Feed represents a large proportion of the variable costs in dairy production systems. The omission of feed intake measures explicitly from national dairy cow breeding objectives is predominantly due to a lack of information from which to make selection decisions. However, individual cow feed intake data are available in different countries, mostly from research or nucleus herds. None of these data sets are sufficiently large enough on their own to generate accurate genetic evaluations. In the current study, we collate data from 10 populations in 9 countries and estimate genetic parameters for dry matter intake (DMI). A total of 224,174 test-day records from 10,068 parity 1 to 5 records of 6,957 cows were available, as well as records from 1,784 growing heifers. Random regression models were fit to the lactating cow test-day records and predicted feed intake at 70 d postcalving was extracted from these fitted profiles. The random regression model included a fixed polynomial regression for each lactation separately, as well as herd-year-season of calving and experimental treatment as fixed effects; random effects fit in the model included individual animal deviation from the fixed regression for each parity as well as mean herdspecific deviations from the fixed regression. Predicted DMI at 70 d postcalving was used as the phenotype for the subsequent genetic analyses undertaken using an animal repeatability model. Heritability estimates of predicted cow feed intake 70 d postcalving was 0.34 across the entire data set and varied, within population, from 0.08 to 0.52. Repeatability of feed intake across lactations was 0.66. Heritability of feed intake in the growing heifers was 0.20 to 0.34 in the 2 populations with heifer data. The genetic correlation between feed intake in lactating cows and growing heifers was 0.67. A combined pedigree and genomic relationship matrix was used to improve linkages between populations for the estimation of genetic correlations of DMI in lactating cows; genotype information was available on 5,429 of the animals. Populations were categorized as North America, grazing, other low input, and high input European Union. Albeit associated with large standard errors, genetic correlation estimates for DMI between populations varied from 0.14 to 0.84 but were stronger (0.76 to 0.84) between the populations representative of high-input production systems. Genetic correlations with the grazing populations were weak to moderate, varying from 0.14 to 0.57. Genetic evaluations for DMI can be undertaken using data collated from international populations; however, genotype-by-environment interactions with grazing production systems need to be considered.
The main effects of, and the interactions between, stocking rate (SR), supplementation and genotype on dry matter (DM) intake, herbage utilisation, milk production and profitability of grazing dairy systems have been reviewed. The SR determines the average herbage allowance (HA) per cow and therefore has a major effect on herbage intake (HI) and on the productivity of grazing dairy systems. In this review, the effect of HA on HI is presented separately for two groups of studies: those that measured allowance at ground level and those that measured allowance at a cutting height of 3Á5 cm above ground level. HI and milk yield per hectare usually increase as SR increases. However, there is generally an associated reduction in HI and milk yield per cow because of the decrease in average HA at a higher SR. The dual objectives of adequate level of feeding per cow and high herbage utilisation per hectare can be achieved through the inclusion of supplements. The milk response to supplements depends mainly on the size of the relative energy deficit between potential energy demand and actual energy supply. The relative energy deficit determines both energy partitioning within the cow and substitution rate. The relative energy deficit is increased by either a high demand for energy within the cow or by a deficit of dietary energy available to meet the demand. Cows of different genotype differ in their potential for milk yield. Cows with high genetic potential for milk yield undergo higher relative energy deficits under grazing dairy systems, resulting in lower substitution rates, higher milk responses to supplements, but also lower body condition score, which, in turn, leads to lower reproductive performance. Whole-farm experiments in many countries have demonstrated that the inclusion of supplements, with a concomitant increase in SR, can have synergistic effects in improving the productivity of grazing dairy systems. Overall, the level of supplementation required per cow and the optimum SR depend on the genetic potential of the cow, the size of the responses to supplement, the value of milk and the costs of feeding supplements.
Variation at the pleiomorphic adenoma gene 1 (PLAG1) locus has recently been implicated in the regulation of stature and weight in Bos taurus. Using a population of 942 outbred Holstein-Friesian dairy calves, we report confirmation of this effect, demonstrating strong association of early life body weight with PLAG1 genotype. Peripubertal body weight and growth rate were also significantly associated with PLAG1 genotype. Growth rate per kilogram of body weight, daily feed intake, gross feed efficiency and residual feed intake were not significantly associated with PLAG1 genotype. This study supports the status of PLAG1 as a key regulator of mammalian growth. Further, the data indicate the utility of PLAG1 polymorphisms for the selection of animals to achieve enhanced weight gain or conversely to aid the selection of animals with lower mature body weight and thus lower maintenance energy requirements.
The objectives of this study were to determine the effect of calving body condition score (BCS) on cow health during the transition period in a pasture-based dairying system. Feed inputs were managed during the second half of the previous lactation so that BCS differed at drying off (BCS 5.0, 4.0, and 3.0 for high, medium, and low treatments, respectively: a 10-point scale); feed allowance was managed after cows were dried off, such that the BCS differences established during lactation remained at the subsequent calving (BCS 5.5, 4.5, and 3.5; n=20, 18, and 19, for high, medium, and low treatments, respectively). After calving, cows were allocated pasture and pasture silage to ensure grazing residuals >1,600 kg of DM/ha. Milk production was measured weekly; blood was sampled regularly pre- and postpartum to measure indicators of health, and udder and uterine health were evaluated during the 6 wk after calving. Milk weight, fat, protein, and lactose yields, and fat content increased with calving BCS during the first 6 wk of lactation. The effect of calving BCS on the metabolic profile was nonlinear. Before calving, cows in the low group had lower mean plasma β-hydroxybutyrate and serum Mg concentrations and greater mean serum urea than cows in the medium and high BCS groups, which did not differ from each other. During the 6 wk after calving, cows in the low group had lower serum albumin and fructosamine concentrations than cows in the other 2 treatment groups, whereas cows in the low- and medium-BCS groups had proportionately more polymorphonucleated cells in their uterine secretions at 3 and 5 wk postpartum than high-BCS cows. In comparison, plasma β-hydroxybutyrate and nonesterified fatty acid concentrations increased linearly in early lactation with calving BCS, consistent with a greater negative energy balance in these cows. Many of the parameters measured did not vary with BCS. The results highlight that calving BCS and, therefore, BCS through early lactation are not effective indicators of functional welfare, with the analyses presented indicating that both low and high BCS at calving will increase the risk of disease: cows in the low group were more prone to reproductive compromise and fatter cows had an increased risk of metabolic diseases. These results are important in defining the welfare consequences of cow BCS.
Prevailing weather conditions influence herbage growth and quality, and therefore may have a substantial impact on animal production. Before investigating relationships between weather factors, herbage quality, and animal production, it is beneficial to first quantify temporal trends in herbage quality characteristics and mineral concentrations. The objective of the present study was to investigate the existence of temporal trends in herbage quality characteristics and mineral concentrations, and to quantify the intra-dependency among these variables. Weekly herbage quality and mineral concentration data from a research farm were collected from 1995 to 2001, inclusive. Fitted sinusoidal functions demonstrated cyclic temporal trends across herbage quality variables, but there was little cyclic temporal variation in the majority of herbage mineral concentration variables. The repeatability of herbage quality measurements was low to moderate (22% for ether extract to 54% for metabolisable energy). Linear relationships were observed within all herbage quality variables and herbage mineral concentration variables. Neutral detergent fibre and acid detergent fibre concentrations were strongly positively correlated with each other (r = 0.87), and negatively correlated with herbage digestibility (r = –0.64 and –0.74, respectively), water-soluble carbohydrate concentration (r = –0.52 and –0.68, respectively) and metabolisable energy content (r = –0.60 and –0.75, respectively). The absolute correlations among most herbage minerals were poor (r <0.30). However, magnesium concentration was positively correlated with calcium (r = 0.54), copper (r = 0.56), and manganese (r = 0.37) concentrations, and negatively correlated with zinc (r = –0.56) concentration. Further investigation is required into the relationships between temporal weather and herbage quality trends, and their impact on animal production.
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