy cattle experimental resources in three countries

This study set out to demonstrate the feasibility of merging data from different experimental resource dairy populations for joint genetic analyses. Data from four experimental herds located in three different countries (Scotland, Ireland and the Netherlands) were used for this purpose. Animals were first lactation Holstein cows that participated in ongoing or previously completed selection and feeding experiments. Data included a total of 60 058 weekly records from 1630 cows across the four herds; number of cows per herd ranged from 90 to 563. Weekly records were extracted from the individual herd databases and included seven traits: milk, fat and protein yield, milk somatic cell count, liveweight, dry matter intake and energy intake. Missing records were predicted with the use of random regression models, so that at the end there were 44 weekly records, corresponding to the typical 305-day lactation, for each cow. A total of 23 different lactation traits were derived from these records: total milk, fat and protein yield, average fat and protein percentage, average fat-to-protein ratio, total dry matter and energy intake and average dry matter intake-to-milk yield ratio in lactation weeks 1 to 44 and 1 to 15; average milk somatic cell count in lactation weeks 1 to 15 and 16 to 44; average liveweight in lactation weeks 1 to 44; and average energy balance in lactation weeks 1 to 44 and 1 to 15. Data were subsequently merged across the four herds into a single dataset, which was analysed with mixed linear models. Genetic variance and heritability estimates were greater (P < 0.05) than zero for all traits except for average milk somatic cell count in weeks 16 to 44. Proportion of total phenotypic variance due to genotype-by-environment (sire-by-herd) interaction was not different (P > 0.05) from zero. When estimable, the genetic correlation between herds ranged from 0.85 to 0.99. Results suggested that merging experimental herd data into a single dataset is both feasible and sensible, despite potential differences in management and recording of the animals in the four herds. Merging experimental data will increase power of detection in a genetic analysis and augment the potential reference population in genome-wide association studies, especially of difficult-to-record traits.     

Genetic analysis for mastitis resistance and milk somatic cell score in French Lacaune dairy sheep

Genetic analysis for mastitis resistance was studied from two data sets. Firstly, risk factors for different mastitis traits, i.e. culling due to clinical or chronic mastitis and subclinical mastitis predicted from somatic cell count (SCC), were explored using data from 957 first lactation Lacaune ewes of an experimental INRA flock composed of two divergent lines for milk yield. Secondly, genetic parameters for SCC were estimated from 5 272 first lactation Lacaune ewes recorded among 38 flocks, using an animal model. In the experimental flock, the frequency of culling due to clinical mastitis (5%) was lower than that of subclinical mastitis (10%) predicted from SCC. Predicted subclinical mastitis was unfavourably associated with the milk yield level. Such an antagonism was not detected for clinical mastitis, which could result, to some extent, from its low frequency or from the limited amount of data. In practice, however, selection for mastitis resistance could be limited in a first approach to selection against subclinical mastitis using SCC. The heritability estimate of SCC was 0.15 for the lactation mean trait and varied from 0.04 to 0.12 from the first to the fifth test-day. The genetic correlation between lactation SCC and milk yield was slightly positive (0.15) but showed a strong evolution during lactation, i.e. from favourable (-0.48) to antagonistic (0.27). On a lactation basis, our results suggest that selection for mastitis resistance based on SCC is feasible. Patterns for genetic parameters within first lactation, however, require further confirmation and investigation.     

Profile and genetic parameters of dairy cattle locomotion score and lameness across lactation

This study investigated the profile of locomotion score and lameness before the first calving and throughout the first (n=237) and second (n=66) lactation of 303 Holstein cows raised on a commercial farm. Weekly heritability estimates of locomotion score and lameness, and their genetic and phenotypic correlations with milk yield, body condition score, BW and reproduction traits were derived. Daughter future locomotion score and lameness predictions from their sires’ breeding values for conformation traits were also calculated. First-lactation cows were monitored weekly from 6 weeks before calving to the end of lactation. Second-lactation cows were monitored weekly throughout lactation. Cows were locomotion scored on a scale from one (sound) to five (severely lame); a score greater than or equal to two defined presence of lameness. Cows’ weekly body condition score and BW was also recorded. These records were matched to corresponding milk yield records, where the latter were 7-day averages on the week of inspection. The total number of repeated records amounted to 12 221. Data were also matched to the farm’s reproduction database, from which five traits were derived. Statistical analyses were based on uni- and bivariate random regression models. The profile analysis showed that locomotion and lameness problems in first lactation were fewer before and immediately after calving, and increased as lactation progressed. The profile of the two traits remained relatively constant across the second lactation. Highest heritability estimates were observed in the weeks before first calving (0.66 for locomotion score and 0.54 for lameness). Statistically significant genetic correlations were found for first lactation weekly locomotion score and lameness with body condition score, ranging from −0.31 to −0.65 and from −0.44 to −0.76, respectively, suggesting that cows genetically pre-disposed for high body condition score have fewer locomotion and lameness issues. Negative (favourable) phenotypic correlations between first lactation weekly locomotion score/lameness and milk yield averaged −0.27 and −0.17, respectively, and were attributed to management factors. Also a phenotypic correlation between lameness and conception rate of −0.19 indicated that lame cows were associated with lower success at conceiving. First-lactation daughter locomotion score and/or lameness predictions from sires’ estimated breeding values for conformation traits revealed a significant linear effect of rear leg side view, rear leg rear view, overall conformation, body condition score and locomotion, and a quadratic effect of foot angle.     

Genetic and phenotypic parameters of age at first mating, litter size and animal size in Finnish mink

Mink skin size in Finland, as well as in other countries, has increased considerably during last decade. However, there are signs that selection for large body size has a negative impact on litter size (LS) and also for survival of kits. Therefore, it is important to study the genetic relationships among fertility traits and animal size (AS). The variance components for age at first mating (AFM) and first three parity LS and AS were estimated using multi-trait restricted maximum likelihood animal model. Data included 82 945 animals born during 1990 to 2004, originating from nine farms. Heritability estimates for the fertility traits were from 0.10 to 0.15. For AS, heritability was estimated to be 0.18. Genetic correlation between AS and all fertility traits was estimated to be negative (varying from -0.004 to -0.38). It is important to recognize this antagonistic relationship and include the reproductive traits into breeding goals to maintain good reproductive performance when selecting for increased body size and hence larger pelts in fur animals. Genetic correlations between the traits should be accounted in breeding value evaluations by using a multi-trait model. Including AFM into breeding value estimation would also improve the accuracy of breeding value estimation for fertility, because females missing the first LS still have record on AFM.     

Quantitative genetics and fitness effects of basal metabolism

The physiological requirements of reproduction are predicted to generate a link between energy, physiology and life history traits. Simultaneously, low maintenance costs, measured by energy consumption, are expected to be advantageous. Here we investigated fitness relatedness of traits by estimating genetic correlations between, and inbreeding depression for, body mass, basal metabolic rate (BMR) and other life history characters in a wild rodent, Myodes glareolus. The narrow-sense heritability of absolute and mass corrected BMRs were high for females (h² = 0.48 and 0.42) but low and non-significant for males (0.32 and 0.09). A significant positive genetic correlation between BMR and litter size suggests that traits connected to female fecundity might favour higher metabolism (i.e. support increased intake hypothesis). However, the estimates of inbreeding depression indicate that, while higher values of body mass and female litter size could be positively associated with overall fitness, the association between BMR and overall fitness in bank voles would be negative (i.e. support compensation hypothesis). This result suggests that the advantages of larger litters and larger body mass might be evolutionary constrained by high costs of maintenance of those traits, as reflected by the level of basal metabolism.     

Effect of genetic merit, milk yield, body condition and lactation number on in vitro oocyte development in dairy cows

The effects of milk yield, body condition score (BCS) and lactation number on the number of oocytes recovered and blastocysts formed were studied following in vitro maturation, fertilization and culture of bovine oocytes collected from 48 high and 46 medium genetic merit dairy cows in their first and third lactation. The cows were slaughtered between 125 and 229 d post partum. Ovaries were recovered, and 2- to 10-mm follicles were aspirated. Cleavage rate and number of blastocysts were determined at 44 h and 7 d after insemination, respectively. Oocytes from high genetic merit cows formed fewer blastocysts and had lower cleavage and blastocyst formation rates than those from medium genetic merit cows (0.36 +/- 0.19, 70.4 and 6.8% vs 0.85 +/- 0.22, 77.4 and 11.4%, respectively). The effect of milk production was tested by grouping cows in their third lactation into high and low groups. There was no difference in number of oocytes recovered and subsequent development into blastocysts between the cows in the high milk production group (4559 to 5114 kg, n = 20) and cows in the low yield (3162 to 3972 kg, n = 20) group (6.9 +/- 1.34 vs 8.9 +/- 1.32, respectively). The effect of BCS was tested by grouping cows in their first or third lactation into high and low groups. Cleavage and blastocyst formation rates were greater for oocytes from cows with a high BCS (3.3 to 4.0, n = 20) than a low BCS (1.5 to 2.5, n = 20) (75.7 vs 61.9% and 9.9 vs 3.0%, respectively). Cows in the first lactation yielded fewer oocytes (5.7 +/- 1.24) than cows in the third lactation (7.8 +/- 0.79). Thus, the quality of oocytes probably contributes to reduced fertility, often evident in high genetic merit dairy cows.     

The role of nutrition, body condition and lactation on calving success in muskoxen

Relationships between nutrition, body weight (BW), body condition score (BCS) and fertility were explored in 11 captive female muskoxen between 1988–1994. In 1987, six adult female muskoxen were allocated to high plane (HP) or low plane (LP) nutritional treatments (HP n = 3; LP n = 3), which were maintained year-round through spring 1995 (HP n = 6; LP n = 5). Treatment group size fluctuated annually. Age, lactation status, calving date and calf birth weight were recorded for each cow. Body weight was measured weekly and BCS measured bi-weekly throughout the mating season from 1 August to 31 October. Sixty-one complete observations of BW and BCS in autumn, lactation status and calving success were collected. Body weight and BCS differed significantly ( t -test) with pregnancy ( P < 0.001) and nutritional treatment ( P < 0.001). A significant logistic regression model was generated for the relationship between BW in October and pregnancy ( P < 0.001). When BCS each month was combined with BW in October, BCS in September was the most significant variable ( P < 0.001) and the only one to enter the model. Neither lactational status nor year, in combination or alone, was significant. Both BW in autumn (176 kg provides a 50% probability of a female calving the following spring) and BCS (score of six provides a 50% probability of successful calving) can be useful predictors of fertility in muskoxen. The ability of muskoxen to make significant gains in weight and body condition in autumn may represent a nutritional control point regulating reproduction in this species.     

Metabolic profiles and progesterone cycles in first lactation dairy cows

This study investigated the ovarian function, metabolic profiles and fertility in first lactation Holstein-Friesian dairy cows (mean 305 day milk yield: 7417+/-191kg, n=37). Reproductive profiles obtained from milk progesterone analysis were categorized into normal (n=17) and four abnormal profiles (delayed ovulation, DOV1, n=9; DOV2, n=2; persistent corpus luteum, PCL1, n=6; PCL2, n=4; 1: immediately post-calving, 2: subsequent cycles). Fifty-five percent of cows had abnormal profiles with half of these being categorized as DOV1. Fertility of DOV1 and DOV2 cows was reduced whereas PCL1 and PCL2 cows had similar reproductive competence to normal profile cows. DOV1 animals had higher milk energy values, lower energy balances, lower dry matter intakes (DMI) and greater body weight and body condition score (BCS) losses post-calving than normal profile animals. DOV1 animals also had lower insulin-like growth factor-I (IGF-I) and higher betahydroxybutyrate (BHB) concentrations and tended to have the lower insulin and glucose concentrations in the pre-service period than normal profile cows. All PCL animals had vulval discharges postpartum. Despite this, the DMI, body weight and BCS changes, IGF-I concentrations and fertility of PCL1 animals was similar to normal profile cows. In conclusion, the high prevalence of delayed ovulation post-calving (DOV1) in primiparous high yielding cows lasted long enough (71+/-8.3 days) to have a detrimental impact on fertility and was associated with significant physiological changes. This study did not establish any detrimental effects of PCL profiles on fertility or production parameters.