The assessment of grazing behavior is important for research and practice in pasture-grazed dairy farm systems. However, few devices are available that enable assessment of cow grazing behavior at an individual animal level. This study investigated whether commercially available Smarttag “eating time” sensors (Nedap Livestock Management, Groenlo, the Netherlands) were suitable for recording the grazing time of cows. Smarttag sensors were mounted on the neck collars of multiparous Holstein-Friesian cows in a herd in Taranaki, New Zealand. Cows were randomly selected each observation day from the milking herd for 8 separate days across a 1-mo period. Trained observers conducted 90-min observation periods to evaluate the relationship between the sensor eating time measure and grazing time. A set of 5 defined cow behaviors (2 “head up” and 3 “head down” behaviors) were assessed. In total, observations of 37 cows were recorded in 14 sessions over 8 d in the study period, providing 55.5 total hours of observations. Observation data were aligned with sensor data according to the sensor time stamps and grouped into matching 15-min intervals. Interobserver reliability was assessed both before and after the main trial period, and the mean percentage eating time per observer had a coefficient of variation of 0.46% [mean 93.2, standard deviation (SD) 0.425] before and 0.07% (mean 96.3, SD 0.074) after. In the main trial, the relationship between observed (mean 70.8%) and sensor-derived (mean 69.3%) percentage eating time over the observation period gave a Pearson correlation coefficient of 0.971, concordance correlation coefficient 0.968, mean difference 1.50% points, and SD 5.8% points. Therefore, sensor-identified percentage “eating time” and observed percentage active grazing time were shown to be both very well correlated and concordant (in agreement, with high correlation and little bias). Therefore, the relationship between observed and sensor-derived data had a high degree of agreement for identifying cow grazing activity. In conclusion, Smarttag sensors are a valid and useful tool for estimating grazing activity at time periods of 1 h or more.

Choice of stocking rate and breed of cow are 2 strategic decisions that affect the profitability of pasture-based dairy farm businesses. This study sought to analyze the effects of a range of fat and protein prices on the profitability of the Jersey (J) and Holstein-Friesian (HF) breeds at 2 comparative stocking rates (CSR): 80 kg of body weight (BW) per tonne of dry matter (DM) of feed (CSR80), and 100 kg of BW per tonne of DM of feed (CSR100). Data were obtained from a recently published study, and equations constructed to determine the values for fat and protein at which each breed broke even (profit = NZ$0/ha; at time of writing, NZ$1 = US$0.69 or €0.60), returned equal profit, and exceeded the other breed by 1% or 5%. At CSR100 there were few combinations of fat and protein prices for which HF were more profitable than J. At CSR80, J and HF were equally profitable at a fat price of NZ$5.67 ± NZ$0.20 per kilogram, depending on protein price. The study also highlighted the importance of including volume adjustments in milk price calculations when differences in milk composition exist, as the fat price at which the profitability of HF and J were equal was NZ$1.23/kg lower when volume adjustments were included. The recent increase in the value of fat relative to protein favors J. Farmers should consider the medium- to long-term outlook of fat price when evaluating breed choice for their farm system.

Reducing enteric methane (CH4) production and improving feed conversion efficiency of dairy cows is of high importance. Residual feed intake (RFI) is one measure of feed efficiency, with low RFI animals being more efficient in feed conversion. Enteric CH4 is an important source of digestible energy loss in ruminants and, because research in beef cattle has reported a positive relationship between RFI and daily CH4 production, we hypothesized that low RFI dairy heifers, which are more feed efficient, would produce less CH4/d. We measured the daily methane production (g of CH4/d), methane yield [g of CH4/kg of dry matter intake (DMI)], and CH4 per kilogram of body weight (BW) gain for 56 heifers (20-22 mo old) in a 2 × 2 factorial arrangement: factors included 2 breeds (Holstein-Friesian and Jersey; n = 28/breed), with equal numbers of animals previously determined as being either high [+2.0 kg of dry matter (DM)/d] or low RFI (-2.1 kg of DM/d; n = 28/RFI category). All heifers were commingled and offered unrestricted access to the same diet of dried alfalfa cubes. Between RFI categories, heifers did not differ in BW or BW gain but low RFI heifers had 9.3 and 10.6% lower DMI and DMI/kg of BW, respectively, than high RFI heifers. Similarly, RFI category did not affect CH4/d or CH4/kg of BWg, but CH4/kg of DMI was higher in low RFI heifers because of their lower DMI. These results might reflect more complete digestion of ingested feed in the more efficient, low RFI heifers, consistent with previous reports of greater apparent digestibility of organic matter. Holstein-Friesian heifers were heavier and consumed more total DM than Jersey heifers, but breed did not affect DMI/kg of BW or BWg. Jersey heifers produced less CH4/d, but not CH4/kg of DMI or CH4/kg of BWg. We detected no interaction between breed and RFI category in any of the variables measured. In conclusion, differences in RFI in dairy heifers did not affect daily CH4 production (g/d); however, low RFI heifers had a greater CH4 yield (g/kg of DMI) on a high forage diet.

In theory, a late winter-early spring calving date in temperate grazing systems best matches pasture supply and herd demand, thereby minimizing the need for nonpasture feeds and maximizing profitability. We used a quantitative case study approach to define the effects of season of calving on biophysical and financial performance in a grazing system without the confounding effects of imported feeds (i.e., milk production directly from grazed pasture). A 2-yr production system experiment was established to quantify the effects of changing onset of seasonal calving (i.e., planned start of calving; PSC) from winter (July in the Southern Hemisphere) to spring (October), summer, (January), or autumn (April) on pasture and animal production and profitability. Eighty Holstein-Friesian cows were randomly allocated to 1 of 4 PSC treatments, each of which had a different PSC [mean calving date of January 10 (JAN), April 10 (APR), July 10 (JUL), or October 10 (OCT)]. Data were analyzed for consistency of treatment response over years using ANOVA procedures with year, PSC treatment, and year × PSC treatment interactions as fixed effects. Collated biological data and financial data extracted from a national economic database were used as fixed variables to model the financial performance for the different treatments. A stochastic risk analysis was undertaken, where historical pasture growth and milk price data were used to estimate the probability distributions for stochastic input variables. Gross farm revenue and operating profit per hectare were modeled under 2 scenarios: (A) milk price did not include a premium for milk supplied during the winter, and (B) milk price included a realistic premium for milk supplied in winter. Annual and seasonal pasture growth did not differ between treatments, but the pasture growth (kg of dry matter/ha) and profile of the JUL treatment best matched the lactation nutrient demand profile. In comparison, profiles for JAN, APR, and OCT calving treatments had periods of greater surplus and deficit due to the time of calving and herd demand relative to the pasture growth profile. As a result, the JAN and OCT treatments conserved more pasture as silage and cows consumed a larger proportion of their annual diet as silage. Although the amount of silage conserved and consumed did not differ between the JUL and APR calving treatments, the timing of the silage consumption was different, with silage making up a greater proportion of the diets in the APR treatment 1 to 90 and 91 to 180 d postcalving and being offered to the JUL calving treatment only 271 to 365 d postcalving. As a result of differences in the quantity and proportion of pasture and pasture silage in the lactating diet, the JUL treatment herd tended to produce greater milk, 4% fat-corrected milk, fat, protein, and lactose yields (kg/cow) than the other PSC treatments, which did not differ from each other. Operating expenses per hectare did not differ materially between calving date scenarios, but operating expenses per kilogram of fat-corrected milk and kilogram of fat and protein were 15 to 20% less in the JUL treatment. With or without a realistic winter milk premium, gross farm revenue and operating profit per hectare were greater in the JUL treatment than in the APR treatment, which had greater revenue and profitability than the remaining 2 calving date treatments. In summary, our results indicate that a PSC in late winter is most profitable in a grazing system not importing feed, with or without a realistic price incentive scheme.

Economic optimum stocking rates for grazing dairy systems have been defined by accounting for the pasture production potential of the farm [t of dry matter (DM)/ha], the amount of feed imported from outside the farm (t of DM/ha), and the size of the cow (kg). These variables were combined into the comparative stocking rate [CSR; kg of body weight (BW)/t of feed DM available] measure. However, CSR assumes no effect of cow genetics beyond BW, and there is increasing evidence of within-breed differences in residual feed intake and between-breed differences in the gross efficiency with which cows use metabolizable energy for milk production. A multiyear production system experiment was established to determine whether Jersey (J) and Holstein-Friesian (HF) breeds performed similarly at the same CSR. Fifty-nine J cows and 51 HF cows were randomly allocated to 1 of 2 CSR in a 2 × 2 factorial arrangement; systems were designed to have a CSR of either 80 or 100 kg of BW/t of feed DM (J-CSR80, J-CSR100, HF-CSR80, and HF-CSR100 treatment groups). Data were analyzed for consistency of farmlet response over years using ANOVA procedures, with year and farmlet as fixed effects and the interaction of farmlet with year as a random effect. The collated biological data and financial data extracted from a national economic database were used to model the financial performance for the different breed and CSR treatments. On average, annual and individual season pasture DM production was greater for the J farmlets and was less in the CSR100 treatment; however, the effect of CSR was primarily driven by a large decline in pasture DM production in the HF-CSR100 treatment (breed × CSR interaction). This interaction in feed availability resulted in a breed × CSR interaction for the per-cow and per-hectare milk production variables, with HF cows producing more milk and milk components per cow in the CSR80 treatment but the same amount as the J cows in the CSR100 treatment. On a per-hectare basis, HF cows produced the same amount of 4% fat-corrected milk and lactose as J cows in the CSR80 treatment, but less fat; at CSR100, J cows produced more 4% fat-corrected milk, fat, and protein per hectare than HF cows. Our results support a greater gross efficiency for use of metabolizable energy by the J cow; 11% less total metabolizable energy was required to produce 1 kg of fat and protein at a system level. Economic modeling indicated that profitability of both breeds was less at CSR100, but the decline in profitability with increasing stocking rate was much greater in the HF breed. Holstein-Friesian cows were more profitable at CSR80 but were less profitable at CSR100.

Although food from grazed animals is increasingly sought by consumers because of perceived animal welfare advantages, grazing systems provide the farmer and the animal with unique challenges. The system is dependent almost daily on the climate for feed supply, with the importation of large amounts of feed from off farm, and associated labour and mechanisation costs, sometimes reducing economic viability. Furthermore, the cow may have to walk long distances and be able to harvest feed efficiently in a highly competitive environment because of the need for high levels of pasture utilisation. She must, also, be: (1) highly fertile, with a requirement for pregnancy within ~80 days post-calving; (2) ‘easy care’, because of the need for the management of large herds with limited labour; (3) able to walk long distances; and (4) robust to changes in feed supply and quality, so that short-term nutritional insults do not unduly influence her production and reproduction cycles. These are very different and are in addition to demands placed on cows in housed systems offered pre-made mixed rations. Furthermore, additional demands in environmental sustainability and animal welfare, in conjunction with the need for greater system-level biological efficiency (i.e. ‘sustainable intensification’), will add to the ‘robustness’ requirements of cows in the future. Increasingly, there is evidence that certain genotypes of cows perform better or worse in grazing systems, indicating a genotype×environment interaction. This has led to the development of tailored breeding objectives within countries for important heritable traits to maximise the profitability and sustainability of their production system. To date, these breeding objectives have focussed on the more easily measured traits and those of highest relative economic importance. In the future, there will be greater emphasis on more difficult to measure traits that are important to the quality of life of the animal in each production system and to reduce the system’s environmental footprint.

Production from pasture-based dairy farms can be increased through using N fertilizer to increase pasture grown, increasing stocking rate, importing feeds from off farm (i.e., supplementary feeds, such as cereal silages, grains, or co-product feeds), or through a combination of these strategies. Increased production can improve profitability, provided the marginal cost of the additional milk produced is less than the milk price received. A multiyear production system experiment was established to investigate the biological and economic responses to intensification on pasture-based dairy farms; 7 experimental farmlets were established and managed independently for 3 yr. Paddocks and cows were randomly allocated to farmlet, such that 3 farmlets had stocking rates of 3.35 cows/ha (LSR) and 4 farmlets had stocking rates of 4.41 cows/ha (HSR). Of the LSR farmlets, 1 treatment received no N fertilizer, whereas the other 2 received either 200 or 400 kg of N/ha per year (200N and 400N, respectively). No feed was imported from off-farm for the LSR farmlets. Of the 4 HSR farmlets, 3 treatments received 200N and the fourth treatment received 400N; cows on 2 of the HSR-200N farmlet treatments also received 1.3 or 1.1 t of DM/cow per year of either cracked corn grain or corn silage, respectively. Data were analyzed for consistency of farmlet response over years using mixed models, with year and farmlet as fixed effects and the interaction of farmlet with year as a random effect. The biological data and financial data extracted from a national economic database were used to model the statement of financial performance for the farmlets and determine the economic implications of increasing milk production/cow and per ha (i.e., farm intensification). Applying 200N or 400N increased pasture grown per hectare and milk production per cow and per hectare, whereas increasing stocking rate did not affect pasture grown or milk production per hectare, but reduced milk production per cow. Importing feed in the HSR farmlets increased milk production per cow and per hectare. Marginal milk production responses to additional feed (i.e., either pasture or imported supplementary feed) were between 0.8 and 1.2 kg of milk/kg of DM offered (73 to 97 g of fat and protein/kg of feed DM) and marginal response differences between feeds were explained by metabolizable energy content differences (0.08 kg of milk/MJ of metabolizable energy offered). The marginal milk production response to additional feed was quadratic, with the greatest milk production generated from the initial investment in feed; 119, 99, and 55 g of fat and protein were produced per kilogram of feed DM by reducing the annual feed deficit from 1.6 to 1.0, 1.0 to 0.5, and 0.5 to 0 t of DM, respectively. Economic modeling indicated that the marginal cost of milk produced from pasture resulting from applied N fertilizer was less than the milk price; therefore, strategic use of N fertilizer to increase pasture grown increased farm operating profit per hectare. In comparison, operating profit declined with purchased feed, despite high marginal milk production responses. The results have implications for the strategic direction of grazing dairy farms, particularly in export-oriented industries, where the prices of milk and feed inputs are subject to the considerable volatility of commodity markets.

An efficient dairy system, that implemented a combination of nitrogen (N) leaching mitigation strategies including lower N fertilizer input, standing cows off pasture for part of the day in autumn and winter (stand-off), and importing limited amounts of low protein supplements was evaluated over four consecutive years of a farmlet study. This efficient system consistently demonstrated a lower measured annual N leaching of 40 to 50% compared with a baseline system representing current practice with no mitigations. To maximize return from this system fewer cows but of higher genetic merit were used resulting in an average decrease in milk production of 2% and operating profit by 5% compared with the baseline system. The magnitude of the N leaching reduction from mitigation strategies was predicted in pre-trial modelling. Using similar mechanistic models in a post-trial study, we were able to satisfactorily predict the trends in the observed N leaching data over the four years. This enabled us to use the calibrated models to explore the contributions of the different mitigation strategies to the overall leaching reduction in the efficient system. In one of the years half of the leaching reduction was achieved by the 'input' component of the strategy (less feed N flowing through the herd from lower fertilizer use, less grass grown, and low-protein supplement use), while the other half was achieved by the stand-off strategy. However, these contributions are determined by the weather of a particular year. We estimate that on average stand-off would contribute 60% and 'input' 40% to the reduction. The implication is that farmers facing nutrient loss limitations have some current and some future technologies available to them for meeting these limitations. A shift towards the mitigations described here can result in a downward trend in their own N-loss metrics. The challenge will be to negate any reductions in production and profit, and remain competitive.

From 1917 to 2017, dairy grazing systems have evolved from uncontrolled grazing of unimproved pastures by dual-purpose dairy-beef breeds to an intensive system with a high output per unit of land from a fit-for-purpose cow. The end of World War I signaled significant government investments in agricultural research institutes around the world, which coincided with technological breakthroughs in milk harvesting and a recognition that important traits in both plants and animals could be improved upon relatively rapidly through genetic selection. Uptake of milk recording and herd testing increased rapidly through the 1920s, as did the recognition that pastures that were rested in between grazing events yielded more in a year than those continuously grazed. This, and the invention and refinement of the electric fence, led to the development of "controlled" rotational grazing. This, in itself, facilitated greater stocking rates and a 5 to 10% increase in milk output per hectare but, perhaps more importantly, it allowed a more efficient use of nitrogen fertilizer, further increasing milk output/land area by 20%. Farmer inventions led to the development of the herringbone and rotary milking parlors, which, along with the "unshortable" electric fence and technological breakthroughs in sperm dilution rates, allowed further dairy farm expansion. Simple but effective technological breakthroughs in reproduction ensured that cows were identified in estrus early (a key factor in maintaining the seasonality of milk production) and enabled researchers to quantify the anestrus problem in grazing herds. Genetic improvement of pasture species has lagged its bovine counterpart, but recent developments in multi-trait indices as well as investment in genetic technologies should significantly increase potential milk production per hectare. Decades of research on the use of feeds other than pasture (i.e., supplementary feeds) have provided consistent milk production responses when the reduction in pasture intake associated with the provision of supplementary feed (i.e., substitution rate) is accounted for. A unique feature of grazing systems research over the last 70 yr has been the use of multi-year farm systems experimentation. These studies have allowed the evaluation of strategic changes to a component of the system on all the interacting features of the system. This technique has allowed excellent component research to be "systemized" and is an essential part of the development of the intensive grazing production system that exists today. Future challenges include the provision of skilled labor or specifically designed automation to optimize farm management and both environmental sustainability and animal welfare concerns, particularly relating to the concentration of nitrogen in each urine patch and the associated risk of nitrate leaching, as well as concerns regarding exposure of animals to harsh climatic conditions. These combined challenges could affect farmers' "social license" to farm in the future.

Exosomes are a specific subpopulation of extracellular vesicles that are widely released by cells of different origins with divergent functions that make their way into body fluids that can be conveniently sampled. In the current study, we isolated and evaluated exosomes from concurrently collected samples of milk, plasma, saliva, and urine from a group of 6 pregnant Holstein-Friesian dairy cows (aged 7 mo, 174 to 203 d of gestation). The cows had BCS of 3.5 to 5.25 (on a scale of 1 to 10), and the milk production for the season to the time of sampling ranged between 5,118 and 6,959 kg. The low levels of extracellular vesicles in saliva and urine (more than 86% fewer compared to the extracellular vesicles in milk and plasma) precluded further detailed evaluation since utility for diagnostics was deemed unlikely. In exosomes isolated from milk and plasma, size distribution, morphology, and the presence of exosome markers was confirmed by nanoparticle tracking analysis, electron microscopy, and Western blot. In addition, a targeted proteomic approach using the quadrupole ion trap mass spectrometer was also used in the study to screen for the exosome marker (e.g., Tumor susceptibility gene 101). Following confirmation of the presence of exosomes, the proteomic profiles of milk and plasma exosomes were evaluated using information-dependent acquisition-mediated liquid chromatography-tandem mass spectrometry (LC-MS/MS). The milk exosomes contain proteins that differed greatly from the plasma exosomes, with only 8 similar proteins harbored in both the milk and plasma exosomes. The milk and plasma exosomes were found to contain proteins (e.g., immunoglobulin J chain and α2 macroglobulin) associated with specific biological processes and molecular functions. Hence, the fluid of origin required for exosome analysis will be dependent on the specific information needed. In conclusion, isolated exosomes from milk and plasma samples collected at the same time point from the same dairy cows encapsulated different profiles of proteins associated with different biological processes and molecular functions.

Urine nitrogen (N) is the main source of N leaching from pasture grazed by dairy cows. The aim of this work was to compare urine-N excretion from lactating dairy cows under two contrasting farm systems (Future (F) and Current (C)). The farm systems differed in: annual N fertiliser inputs to the pasture (50 (F) and 150 (C) kg N ha(-1)); stocking rate (2.6 (F) vs. 3.2 (C) cows ha(-1)); and moving cows off pasture to a stand-off pad for 6 h per day in autumn (F). Continuous measurements of urine volume, time of urination and N concentration were made over three days in both early summer and in autumn using urine sensors.There was no difference between the two farm systems in average urine-N concentration (5.5. g N L-1) or urine volume (1.98 L) per urination, over the two sampling periods. There was a trend for more urinations per cow in F system (c. 14.8 vs. 13.5 cow(-1) day(-1), P=0.1), which was primarily attributed to greater feed intake per cow at the lower stocking rate. Estimated daily urine-N production per cow was unaffected by system (average c. 190 g N cow(-1) day(-1)). Despite no difference in urine-N excretion per cow, there was less urine-N deposited per ha in the lower N input F system (504 vs. 585 g N ha(-1) day(-1), P < 0.05). The reduction was due to less pasture consumed (and less N eaten) per ha in the F system. We conclude difference in stocking rate had a greater impact than the difference in feed intake per cow between the two systems. It was estimated that removing cows from the paddock for 6 h per day in autumn would reduce the daily amount of urinary-N deposited onto the paddock by c. 25%, allowing more N to be recycled as effluent. We would expect less N leaching as a result of less urine-N deposition in the F system arising from a combination of lower N inputs and removing cows for periods of the day. (C) 2016 Elsevier B.V. All rights reserved.

To investigate the potential to select for feed conversion efficiency in dairy cattle, we measured daily feed intake and body liveweight on 73 bull and 246 half sib heifer calves in a feeding trial using ad libitum Lucerne cube feed at the Westpac Taranaki Agricultural Research Station in Hawera, New Zealand. We measured feed consumption using automated systems, weighed all animals thrice weekly, and estimated residual feed intake (RFI) as the residual from a regression of daily dry matter intake (DMI) on average daily gain (ADG) and metabolic body weight (MBW 0.75 ). Using ASReml, we estimated the sex-specific additive genetic variances and heritabilities using univariate animal models as 0.05 and 0.13 ± 0.14 for the heifers, and 0.09 and 0.18 ± 0.57 for the young bulls. We also used a bivariate animal model that treated the RFI of the two sexes as different traits to estimate the genetic correlation between young bulls and heifers as 0.93 ± 1.46. Despite the high standard errors around the genetic parameter estimates due to small sample size, our results provide a preliminary indication that RFI is largely controlled by the same genes in both sexes and that genetic variation in RFI in Friesian dairy cattle is sufficient to support a response to selection in female relatives of elite young bulls.

Two DairyNZ farmlets, differing in nitrogen fertiliser inputs, cow genetic merit and autumn/winter grazing management, with stocking rates of 2.6 ('Future') and 3.2 ('Current') cows/ha, were compared for pasture residual and quality over 4 years. Target intakes for lactating cows were 18 and 16 kg DM/cow/day, respectively, with target grazing residuals of 3.5-4 cm (1500 kg DM/ha in late winter/spring, 7-8 clicks on the rising plate meter) for both herds. Measurement of grazing residuals, pasture quality and botanical composition identified small differences between farmlets. Grazing residuals on the Future farmlet averaged 0.2 cm (0.4 clicks on rising plate meter, RPM) (P

The effect of intensive agricultural systems on the environment is of increasing global concern, and recent review articles have highlighted the need for sustainable intensification of food production. In grazing dairy systems, the leaching of nitrate-N (NO3-N) to groundwater is a primary environmental concern. A herd-level factor considered by many to be a key contributor to the amount of NO3-N leached from dairy pastures is stocking rate (SR), and some countries have imposed limits to reduce the risk of NO3-N loss to groundwater. The objective of the current experiment was to determine the effect of dairy cow SR on NO3-N leached in a grazing system that did not import feed from off-farm and had the same N fertilizer input. Five SR were evaluated (2.2, 2.7, 3.1, 3.7, and 4.3 cows/ha) in a completely randomized design (i.e., 2 replicates of each SR as independent farmlets) over 2 y. Pasture utilization, milk production/hectare, and days in milk/hectare increased with SR, but days in milk/cow and milk production/cow declined. The concentration of NO3-N in drainage water and the quantity of NO3-N leached/ha per year declined linearly with increasing SR, and the operating profit/kg NO3-N leached per ha increased. Higher SR was associated with fewer days in milk/cow, resulting in a reduction in estimated urine N excretion/cow (the main source of N leaching) during the climatically sensitive period for NO3-N leaching (i.e., late summer to winter). We hypothesized that the reduction in estimated urine N excretion per cow led to an increase in urinary N spread and reduced losses from urine patches. The results presented indicate that lowering SR may not reduce nitrate leaching and highlight the need for a full farm system-level analysis of any management change to determine its effect on productivity and environmental outcomes.

Residual feed intake (RFI) is the difference between actual and predicted dry matter intake (DMI) of individual animals. Recent studies with Holstein-Friesian calves have identified an ~20% difference in RFI during growth (calf RFI) and these groups remained divergent in RFI during lactation. The objective of the experiment described here was to determine if cows selected for divergent RFI as calves differed in milk production, reproduction or in the profiles of BW and body condition score (BCS) change during lactation, when grazing pasture. The cows used in the experiment (n=126) had an RFI of -0.88 and +0.75 kg DM intake/day for growth as calves (efficient and inefficient calf RFI groups, respectively) and were intensively grazed at four stocking rates (SR) of 2.2, 2.6, 3.1 and 3.6 cows/ha on self-contained farmlets, over 3 years. Each SR treatment had equal number of cows identified as low and high calf RFI, with 24, 28, 34 and 40/11 ha farmlet. The cows divergent for calf RFI were randomly allocated to each SR. Although SR affected production, calf RFI group (low or high) did not affect milk production, reproduction, BW, BCS or changes in these parameters throughout lactation. The most efficient animals (low calf RFI) lost similar BW and BCS as the least efficient (high calf RFI) immediately post-calving, and regained similar BW and BCS before their next calving. These results indicate that selection for RFI as calves to increase efficiency of feed utilisation did not negatively affect farm productivity variables (milk production, BCS, BW and reproduction) as adults when managed under an intensive pastoral grazing system.

The GreenFeed (GF; C-lock Inc.) system for estimating methane (CH4) and carbon dioxide emissions from cows enables data to be acquired from a grazing herd, where individuals are unencumbered by equipment associated with sampling respired breath. Cows choose when or if they want to visit a GF. Confidence in CH4 measurements from this system requires information on individual cow use, patterns of visits and data need to be accumulated over several days or weeks. The effect of stocking rate (SR) on CH4 and carbon dioxide emissions was examined in herds of 28 and 40 dairy cows, each grazing an 11-ha self-contained farmlet (Low SR and High SR), in four measurement periods over a lactation. Emissions were measured for up to 3 weeks in each period; CH4 averaged 331 and 305 g/cow.day, with 19.6 and 16.5 kg milk/cow.day during the measurements for the Low and High SR, respectively. Values for CH4 were similar to estimates derived from calculated feed intakes, and daily carbon dioxide emissions averaged 10.8 and 10.0 kg/day for cows in Low and High SR treatments, respectively. Data from the GF system distinguished effects of SR, but only ~20 cows from each farmlet were regular (daily) users, despite feed restrictions for the High SR cows. Visits by ‘users’ averaged 1.6 and 1.1 cows/h for Low and High SR herds, respectively, and were spread over 24 h with a small circadian variation in emission rates. The GF can be integrated into intensive pasture-based dairying and estimates of CH4 emissions are in line with expectations associated with feed availability and stage of lactation, however the variation between cows in number of visits to the GF has not been explained.

With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in Holstein-Friesian dairy cattle, data from 10 research herds in Europe, North America, and Australasia were combined. The DMI records were available on 10,701 parity 1 to 5 records from 6,953 cows, as well as on 1,784 growing heifers. Predicted DMI at 70 d in milk was used as the phenotype for the lactating animals, and the average DMI measured during a 60- to 70-d test period at approximately 200 d of age was used as the phenotype for the growing heifers. After editing, there were 583,375 genetic markers obtained from either actual high-density single nucleotide polymorphism (SNP) genotypes or imputed from 54,001 marker SNP genotypes. Genetic correlations between the populations were estimated using genomic REML. The accuracy of genomic prediction was evaluated for the following scenarios: (1) within-country only, by fixing the correlations among populations to zero, (2) using near-unity correlations among populations and assuming the same trait in each population, and (3) a sharing data scenario using estimated genetic correlations among populations. For these 3 scenarios, the data set was divided into 10 sub-populations stratified by progeny group of sires; 9 of these sub-populations were used (in turn) for the genomic prediction and the tenth was used for calculation of the accuracy (correlation adjusted for heritability). A fourth scenario to quantify the benefit for countries that do not record DMI was investigated (i.e., having an entire country as the validation population and excluding this country in the development of the genomic predictions). The optimal scenario, which was sharing data, resulted in a mean prediction accuracy of 0.44, ranging from 0.37 (Denmark) to 0.54 (the Netherlands). Assuming near-unity among-country genetic correlations, the mean accuracy of prediction dropped to 0.40, and the mean within-country accuracy was 0.30. If no records were available in a country, the accuracy based on the other populations ranged from 0.23 to 0.53 for the milking cows, but were only 0.03 and 0.19 for Australian and New Zealand heifers, respectively; the overall mean prediction accuracy was 0.37. Therefore, there is a benefit in collaboration, because phenotypic information for DMI from other countries can be used to augment the accuracy of genomic evaluations of individual countries.

The aim of this study was to investigate and assess differences in the grazing pattern of 2 groups of mature dairy cows selected as calves for divergent residual feed intake (RFI). Sixteen Holstein-Friesian cows (471±31kg of body weight, 100 d in milk), comprising 8 cows selected as calves (6-8 mo old) for low (most efficient: CSCLowRFI) and 8 cows selected as calves for high (least efficient: CSCHighRFI) RFI, were used for the purpose of this study. Cows (n=16) were managed as a single group, and strip-grazed (24-h pasture allocation at 0800h) a perennial ryegrass sward for 31 d, with measurements taken during the last 21 d. All cows were equipped with motion sensors for the duration of the study, and jaw movements were measured for three 24-h periods during 3 random nonconsecutive days. Measurements included number of steps and jaw movements during grazing and rumination, plus fecal particle size distribution. Jaw movements were analyzed to identify bites, mastication (oral processing of ingesta) during grazing bouts, chewing during rumination, and to calculate grazing and rumination times for 24-h periods. Grazing and walking behavior were also analyzed in relation to the first meal of the day after the new pasture was allocated. Measured variables were subjected to multivariate analysis. Cows selected for low RFI as calves appeared to (a) prioritize grazing and rumination over idling; (b) take fewer steps, but with a higher proportion of grazing steps at the expense of nongrazing steps; and (c) increase the duration of the first meal and commenced their second meal earlier than CSCHighRFI. The CSCLowRFI had fewer jaw movements during eating (39,820 vs. 45,118 for CSCLowRFI and CSCHighRFI, respectively), more intense rumination (i.e., 5 more chews per bolus), and their feces had 30% less large particles than CSCHighRFI. These results suggest that CSCLowRFI concentrate their grazing activity to the time when fresh pasture is allocated, and graze more efficiently by walking and masticating less, hence they are more efficient grazers than CSCHighRFI.

Dairy heifer growth and liveweight at first calving are regarded as important management variables affecting profitability and animal welfare. However, the appropriateness of heifer growth rate targets for different farming systems is not clear. Retrospective assessments of the association between heifer liveweight and subsequent productivity indicate significant benefits in milk production and, even, reproduction from increasing liveweight at breeding and first calving. However, prospective interventionist experiments do not concur, with very variable effects of liveweight at breeding on milk production and with only limited evidence of a positive effect of first-calving liveweight on first-lactation milk yield. In addition, any benefit in the first lactation is not evident in subsequent lactations in the limited number of long-term studies reported. Pre-weaning nutrition and average daily weight gain are areas of increasing interest, with lifelong increases in milk production resulting from accelerated growth rates during the first 8 weeks of life, indicating a possible significant return from a short-term investment. This could be one reason for the inconsistent effects of heifer liveweight at breeding and first lactation on milk production. Although the effect of pre-weaning average daily gain on heifer liveweight is short-lived, a recent meta-analysis indicated that pre-weaning average daily gain explains 22% of the variation in first-lactation milk production. Whether these differences in animal physiology have relevance in grazing systems, wherein heifers and cows do not consume sufficient nutrients to reach their potential, requires investigation. Despite considerable extension efforts over successive decades, current evidence indicates that failure to provide the new-born calf with sufficient high-quality colostrum is common. To understand the reasons for suboptimal colostrum feeding requires social research, with appropriate extension strategies developed to elicit practice change. Although there can be little doubt regarding the importance of heifer rearing to the profitability and sustainability of the farming business, the collective literature points to a failure of retrospective analyses in determining the cause of poor heifer performance. In reality, it is likely to be a combination of factors. The objective of this review is to investigate the effect of liveweight gain at various stages of the growth cycle of the heifer on the milk-production capacity of the lactating animal.

Calving body condition score (BCS) is an important determinant of early-lactation dry matter intake, milk yield, and disease incidence. The current study investigated the metabolic and molecular changes induced by the change in BCS. A group of cows of mixed age and breed were managed from the second half of the previous lactation to achieve mean group BCS (10-point scale) that were high (HBCS, 5.5; n=20), medium (MBCS, 4.5; n=18), or low (LBCS, 3.5; n=19). Blood was sampled at wk -4, -3, -2, 1, 3, 5, and 6 relative to parturition to measure biomarkers of energy balance, inflammation, and liver function. Liver was biopsied on wk 1, 3, and 5 relative to parturition, and 10 cows per BCS group were used for transcript profiling via quantitative PCR. Cows in HBCS and MBCS produced more milk and had greater concentrations of nonesterified fatty acids and β-hydroxybutyrate postpartum than LBCS. Peak concentrations of nonesterified fatty acids and β-hydroxybutyrate and greater hepatic triacylglycerol concentrations were recorded in HBCS at wk 3. Consistent with blood biomarkers, HBCS and MBCS had greater expression of genes associated with fatty acid oxidation (CPT1A, ACOX1), ketogenesis (HMGCS2), and hepatokines (FGF21, ANGPTL4), whereas HBCS had the lowest expression of APOB (lipoprotein transport). Greater expression during early lactation of BBOX1 in MBCS and LBCS suggested greater de novo carnitine synthesis. The greater BCS was associated with lower expression of growth hormone/insulin-like growth factor-1 signaling axis genes (GHR1A, IGF1, and IGFALS) and greater expression of gluconeogenic genes. These likely contributed to the higher milk production and greater gluconeogenesis. Despite greater serum haptoglobin around calving, cows in HBCS and MBCS had greater blood albumin. Cows in MBCS, however, had a higher albumin:globulin ratio, probably indicating a less pronounced inflammatory status and better liver function. The marked decrease in expression of NFKB1, STAT3, HP, and SAA3 coupled with the increase in ALB on wk 3 in MBCS cows were consistent with blood measures. Overall, results suggest that the greater milk production of cows with higher calving BCS is associated with a proinflammatory response without negatively affecting expression of genes related to metabolism and the growth hormone/insulin-like growth factor-1 axis. Results highlight the sensitivity of indicators of metabolic health and inflammatory state to subtle changes in calving BCS and, collectively, indicate a suboptimal health status in cows calving at either BCS 3.5 or 5.5 relative to BCS 4.5.