RSS 1.0Livestock Systems
Moorepark is one of the world's leading dairy research centres and specialises in pasture based systems of milk production.Research at Moorepark endeavours to anticipate the production needs of a rapidly changing industry and develop sustainable systems of milk production that will advance the competitive edge of Irish dairy farmers on the global market. Grange Animal & Grassland Research and Innovation Centre is the national Beef Research Centre which provides research information on all aspects of beef production in Ireland. Research at Grange supports the efficient production of safe, quality, healthy produce, in profitable production systems that meet stringent environmental and animal welfare standards. The Athenry Animal & Grassland Research and Innovation Centre, located in Co. Galway,provides national research services in sheep production and animal reproduction.
Recent Submissions
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Annual electricity consumption prediction and future expansion analysis on dairy farms using a support vector machineThis study utilised a previously developed support vector machine (SVM) (trained using empirical data from 56 dairy farms) for predicting and analysing annual dairy farm electricity consumption to help improve the sustainability of the projected expansion of milk production in Ireland. Firstly, the capability of the SVM to predict annual electricity consumption was investigated at both a farm and catchment-level (combined consumption). Electricity consumption data were attained from 16 pasture-based, Irish dairy farms between June 2016 and May 2017 in conjunction with farm data related to herd size, milk production, infrastructural equipment and managerial tendencies, required to generate predictions using the SVM. The SVM predicted annual electricity consumption of dairy farms to within 10.4% (relative prediction error). Concurrently, catchment-level electricity consumption was predicted with an error value less than 5.0%. Secondly, an investigation was carried out to assess the impact of increasing herd size and milk production on dairy farm related electricity consumption at a catchment-level across ten hypothetical infrastructural scenarios. The dairy expansion analysis showed electricity economies of scale across all ten infrastructural scenarios. The greatest reduction in electricity consumption per litre was observed when all farms employed ground water for pre-cooling milk with two additional parlour units, reducing by 4% in 2018, relative to a base scenario (no change to infrastructural equipment). The results presented in this article demonstrate the potential effectiveness of the SVM as a macro-level simulation forecast tool for dairy farm electricity consumption that may be used to quantify the impact of milk production on electricity resources, or to offer decision support to dairy farmers.
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A Global Review of Monitoring, Modeling, and Analyses of Water Demand in Dairy FarmingThe production of milk must be balanced with the sustainable consumption of water resources to ensure the future sustainability of the global dairy industry. Thus, this review article aimed to collate and summarize the literature in the dairy water-usage domain. While green water use (e.g., rainfall) was found to be largest category of water use on both stall and pasture-based dairy farms, on-farm blue water (i.e., freshwater) may be much more susceptible to local water shortages due to the nature of its localized supply through rivers, lakes, or groundwater aquifers. Research related to freshwater use on dairy farms has focused on monitoring, modeling, and analyzing the parlor water use and free water intake of dairy cows. Parlor water use depends upon factors related to milk precooling, farm size, milking systems, farming systems, and washing practices. Dry matter intake is a prominent variable in explaining free water intake variability; however, due to the unavailability of accurate data, some studies have reported moving away from dry matter intake at the expense of prediction accuracy. Machine-learning algorithms have been shown to improve dairy water-prediction accuracy by 23%, which may allow for coarse model inputs without reducing accuracy. Accurate models of on-farm water use allow for an increased number of dairy farms to be used in water footprinting studies, as the need for physical metering equipment is mitigated.
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Responses in lactose yield, lactose percentage and protein-to-protein-plus-lactose ratio from index selection in New Zealand dairy cattleThe breeding goal of the New Zealand dairy industry is to improve the genetic capability of cows to convert pasture-based feed into farmer profit. The New Zealand dairy industry exports over 95% of milk produced and the most significant product by export volume is whole milk powder (WMP). The current selection objective, breeding worth (BW), will increase yields of protein and fat, potentially shifting milk composition further from the ideal composition for making WMP. This study aimed to investigate the correlated responses in lactose yield (LY), lactose percentage (LP) and protein-to-protein-plus-lactose ratio (P:P + L) from selection for BW, BW plus LY, BW plus LP and BW plus P:P + L. Selection for BW is predicted to have per-cow responses of 54.92 kg milk/year, 2.22 kg fat/year, 1.78 kg protein/year and 2.84 kg lactose/year. When lactose was included in the selection objective in the form of LY, LP or P:P + L, genetic responses ranged from −59.98 kg to 61.08 kg milk/year and from −2.67 kg to 3.70 kg lactose/year. The industry could reduce imported lactose requirements per tonne of WMP by 6%–11% by including lactose into the selection objective, compared with selection on BW alone.
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Effect of mechanical premilking stimulation on milking duration in late lactationThis study documents the effect of mechanical prestimulation on the milking duration of pasture-based cows in late lactation to better harness increased capacity of automation in the milk harvesting process. Premilking stimulation, provided via manual or mechanical means, has been shown to promote the milk letdown reflex and assist in achieving quick, comfortable, and complete milk removal from the udder. The literature is lacking knowledge on the effect of mechanical premilking stimulation on milking duration, especially in late lactation and in pasture-based systems, and many pasture-based farms do not practice a full premilking routine because of a lack of labor availability. The current study addresses this gap in knowledge. In this study, we tested 2 treatments: (1) the No Stim treatment used normal farm milking settings with no premilking preparation and (2) the Stim treatment used 60 s of mechanical premilking stimulation, with a rate of 120 cycles per minute and a pulsator ratio of 30:70 on cluster attachment. Once the 60 s of stimulation had elapsed, normal milking settings resumed for the remainder of the milking. Sixty cows were enrolled in the study, which ran for 20 d. The effect of treatment on a.m. milking duration was significant, a.m. milking duration for Stim was 12 s shorter than that of No Stim. The effect of treatment on p.m. milk duration was not significant. Treatment had no effect on a.m./p.m. milk yields, average milk flowrates or peak milk flowrates. Significant differences emerged between treatments on a.m. and p.m. dead time (time from cluster attachment to reach a milk flowrate of 0.2 kg/min). The a.m. and p.m. dead times were 6 s shorter for Stim compared with No Stim. The time taken to achieve peak milk flowrate (time to peak) at morning milking was 7 s shorter for Stim compared with No Stim, and treatment yielded no significant effects on time to peak at p.m. milkings. Treatment also had no significant effect on log10 somatic cell count. Although the percentage of congested teat-ends and teat-barrels was numerically lower for Stim versus No Stim, no statistical differences were detected across these measures. Based on the results of the study, we found merit in applying 60 s of mechanical pre-stimulation at a.m. milking from a milking duration perspective. However, the strategy was not as successful for the p.m. milking. Analysis of the milk flowrate profiles recorded during the study suggest potential utility in employing different machine settings for various milkings based on anticipated yield and level of udder fill.
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The effect of fertilizer nitrogen input to grass-clover swards and calving date on the productivity of pasture-based dairy productionThe objective of this systems-scale study was to investigate grazing season timeframes on pasture and milk production and on milk processability of dairy systems with compact spring-calving dairy cows grazing white clover (Trifolium repens L.) based grassland. Fifty-four primiparous and multiparous Holstein-Friesian dairy cows were used in a one-factor study with 3 systems (n = 18) and repeated over 2 yr (2008/09 and 2009/10). The 3 systems were: early spring calving with annual fertilizer N input of 100 kg·ha−1 applied in spring (ES100N; 2.1 cows·ha−1; grazing February to November), early spring calving without fertilizer N (ES0N; 1.6 cows·ha−1; grazing February to November) and late spring calving without fertilizer N (LS0N; 1.53 cows·ha−1; grazing April to January). Annual pasture production was affected by an interaction between grazing system and year: Mean annual pasture yields for 2008 and 2009 were ES100N; 10.35 and 9.88, ES0N; 8.88 and 8.63, LS0N; 9.18 and 10.31 t of dry matter (DM)·ha−1 (SEM 0.39). LS0N had higher pasture DM yield in 2009 due to higher clover DM production and biological N fixation compared with the other systems. Clover stolon and root mass in the following February was correlated with stolon and root mass in the previous November with 64% of stolon mass present on LS0N in February (R2 = 0.84). There were no detectable differences in per-lactation milk yield (6,335 kg·cow−1), fat, protein and lactose yields (271, 226, 297 kg·cow−1, respectively), cow liveweight (585 kg) or body condition score (3.02). Although winter grazing favored subsequent clover DM production, biological N fixation and pasture DM production, delaying calving date in spring and extending lactation into the following winter led to inefficient use of this pasture by the grazing herd and lowered the quality of late-lactation milk for processing purposes. Hence, a mean calving date in mid- to late-February is recommended for zero-fertilizer N input clover-based grassland.
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Invited review: A 2020 perspective on pasture-based dairy systems and productsGrazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as “grass-fed” milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.
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Effects of substrate stress and light intensity on enhanced biological phosphorus removal in a photo-activated sludge systemPhoto-activated sludge (PAS) systems are an emerging wastewater treatment technology where microalgae provide oxygen to bacteria without the need for external aeration. There is limited knowledge on the optimal conditions for enhanced biological phosphorus removal (EBPR) in systems containing a mixture of polyphosphate accumulating organisms (PAOs) and microalgae. This research aimed to study the effects of substrate composition and light intensity on the performance of a laboratory-scale EBPR-PAS system. Initially, a model-based design was developed to study the effect of organic carbon (COD), inorganic carbon (HCO3) and ammonium-nitrogen (NH4-N) in nitrification deprived conditions on phosphorus (P) removal. Based on the mathematical model, two different synthetic wastewater compositions (COD:HCO3:NH4-N: 10:20:1 and 10:10:4) were examined at a light intensity of 350 µmol m−2 sec−1. Add to this, the performance of the system was also investigated at light intensities: 87.5, 175, and 262.5 µmol m−2 sec−1 for short terms. Results showed that wastewater having a high level of HCO3 and low level of NH4-N (ratio of 10:20:1) favored only microalgal growth, and had poor P removal due to a shortage of NH4-N for PAOs growth. However, lowering the HCO3 level and increasing the NH4-N level (ratio of 10:10:4) balanced PAOs and microalgae symbiosis, and had a positive influence on P removal. Under this mode of operation, the system was able to operate without external aeration and achieved a net P removal of 10.33 ±1.45 mg L−1 at an influent COD of 100 mg L−1. No significant variation was observed in the reactor performance for different light intensities, indicating the EBPR-PAS system can be operated at low light intensities with a positive influence on P removal.
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Greenhouse gas emissions and nitrogen efficiency of dairy cows of divergent economic breeding index under seasonal pasture-based managementGreenhouse gas (GHG) emissions and nitrogen (N) efficiencies were modeled for 2 genetic groups (GG) of Holstein-Friesian cows across 3 contrasting feeding treatments (FT). The 2 GG were (1) high economic breeding index (EBI) animals representative of the top 5% of cows nationally (elite) and (2) EBI representative of the national average (NA). The FT represented (1) generous feeding of pasture, (2) a slight restriction in pasture allowance, and (3) a high-concentrate feeding system with adequate pasture allowance. Greenhouse gas and N balance models were parameterized using outputs generated from the Moorepark Dairy Systems model, a stochastic budgetary simulation model, having integrated biological data pertaining to the 6 scenarios (2 GG × 3 FT) obtained from a 4-yr experiment conducted between 2013 and 2016. On a per hectare basis, total system GHG emissions were similar for both elite and NA across the 3 FT. Per unit of product, however, the elite group had 10% and 11% lower GHG emissions per kilogram of fat- and protein-corrected milk and per kilogram of milk solids (MSO; fat + protein kg), respectively, compared with the NA across the 3 FT. The FT incorporating high concentrate supplementation had greater absolute GHG emissions per hectare as well as GHG per kilogram of fat- and protein-corrected milk and MSO. The elite group had a slightly superior N use efficiency (N output/N input) and lower N surplus (N input – N output) compared with the NA group. The high concentrate FT had an inferior N use efficiency and a higher N surplus. The results of the current study demonstrate that breeding for increased EBI will lead to a general improvement in GHG emissions per unit of product as well as improved N efficiency. The results also illustrate that reducing concentrate supplementation will reduce GHG emissions, GHG emissions intensity, while improving N efficiency in the context of pasture-based dairy production.
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Evaluation of the contribution of 16 European beef production systems to food securityContext Livestock production, and more particularly ruminants, is criticized for its low conversion efficiency of natural resources into edible food. Objective The objectives of this paper are to propose an evaluation of the contribution to food security of different European cattle farms through three criteria: 1) food production assessed by the amount of human-edible protein (HEP) and energy (HEE) produced at farm level, 2) feed-food competition at the beef production scale estimated in terms of net human-edible protein and energy and in terms of land used, and 3) food affordability assessed by the production cost of meat, protein and energy. Methods The analysis is based on 16 representative beef production systems in France, Belgium, Ireland, Italy and Germany and covers cow-calf systems, finishing systems, dairy and mixed dairy- finishing systems, with or without cash crops. Results and conclusions The results show that, at the farm level, systems producing both beef and milk or cereals have higher HEP and HEE production per hectare (up to 370 kg of HEP and 60,000 106J.ha−1) than specialized beef systems (up to 50 kg of HEP and 1600 106J.ha−1) and have lower production costs (approximately €6 kg−1 of HEP in mixed beef system and €29 kg−1 of HEP in a specialized cow-calf-fattener system). Beef systems are almost all HEE net consumers. Results are more variable concerning net HEP efficiency. The cow-calf enterprises are mostly net producers of HEP but, in order to produce human edible meat, these systems need to be combined with finishing systems that are mostly net consumers of HEP. In most cases, cow-calf-finishing systems are net consumers of HEP (between 0.6 and 0.7) but grass-based systems using very little concentrates or systems using co-products not edible by humans are net HEP producers. The grass-based systems use more land area per kilogram of carcass but a major part of this area is non-tilled land, thus these systems are not in direct competition with human food production. The lowest meat production costs are the finishing systems producing the most live weight per livestock unit (LU) per year and dairy systems in lowland which share the costs between milk and meat. Significance Although most of HEE and HEP efficient farms typically have higher meat production costs, some grassland based systems stand out positively for all indicators. These results pave the way for improvements of the contribution of beef production systems to food security. Graphical abstract Net Human Edible Protein and Energy Efficiencies of meat production (M_HEP_eff and M_HEE_eff).
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Short communication: Increasing the teatcup removal settings of the last milking quarter did not reduce box time in a pasture-based automatic milking systemThis research followed our previous experimental and simulation work on the effect of different teatcup removal settings based on the rolling average milk flowrate and on milking duration at the quarter and udder levels. The aims of this experiment were to (1) quantify the differences in quarter milking duration in a pasture-based automatic milking system and (2) test the effect of increasing the milk flowrate at which teatcups are removed on the last milking quarter on udder milking duration, box time, milk production rate, and somatic cell count (SCC). Milking duration is an important component of efficiency and profitability in conventional and automatic milking systems. Additionally, quarters within an udder have significantly different milk yields and milking durations. This study used data from April to May 2018 of a pasture-based automatic milking system to evaluate quarter milking duration differences between quarters of an udder. Subsequently, we experimentally evaluated the use of 2 percentage-based teatcup removal settings applied to the last milking quarter (i.e., the last quarter with a teatcup still attached) on milking duration, box time, milk production rate, and SCC. The teatcup removal settings were at 30 or 50% of the last quarter's rolling average milk flowrate, while the other quarters remained at the 30% level. The selection of the quarter that would receive the more aggressive teatcup removal setting was determined by identifying the last quarter with a teatcup attached in every milking. Sixty-nine cows were divided into 2 groups that each received 1 of the 2 treatments for a 1-wk period and then switched to the other treatment for a second week. For the months of April and May 2018, quarter milking duration was significantly different between the quarter with the longest and the second longest milking duration within an udder. The quarter with the longest milking duration was milked on average 49 s longer than the quarter with second longest milking duration. However, in 36% of the milkings, the quarter with the longest milking duration was different from that of the previous milking. In the experimental part of this study, we saw no differences in milking duration, box time, milk production rate, or SCC between the 30 and 50% teatcup removal setting applied to the last milking quarter. Further research on using a variation of this percentage-based setting to target the quarter with the average longest milking duration or using an absolute milk flowrate switch-point or a maximum milking duration setting on the last quarter for reducing cow milking duration and box time is warranted.
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Economic assessment of Holstein-Friesian dairy cows of divergent Economic Breeding Index evaluated under seasonal calving pasture-based managementThe objective of this study was to investigate the economic performance of 2 genetic groups (GG) of Holstein-Friesian dairy cows of divergent Economic Breeding Index (EBI), evaluated within 3 contrasting spring-calving pasture-based feeding treatments (FT). The study was a simulated economic appraisal, using the Moorepark Dairy Systems Model, a stochastic budgetary simulation model integrating biological data obtained from a 4-yr experiment conducted from 2013 to 2016. The 2 divergent GG were (1) high EBI representative of the top 5% nationally (elite) and (2) EBI representative of the national average (NA). The 3 FT were reflective of slight restriction to generous feeding. The elite GG had the lowest replacement rate, and therefore had lower replacement costs and an older and more productive parity structure. The elite GG consistently had higher sales of milk (on average +3% or +18,370 kg of milk) and milk solids (milk fat plus protein yield; +8.7% or +4,520 kg) compared with the NA GG across the 3 FT scenarios. Milk income was consequently greater for elite versus NA (on average +9.5% or +€21,489) cows. Livestock sales were greater (on average +13.2% or +€4,715) for NA compared with elite cows. Baseline net farm profit and net profit/ha at a base milk price of 29.5 cents per liter (3.3% protein and 3.6% fat) were on average €31,156, and €772 greater for elite compared with NA cows across the 3 FT. Greater profitability achieved with elite cows in each of the FT investigated demonstrated the adaptability of high-EBI cows across different levels of feeding intensities in seasonal pasture-based feeding systems. Sensitivity analysis of varying milk price and concentrate cost did not result in a reranking of GG for farm profit. This study clearly demonstrates the power of a suitably constructed genetic-selection index together with a well-considered breeding program to deliver genetics capable of favorable change to farm physical performance and profit over a relatively short duration.
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Associating mobility scores with production and reproductive performance in pasture-based dairy cowsLameness in dairy cows can have significant effects on cow welfare, farm profitability, and the environment. To determine the economic and environmental consequences of lameness, we first need to quantify its effect on performance. The objective of this study, therefore, was to determine the associations of various production and reproductive performance measurements (including milk, fat, and protein yield, somatic cell count, calving interval, cow death, or cow slaughter), and mobility scores in spring-calving, pasture-based dairy cows. We collected mobility scores (0 = good, 1 = imperfect, 2 = impaired, and 3 = severely impaired mobility), body condition scores, and production data for 11,116 cows from 68 pasture-based dairy herds. Linear mixed modeling was used to determine the associations between specific mobility scores and milk, fat and protein yield, and somatic cell count and calving interval. Binomial logistic regression was used to determine the association between mobility score and cow death, or slaughter. Significant yield losses of up to 1.4% of the average yield were associated with mobility score 2 and yield losses of up to 4.7% were associated with mobility score 3 during the early scoring period. Elevated somatic cell count was associated with all levels of suboptimal mobility during the late scoring period. Cows with a mobility score of 2 during the early scoring period were associated with longer calving interval length, whereas only cows with a mobility score of 3 during the late scoring period were associated with longer calving interval length. Cows with a mobility score ≥1 were more likely to be culled during both scoring periods. Our study, therefore, shows an association between specific mobility scores and production and reproductive performance in spring-calving, pasture-based dairy cows scored during the summer grazing period.
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Quality of three muscles from suckler bulls finished on concentrates and slaughtered at 16 months of age or slaughtered at 19 months of age from two production systemsThere is a requirement in some beef markets to slaughter bulls at under 16 months of age. This requires high levels of concentrate feeding. Increasing the slaughter age of bulls to 19 months facilitates the inclusion of a grazing period, thereby decreasing the cost of production. Recent data indicate few quality differences in longissimus thoracis (LT) muscle from conventionally reared 16-month bulls and 19-month-old bulls that had a grazing period prior to finishing on concentrates. The aim of the present study was to expand this observation to additional commercially important muscles/cuts. The production systems selected were concentrates offered ad libitum and slaughter at under 16 months of age (16-C) or at 19 months of age (19-CC) to examine the effect of age per se, and the cheaper alternative for 19-month bulls described above (19-GC). The results indicate that muscles from 19-CC were more red, had more intramuscular fat and higher cook loss than those from 16-C. No differences in muscle objective texture or sensory texture and acceptability were found between treatments. The expected differences in composition and quality between the muscles were generally consistent across the production systems examined. Therefore, for the type of animal and range of ages investigated, the effect of the production system on LT quality was generally representative of the effect on the other muscles analysed. In addition, the data do not support the under 16- month age restriction, based on meat acceptability, in commercial suckler bull production.
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Evaluation of production efficiencies at pasture of lactating suckler cows of diverse genetic merit and replacement strategyFeed costs account for the largest proportion of direct cost within suckler beef production systems. By identifying the cow type with enhanced capability of converting grazed herbage to beef output across lactations, suckler cow systems would become more efficient and sustainable. The objective of this study was to estimate grass DM intake (GDMI) and production efficiency among lactating suckler cows of diverse genetic merit for the national Irish maternal index (Replacement Index) which includes cow efficiency components such as milk yield and feed intake. Data from 131 cows of diverse genetic merit within the Replacement Index, across two different replacement strategies (suckler or dairy sourced), were available over two grazing seasons. Milk yield, GDMI, cow live weight (BW) and body condition score (BCS) were recorded during early, mid and late-lactation, with subsequent measures of production efficiency extrapolated. Genetic merit had no significant effect on any variables investigated, with the exception of low genetic merit (LOW) cows being 22 kg heavier in BW than high genetic merit (HIGH) cows (P < 0.05). Beef cows were 55 kg heavier in BW (P < 0.001), had a 0.31 greater BCS (P < 0.05) and 0.30 Unité Fourragère Lait (UFL) greater energy requirement for maintenance compared to dairy sourced beef × dairy crossbred (BDX) cows (P < 0.001). The BDX had 0.8 kg greater GDMI, produced 1.8 kg more milk (P < 0.001), had a 0.8 UFL greater energy requirement for lactation and produced weanlings that were 17 kg heavier in BW than beef cows (P < 0.05). Subsequent efficiency variables of milk per 100 kg BW (P < 0.001), milk per kg GDMI (P < 0.001) and GDMI per 100 kg BW (P < 0.001) were more favourable for BDX. The correlations examined showed GDMI had moderate positive correlations (P < 0.001) with intake per 100 kg BW, net energy intake per kg milk yield, RFI and intake per 100 kg calf weaning weight but was weakly negatively correlated to milk yield per kg GDMI (P < 0.001). No difference was observed across genetic merit for beef cows for any of the traits investigated. Results from the current study showed that, while contrasting replacement strategies had an effect on GDMI and production efficiency, no main effect was observed on cows diverse in genetic merit for Replacement Index. Nonetheless, utilising genetic indexes in the suckler herd is an important resource for selecting breeding females for the national herd and phenotypic performance generated from this study can be included in future genetic evaluations to improve reliability of genetic values.
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Developing and validating a model to predict the dry matter intake of grazing lactating beef cowsCurrent techniques for measuring the dry matter intake (DMI) of grazing lactating beef cows are invasive, time consuming and expensive making them impractical for use on commercial farms. This study was undertaken to explore the potential to develop and validate a model to predict DMI of grazing lactating beef cows, which could be applied in a commercial farm setting, using non-invasive animal measurements. The calibration dataset used to develop the model was comprised of 94 measurements recorded on 106 beef or beef–dairy crossbred cows (maternal origin). The potential of body measurements, linear type scoring, grazing behaviour and thermal imaging to predict DMI in combination with known biologically plausible adjustment variables and energy sinks was investigated. Multivariable regression models were constructed for each independent variable using SAS PROC REG and contained milk yield, BW, parity, calving day and maternal origin (dairy or beef). Of the 94 variables tested, 32 showed an association with DMI (P < 0.25) upon multivariable analysis. These variables were incorporated into a backwards linear regression model using SAS PROC REG. Variables were retained in this model if P < 0.05. Five variables; width at pins, full body depth, ruminating mastications, central ligament and rump width score, were retained in the model in addition to milk yield, BW, parity, calving day and maternal origin. The inclusion of these variables in the model increased the predictability of DMI by 0.23 (R2 = 0.68) when compared to a model containing milk yield, BW, parity, calving day and maternal origin only. This model was applied to data recorded on an independent dataset; a herd of 60 lactating beef cows two years after the calibration study. The R2 for the validation was 0.59. Estimates of DMI are required for measuring feed efficiency. While acknowledging challenges in applicability, the findings suggest a model such as that developed in this study may be used as a tool to more easily and less invasively estimate DMI on large populations of commercial beef cows, and therefore measure feed efficiency.
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Evaluation and application potential of an accelerometer-based collar device for measuring grazing behavior of dairy cowsThe commercially available collar device MooMonitor+ was evaluated with regards to accuracy and application potential for measuring grazing behavior. These automated measurements are crucial as cows feed intake behavior at pasture is an important parameter of animal performance, health and welfare as well as being an indicator of feed availability. Compared to laborious and time-consuming visual observation, the continuous and automated measurement of grazing behavior may support and improve the grazing management of dairy cows on pasture. Therefore, there were two experiments as well as a literature analysis conducted to evaluate the MooMonitor+ under grazing conditions. The first experiment compared the automated measurement of the sensor against visual observation. In a second experiment, the MooMonitor+ was compared to a noseband sensor (RumiWatch), which also allows continuous measurement of grazing behavior. The first experiment on n = 12 cows revealed that the automated sensor MooMonitor+ and visual observation were highly correlated as indicated by the Spearman’s rank correlation coefficient (rs) = 0.94 and concordance correlation coefficient (CCC) = 0.97 for grazing time. An rs-value of 0.97 and CCC = 0.98 was observed for rumination time. In a second experiment with n = 12 cows over 24-h periods, a high correlation between the MooMonitor+ and the RumiWatch was observed for grazing time as indicated by an rs-value of 0.91 and a CCC-value of 0.97. Similarly, a high correlation was observed for rumination time with an rs-value of 0.96 and a CCC-value of 0.99. While a higher level of agreement between the MooMonitor+ and both visual observation and RumiWatch was observed for rumination time compared to grazing time, the overall results showed a high level of accuracy of the collar device in measuring grazing and rumination times. Therefore, the collar device can be applied to monitor cow behavior at pasture on farms. With regards to the application potential of the collar device, it may not only be used on commercial farms but can also be applied to research questions when a data resolution of 15 min is sufficient. Thus, at farm level, the farmer can get an accurate and continuous measurement of grazing behavior of each individual cow and may then use those data for decision-making to optimize the animal management.
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Effect of cow replacement strategy on cow and calf performance in the beef herdTwo contrasting replacement strategies are used by Irish beef farmers to select replacement females – animals sourced from within the suckler beef herd and sourced from the dairy herd. The objective of this study was to investigate the effect of replacement strategy (i.e. beef v. beef×dairy (BDX)) on cow and calf performance using data from the national beef database across a range of beef and dairy breeds. The association between replacement strategy and calving difficulty score, calving interval, weaning weight, weaning price and all carcass traits was investigated using a mixed model. The effect of replacement strategy on cow survival, calving dystocia and calf perinatal mortality was quantified using logistic regression. Beef cows were older (10.92 days; P<0.001) at their first calving, but were 1.15 times (P<0.01) more likely to survive to a subsequent lactation compared with BDX cows. Calving interval was 1.53 days shorter (P<0.001) for BDX compared with beef cows. Greater calving difficulty and calving dystocia was associated with beef cows (P<0.001) relative to BDX. However, BDX were 1.36 times (P<0.001) more likely to have a dead calf at birth relative to beef cows. Calves weaned from BDX were heavier (18.49 kg; P<0.001) at weaning, reached slaughter 12.8 days earlier (P<0.001), had 7.99 kg heavier carcass (P<0.001) and a greater fat score (P<0.001) compared with the progeny of beef cows. Beef cow progeny had a superior conformation score (0.5; P<0.001) and achieved a greater price per kilogram (P<0.001) compared with progeny from BDX. Beef cull cows had a heavier carcass (5.58 kg), superior carcass conformation, greater carcass price per kilogram and greater overall carcass value (P<0.001) than BDX. Results from this study show that replacement strategy is of fundamental importance depending on the type of system implemented by farmers and consideration must be given to the traits of importance within the context of the individual production system.
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Performance, profitability and greenhouse gas emissions of alternative finishing strategies for Holstein-Friesian bulls and steersModifying finishing strategies within established production systems has the potential to increase beef output and farm profit while reducing greenhouse gas (GHG) emissions. Thus, the objectives of this study were to investigate the effects of finishing duration on animal performance of Holstein-Friesian (HF) bulls and steers and evaluate the profitability and GHG emissions of these finishing strategies. A total of 90 HF calves were assigned to a complete randomised block design; three bull and three steer finishing strategies. Calves were rotationally grazed in a paddock system for the first season at pasture, housed and offered grass silage ad libitum plus 1.5 kg DM of concentrate per head daily for the first winter and returned to pasture for a second season. Bulls were slaughtered at 19 months of age and either finished indoors on concentrates ad libitum for 100 days (19AL), finished at pasture supplemented with 5 kg DM of concentrate per head daily for 100 (19SP) or 150 days (19LP). Steers were slaughtered at 21 months of age and finished at pasture, supplemented with 5 kg DM of concentrate per head daily for 60 (21SP) and 110 days (21LP) or slaughtered at 24 months of age and finished indoors over the second winter on grass silage ad libitum plus 5 kg DM of concentrate per head daily (24MO). The Grange Dairy Beef Systems Model and the Beef Systems Greenhouse Gas Emissions Model were used to evaluate profitability and GHG emissions, respectively. Average daily gain during the finishing period (P<0.001), live weight at slaughter (P<0.01), carcass weight (P<0.05) and fat score (P<0.001) were greater for 19AL than 19SP and 19LP, respectively. Similarly, concentrate dry matter intake was greater for 19AL than 19SP; 19LP was intermediate (P<0.001). Live weight at slaughter (P<0.001), carcass weight (P<0.001), conformation score (P<0.05) and fat score (P<0.001) were greater for 24MO than 21SP and 21LP, respectively. During the finishing period concentrate dry matter intake was greater for 21LP than 21SP with 24MO intermediate; 542, 283 and 436 kg DM, respectively. Although pasture-based finishing strategies had lower gross output values, concentrate feed costs were also reduced thus net margin was greater than indoor finishing strategies. Reducing concentrate input increased GHG emissions for bulls and steers slaughtered at the same age, respectively. Although prolonging the finishing duration reduced GHG emissions for bull and steer production systems, finishing bulls and steers over a longer period at pasture did not enhance animal performance and profit.
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Water footprinting of pasture-based farms; beef and sheepIn the context of water use for agricultural production, water footprints (WFs) have become an important sustainability indicator. To understand better the water demand for beef and sheep meat produced on pasture-based systems, a WF of individual farms is required. The main objective of this study was to determine the primary contributors to freshwater consumption up to the farm gate expressed as a volumetric WF and associated impacts for the production of 1 kg of beef and 1 kg of sheep meat from a selection of pasture-based farms for 2 consecutive years, 2014 and 2015. The WF included green water, from the consumption of soil moisture due to evapotranspiration, and blue water, from the consumption of ground and surface waters. The impact of freshwater consumption on global water stress from the production of beef and sheep meat in Ireland was also computed. The average WF of the beef farms was 8391 l/kg carcass weight (CW) of which 8222 l/kg CW was green water and 169 l/kg CW was blue water; water for the production of pasture (including silage and grass) contributed 88% to the WF, concentrate production – 10% and on-farm water use – 1%. The average stress-weighted WF of beef was 91 l H2O eq/kg CW, implying that each kg of beef produced in Ireland contributed to freshwater scarcity equivalent to the consumption of 91 l of freshwater by an average world citizen. The average WF of the sheep farms was 7672 l/kg CW of which 7635 l/kg CW was green water and 37 l/kg CW was blue water; water for the production of pasture contributed 87% to the WF, concentrate production – 12% and on-farm water use – 1%. The average stress-weighted WF was 2 l H2O eq/kg CW for sheep. This study also evaluated the sustainability of recent intensification initiatives in Ireland and found that increases in productivity were supported through an increase in green water use and higher grass yields per hectare on both beef and sheep farms.
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Development and evaluation of the herd dynamic milk model with focus on the individual cow componentThe herd dynamic milk (HDM) model is a dynamic model capable of simulating the performance of individual dairy animals (from birth to death), with a daily time step. Within this study, the HDM model is described and evaluated in relation to milk production, body condition score (BCS) and BCS change throughout lactation by comparing model simulations against data from published experimental studies. The model’s response to variation in genetic potential, herbage allowance and concentrate supplementation was tested in a sensitivity analysis. Data from experiments in Ireland and France over a 3-year period (2009–11) were used to complete the evaluation. The aim of the Irish experiment was to determine the impact of different stocking rates (SRs) (SR1: 3.28 cow/ha, SR2: 2.51 cow/ha) on key physical, biological and economic performance. The aim of the French experiment was to evaluate over a prolonged time period, the ability of two breeds of dairy cows (Holstein and Normande) to produce and to reproduce under two feeding strategies (high level and low level) in the context of compact calving. The model evaluation was conducted at the herd level with separate evaluations for the primiparous and multiparous cows. The evaluation included the two extreme SRs for the Irish experiment, and an evaluation at the overall herd and individual animal level for the different breeds and feeding levels for the French data. The comparison of simulation and experimental data for all scenarios resulted in a relative prediction error, which was consistently <15% across experiments for weekly milk production and BCS. In relation to BCS, the highest root mean square error was 0.27 points of BCS, which arose for Holstein cows in the low feeding group in late lactation. The model responded in a realistic fashion to variation in genetic potential for milk production, herbage allowance and concentrate supplementation.
