Short communication: Evaluation of an eating time sensor for use in pasture-based dairy systems.

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.

Short communication: Milk fat payment affects the relative profitability of Jersey and Holstein-Friesian cows at optimal comparative stocking rate.

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.

Hot topic: Selecting cattle for low residual feed intake did not affect daily methane production but increased methane yield.

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.

A quantitative case study assessment of biophysical and economic effects from altering season of calving in temperate pasture-based dairy systems.

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.

Dairy cow breed interacts with stocking rate in temperate pasture-based dairy production systems.

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.

Production and economic responses to intensification of pasture-based dairy production systems.

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.

A 100-Year Review: A century of change in temperate grazing dairy systems.

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.

Increased stocking rate and associated strategic dry-off decision rules reduced the amount of nitrate-N leached under grazing.

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.

Short communication: grazing pattern of dairy cows that were selected for divergent residual feed intake as calves.

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.

Genomic prediction of dry matter intake in dairy cattle from an international data set consisting of research herds in Europe, North America, and Australasia.

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.

Residual feed intake of lactating Holstein-Friesian cows predicted from high-density genotypes and phenotyping of growing heifers.

A genomic prediction for residual feed intake (RFI) developed in growing dairy heifers (RFIgro) was used to predict and test breeding values for RFI in lactating cows (RFIlac) from an independent, industry population. A selection of 3,359 cows, in their third or fourth lactation during the study, of above average genetic merit for milk production, and identified as at least 15/16ths Holstein-Friesian breed, were selected for genotyping from commercial dairy herds. Genotyping was carried out using the bovine SNP50 BeadChip (Illumina Inc., San Diego, CA) on DNA extracted from ear-punch tissue. After quality control criteria were applied, genotypes were imputed to the 624,930 single nucleotide polymorphisms used in the growth study. Using these data, genomically estimated breeding values (GEBV) for RFIgro were calculated in the selected cow population based on a genomic prediction for RFIgro estimated in an independent group of growing heifers. Cows were ranked by GEBV and the top and bottom 310 identified for possible purchase. Purchased cows (n=214) were relocated to research facilities and intake and body weight (BW) measurements were undertaken in 99 "high" and 98 "low" RFIgro animals in 4 consecutive groups [beginning at d 61 ± 1.0 standard error (SE), 91 ± 0.5 SE, 145 ± 1.3 SE, and 191 ± 1.5 SE d in milk, respectively] to measure RFI during lactation (RFIlac). Each group of ~50 cows (~25 high and ~25 low RFIgro) was in a feed intake facility for 35 d, fed pasture-alfalfa cubes ad libitum, milked twice daily, and weighed every 2 to 3 d. Milk composition was determined 3 times weekly. Body weight change and BW at trial mid-point were estimated by regression of pre- and posttrial BW measurements. Residual feed intake in lactating cows was estimated from a linear model including BW, BW change, and milk component yield (as MJ/d); RFIlac differed consistently between the high and low selection classes, with the overall means for RFIlac being +0.32 and -0.31 kg of dry matter (DM) per day for the high and low classes, respectively. Further, we found evidence of sire differences for RFIlac, with one sire, in particular, being highly represented in the low RFIgro class, having a mean RFIlac of -0.83 kg of DM per day in 47 daughters. In conclusion, genomic prediction of RFIgro based on RFI measured during growth will discriminate for RFIlac in an independent group of lactating cows.

Evaluation of selective dry cow treatment following on-farm culture: risk of postcalving intramammary infection and clinical mastitis in the subsequent lactation.

The objective of the study was to evaluate the utility of a Petrifilm-based on-farm culture system when used to make selective antimicrobial treatment decisions on low somatic cell count cows (<200,000 cells/mL) at drying off. A total of 729 cows from 16 commercial dairy herds with a low bulk tank somatic cell count (<250,000 cells/mL) were randomly assigned to receive either blanket dry cow therapy (DCT) or Petrifilm-based selective DCT. Cows belonging to the blanket DCT group were infused with a commercial dry cow antimicrobial product and an internal teat sealant (ITS) at drying off. Using composite milk samples collected on the day before drying off, cows in the selective DCT group were treated at drying off based on the results obtained by the Petrifilm on-farm culture system with DCT + ITS (Petrifilm culture positive), or ITS alone (Petrifilm culture negative). Quarters of all cows were sampled for standard laboratory bacteriology on the day before drying off, at 3 to 4d in milk (DIM), at 5 to 18 DIM, and from the first case of clinical mastitis occurring within 120 DIM. Multilevel logistic regression was used to assess the effect of study group (blanket or selective DCT) and resulting dry cow treatment (DCT + ITS, or ITS alone) on the risk of intramammary infection (IMI) at calving and the risk of a first case of clinical mastitis between calving and 120 DIM. According to univariable analysis, no difference was observed between study groups with respect to quarter-level cure risk and new IMI risk over the dry period. Likewise, the risk of IMI at calving and the risk of clinical mastitis in the first 120 DIM was not different between quarters belonging to cows in the blanket DCT group and quarters belonging to cows in the selective DCT group. The results of this study indicate that selective DCT based on results obtained by the Petrifilm on-farm culture system achieved the same level of success with respect to treatment and prevention of IMI over the dry period as blanket DCT and did not affect the risk of clinical mastitis in the first 120 d of the subsequent lactation.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user.

Holstein-Friesian calves selected for divergence in residual feed intake during growth exhibited significant but reduced residual feed intake divergence in their first lactation.

Residual feed intake (RFI), as a measure of feed conversion during growth, was estimated for around 2,000 growing Holstein-Friesian heifer calves aged 6 to 9 mo in New Zealand and Australia, and individuals from the most and least efficient deciles (low and high RFI phenotypes) were retained. These animals (78 New Zealand cows, 105 Australian cows) were reevaluated during their first lactation to determine if divergence for RFI observed during growth was maintained during lactation. Mean daily body weight (BW) gain during assessment as calves had been 0.86 and 1.15 kg for the respective countries, and the divergence in RFI between most and least efficient deciles for growth was 21% (1.39 and 1.42 kg of dry matter, for New Zealand and Australia, respectively). At the commencement of evaluation during lactation, the cows were aged 26 to 29 mo. All were fed alfalfa and grass cubes; it was the sole diet in New Zealand, whereas 6 kg of crushed wheat/d was also fed in Australia. Measurements of RFI during lactation occurred for 34 to 37 d with measurements of milk production (daily), milk composition (2 to 3 times per week), BW and BW change (1 to 3 times per week), as well as body condition score (BCS). Daily milk production averaged 13.8 kg for New Zealand cows and 20.0 kg in Australia. No statistically significant differences were observed between calf RFI decile groups for dry matter intake, milk production, BW change, or BCS; however a significant difference was noted between groups for lactating RFI. Residual feed intake was about 3% lower for lactating cows identified as most efficient as growing calves, and no negative effects on production were observed. These results support the hypothesis that calves divergent for RFI during growth are also divergent for RFI when lactating. The causes for this reduced divergence need to be investigated to ensure that genetic selection programs based on low RFI (better efficiency) are robust.

Relationships between residual feed intake, average daily gain, and feeding behavior in growing dairy heifers.

Residual feed intake (RFI) is a measure of an individual's efficiency in utilizing feed for maintenance and production during growth or lactation, and is defined as the difference between the actual and predicted feed intake of that individual. The objective of this study was to relate RFI to feeding behavior and to identify behavioral differences between animals with divergent RFI. The intakes and body weight (BW) of 1,049 growing dairy heifers (aged 5-9 mo; 195 ± 25.8 kg of BW) in 5 cohorts were measured for 42 to 49 d to ascertain individual RFI. Animals were housed in an outdoor feeding facility comprising 28 pens, each with 8 animals and 1 feeder per pen, and were fed a dried, cubed alfalfa diet. This forage diet was chosen because most dairy cows in New Zealand are grazed on ryegrass-dominant pastures, without grain or concentrates. An electronic feed monitoring system measured the intake and feeding behavior of individuals. Feeding behavior was summarized as daily intake, daily feeding duration, meal frequency, feeding rate, meal size, meal duration, and temporal feeding patterns. The RFI was moderately to strongly correlated with intake in all cohorts (r=0.54-0.74), indicating that efficient animals ate less than inefficient animals, but relationships with feeding behavior traits (meal frequency, feeding duration, and feeding rate) were weak (r=0.14-0.26), indicating that feeding behavior cannot reliably predict RFI in growing dairy heifers. Comparison of the extremes of RFI (10% most and 10% least efficient) demonstrated similar BW and average daily gain for both groups, but efficient animals ate less; had fewer, longer meals; shorter daily feeding duration; and ate more slowly than the least-efficient animals. These groups also differed in their feeding patterns over 24h, with the most efficient animals eating less and having fewer meals during daylight (0600 to 2100 h), especially during the afternoon (1200 to 1800 h), but ate for a longer time during the night (0000-0600 h) than the least-efficient animals. In summary, correlations between RFI and feeding behavior were weak. Small differences in feeding behavior were observed between the most- and least-efficient animals but adverse behavioral effects associated with such selection in growing dairy heifers are unlikely.

Behavioral and physiological effects of a short-term feed restriction in lactating dairy cattle with different body condition scores at calving.

Body condition score (BCS) around calving, and the typical BCS loss for up to 100 d after parturition, is associated with both production and reproductive performance of dairy cattle. In addition, there is public concern that thin cows may have impaired welfare, particularly in early lactation where feed demand exceeds pasture growth, and a lag exists between peak milk energy requirements and intake. The aim of this experiment was to determine how BCS at calving influences behavioral and physiological responses to a short-term feed restriction at 47 DIM. Body condition score (on a 10-point scale) at calving was manipulated by modifying the diets in the previous lactation of healthy dairy cattle to generate 3 treatment groups: low BCS (3.4; n=17), medium BCS (4.6; n=18), or high BCS (5.4; n=20). Cows were tested in 4 groups for 8 consecutive days; testing consisted of different levels of feed allocation (d 1 and 2: 100%; d 3 and 4: 75%; d 5: 50%; d 6 to 8: 125%), where 100% was 15kg of DM/cow per day. All BCS groups had similar and marked behavioral and physiological responses to feed restriction. For example, they increased vocalization, time spent eating silage and grazing, aggressive behavior, and fat metabolism (as measured by concentrations of ß-hydroxybutyrate and nonesterified fatty acids), and reduced milk production. Body condition affected some of these responses. Fewer cows with low BCS engaged in aggressive interactions in a feed competition test (trough filled with silage that could be consumed in 15 min) on the first day of feed restriction (low: 32%; medium: 74%; high: 64%; standard error of difference=15.4%). High BCS cows had greater concentrations of ß-hydroxybutyrate and nonesterified fatty acids throughout the experimental period, which suggests more fat mobilization; however, plasma leptin and fecal glucocorticosteroid metabolite concentrations were unaffected by BCS. Whereas cows demonstrated marked responses to feed restriction, the results suggest that a BCS of 3.4, 4.6, or 5.4 in healthy cows at calving does not overwhelmingly influence this response at 47 DIM.

Calving body condition score affects indicators of health in grazing dairy cows.

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 ß-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 ß-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.

Measuring residual feed intake in dairy heifers fed an alfalfa (Medicago sativa) cube diet.

Selection for divergence between individuals for efficiency of feed utilization (residual feed intake, RFI) has widespread application in the beef industry and is usually undertaken when animals are fed diets based on silages with grain. The objective of this research was to develop a feeding system (using Gallagher, Hamilton, New Zealand, electronics) to measure RFI for growth in Holstein-Friesian heifers (aged 5-9 mo), and identify divergent individuals to be tested for RFI during lactation. A dry forage diet (alfalfa cubes) was fed because intakes could be measured accurately, and the New Zealand dairy industry (4.4 million milking cows in lactation) relies heavily on forage feeding. The evaluation was undertaken over 3 yr with 1,052 animals fed in a facility for 7 wk, and weighed 3 times weekly. The mean age at the start of measurements was 215 d, body weight (BW) 189 kg, and mean daily dry matter intakes averaged 6.7 kg. Body weight gain (all animals) averaged 0.88 kg/d. The RFI was determined as the residuals from the regression of mean intake on mean BW(0.75) and daily BW gain of individuals. Actual and fitted intakes were strongly related (R(2) = 0.82). In terms of gross efficiency (feed intake/BW gain), RFI+year explained 43% of the variation, BW gain+year explained 66%, and RFI+BW gain+year explained 79% of the variation (all P<0.001). Daily BW gains (kg) of the most and least efficient 10% averaged (± standard deviation) 0.88 ± 0.15 and 0.88 ± 0.12 (P = 0.568), respectively, and the divergence between mean intakes was 1.46 kg of dry matter/d. The most and least efficient animals will be tested for RFI during lactation and genetic markers will be identified for the trait.

Nitrogen metabolism and rumen microbial enumeration in lactating cows with divergent residual feed intake fed high-digestibility pasture.

Dairy cattle selected for negative residual feed intake (n-RFI; efficient) should maintain production while reducing dry matter intake over a lactation because of improvements in feed digestion and efficient use of nutrients. The objective of this study was to measure nitrogen (N) digestibility and rumen microbial community composition over a short period during early lactation in lactating Holstein-Friesian cows selected previously for divergent RFI. It was proposed that n-RFI cows would have greater apparent digestibility of N than the positive RFI (p-RFI; inefficient) animals, to compensate for the lower dry matter intake determined during selection for divergence. Sixteen 3-yr-old rumen-cannulated, lactating cows (56 ± 10d in milk) selected for n-RFI (n = 8) and p-RFI (n = 8) were housed in metabolism stalls and fed fresh vegetative ryegrass (Lolium perenne L.) pasture ad libitum as a sole diet during an 8-d digestibility study. Intake of nutrients and outputs of milk, feces, and urine were determined. Rumen parameters were determined by removing, weighing, and sampling digesta, and by cobalt-EDTA dilution. Intakes of N, dry matter, organic matter, or its components did not differ with RFI. Compared with p-RFI cows, n-RFI cows had a greater apparent N digestibility (77.2 vs. 75.5%), and a tendency toward greater dry matter and organic matter digestibilities. The n-RFI cows had a lower fecal N output (126 vs. 138 g/d) and a lower partition of feed N to fecal N (23.1 vs. 24.7%) compared with p-RFI animals. We found no differences between phenotypes in the partition of N to urinary N or milk crude protein but did observe a trend for n-RFI cows to partition less N to milk casein (16.8 vs. 17.9%). Rumen digesta mass was similar for both groups, despite differences in calculated fractional liquid outflow rates, and most bacterial, archaeal, protozoal, and fungal communities were similar for both phenotype groups. In conclusion, dry matter intake and rumen function were similar for both phenotypes when the animals were fed highly digestible fresh ryegrass, but apparent digestibility of dietary N was higher in the efficient (n-RFI) cows. Future research should measure digestion parameters in cows with divergent RFI when fed diets differing in chemical composition (e.g., divergent crude protein contents).

Accuracy of genomic predictions of residual feed intake and 250-day body weight in growing heifers using 625,000 single nucleotide polymorphism markers.

Feed makes up a large proportion of variable costs in dairying. For this reason, selection for traits associated with feed conversion efficiency should lead to greater profitability of dairying. Residual feed intake (RFI) is the difference between actual and predicted feed intakes and is a useful selection criterion for greater feed efficiency. However, measuring individual feed intakes on a large scale is prohibitively expensive. A panel of DNA markers explaining genetic variation in this trait would enable cost-effective genomic selection for this trait. With the aim of enabling genomic selection for RFI, we used data from almost 2,000 heifers measured for growth rate and feed intake in Australia (AU) and New Zealand (NZ) genotyped for 625,000 single nucleotide polymorphism (SNP) markers. Substantial variation in RFI and 250-d body weight (BW250) was demonstrated. Heritabilities of RFI and BW250 estimated using genomic relationships among the heifers were 0.22 and 0.28 in AU heifers and 0.38 and 0.44 in NZ heifers, respectively. Genomic breeding values for RFI and BW250 were derived using genomic BLUP and 2 bayesian methods (BayesA, BayesMulti). The accuracies of genomic breeding values for RFI were evaluated using cross-validation. When 624,930 SNP were used to derive the prediction equation, the accuracies averaged 0.37 and 0.31 for RFI in AU and NZ validation data sets, respectively, and 0.40 and 0.25 for BW250 in AU and NZ, respectively. The greatest advantage of using the full 624,930 SNP over a reduced panel of 36,673 SNP (the widely used BovineSNP50 array) was when the reference population included only animals from either the AU or the NZ experiment. Finally, the bayesian methods were also used for quantitative trait loci detection. On chromosome 14 at around 25 Mb, several SNP closest to PLAG1 (a gene believed to affect stature in humans and cattle) had an effect on BW250 in both AU and NZ populations. In addition, 8 SNP with large effects on RFI were located on chromosome 14 at around 35.7 Mb. These SNP may be associated with the gene NCOA2, which has a role in controlling energy metabolism.