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Residual methane emission (RME) is a trait that has previously been identified as being independent of animal production traits. The objective of this study was to investigate the effect of ranking grazing dairy cows by RME on animal productivity and enteric methane (CH4) emissions. Milk production, dry matter intake (DMI), liveweight (LWT) and CH4 were recorded on grazing late lactation dairy cows at Teagasc Moorepark, Ireland. The dairy cows were producing 352 g CH4/day, while consuming 16.6 kg DM. The mean methane yield was 20.79 g CH4/kg DMI. Residual methane emission was calculated as the difference between measured CH4 yield and New Zealand emission factor (21.6 g CH4/kg DMI). These dairy cows were ranked based on their RME and classified into groups. The low RME group produced 15% less CH4 than the high RME group while maintaining milk production and feed conversion efficiency. The low RME group had lower methane yield, and methane intensity. There are no significant phenotypic correlations between RME and animal production traits such as energy corrected milk yield, or LWT. These results indicate that RME has the ability to select and rank low emitting grazing dairy cows while being independent from animal productivity traits. [ABSTRACT FROM AUTHOR]

Similar to all dairy systems internationally, pasture-based dairy systems are under increasing pressure to reduce their greenhouse gas (GHG) emissions. Ireland and New Zealand are 2 countries operating predominantly pasture-based dairy production systems where enteric CH 4 contributes 23% and 36% of total national emissions, respectively. Ireland currently has a national commitment to reduce 51% of total GHG emissions by 2030 and 25% from agriculture by 2030, as well as striving to achieve climate neutrality by 2050. New Zealand's national commitment is to reduce 10% of methane emissions by 2030 and between 24% and 47% reduction in methane emissions by 2050. To achieve these reductions, factors that affect enteric methane (CH 4) production in a pasture-based system need to be investigated. The objective of this study was to assess the relationship between enteric CH 4 and other animal traits (feed intake, metabolic liveweight, energy corrected milk yield, milk urea concentration, and body condition score [BCS]) in a grazing dairy system. Enteric CH 4 emissions were measured on 45 late lactation (213.8 ± 29 d after calving) grazing Holstein-Friesian and Holstein-Friesian × Jersey crossbred cows (lactation number 3.01 ± 1.65, 538.64 ± 59.37 kg live weight, and 3.14 ± 0.26 BCS) using GreenFeed monitoring equipment for 10 wk. There was a training period for the cows to use the GreenFeed of 3 wk before the 10-wk study period. The average enteric CH 4 produced in the study was 352 g ± 45.7 g per day with an animal to animal coefficient of variation of 13%. Dry matter intake averaged 16.6 kg ± 2.23 kg per day, while milk solids (fat plus protein) averaged 1.62 kg ± 0.29 kg per day. A multiple linear regression model indicated that each one unit increase in energy corrected milk yield, metabolic liveweight and milk urea concentration, resulted in an increase in enteric CH 4 production per day by 3.9, 1.74, and 1.38 g, respectively. Although each one unit increase in BCS resulted in a decrease in 39.03 g CH 4 produced per day. When combined, these factors explained 47% of the variation in CH 4 production, indicating that there is a large proportion of variation not included in the model. The repeatability of the CH 4 measurements was 0.66 indicating that cows are relatively consistently exhibiting the same level of CH 4 throughout the study. Therefore, enteric CH 4 production is suitable for phenotyping. [ABSTRACT FROM AUTHOR]

This document provides abstracts of papers presented at the Society of Dairy Technology 80th Anniversary Conference, covering a range of topics in the dairy industry. One paper examines the impact of process conditions on water evaporation and energy usage in spray drying, while another explores the use of near-infrared spectroscopy to analyze the composition of raw milk. Other papers discuss the development of high-protein soft cheese alternatives, plant-based cheese analogues, and sustainable cleaning strategies in dairy facilities. The document also mentions a project focused on characterizing the milk metabolome and developing biomarkers for milk processability and methane production. Additionally, the document highlights a study that modified sediment quantification tests for dairy powders to improve image analysis capabilities, with promising results. Further research is planned to investigate the effects of robotic agitation and test additional powders. [Extracted from the article]

The objective of this study was to quantify the farm gate nitrogen (N) offset potential of perennial ryegrass (Lolium perenne L.; PRG) white clover (Trifolium repens L.; WC) swards by comparing the herbage and milk production from dairy farmlets that were simulations of full farming systems. A study was established where 120 cows were randomly assigned to 4 farmlets of 10.9 ha (stocking rate: 2.75 cow/ha), composed of 20 paddocks each. Cows were fed 526 kg of DM of concentrate on average each year. The 4 grazing treatments were PRG-only at 150 or 250 kg of N/ha and PRG-WC at 150 or 250 kg of N/ha. Cows remained in their treatment group for an entire grazing season and were re-randomized as they calved across treatments each year. As cows calved in the spring as standard practice in Ireland, they were rotationally grazed from early February both day and night (weather permitting) to mid-November, to a target postgrazing sward height of 4.0 cm. Mean sward WC content was 18.1% and 15.4% for the 150 and 250 kg of N/ha PRG-WC treatments, respectively over the 3-yr period. When WC was included, lowering the N rate did not reduce pregrazing yield, pregrazing height, or herbage removed, but those factors decreased significantly when WC was absent. Total annual herbage DM production was 13,771, 15,242, 14,721, and 15,667 kg of DM/ha for PRG-only swards receiving 150 or 250 kg of N/ha and PRG-WC swards receiving 150 or 250 kg of N/ha, respectively. In addition, when WC was present, compressed postgrazing sward heights were lower (4.10 vs. 4.21 cm) and herbage allowance (approximately 17 kg/cow feed allocation per cow per day) higher than the high-N control (+ 0.7 kg of DM/cow per day). There was a significant increase in milk production, both per cow and per hectare, when WC was included in PRG swards. Over the 3-yr study, cows grazing PRG-WC had greater milk (+304 kg) and milk solids (+31 kg of fat + protein) yields than cows grazing PRG-only swards. This significant increase in milk production suggests that the inclusion of WC in grazing systems can be effectively used to increase milk production per cow and per hectare and help offset nitrogen use. This result shows the potential to increase farm gate N use efficiency and reduce the N surplus compared with PRG-dominant sward grazing systems receiving 250 kg of N/ha, without negatively affecting milk solids yield or herbage production, thus increasing farm profit by €478/ha. [ABSTRACT FROM AUTHOR]

The objective of this study was to document the milking efficiency of a sample of Irish dairy farms and to understand the effects of (1) seasonality, (2) management practices, (3) parlor infrastructure, and (4) parlor automations on milking efficiency metrics. A novel methodology based on empirical data from video cameras, infrastructure surveys, and milk yield data allowed for the accurate computation of milking efficiency metrics and quantification of the effects of seasonality, number of operators, and parlor automations on milking efficiency across 2 parlor types. The data for this study were collected over 2 periods: period 1 (July 28, 2020, to October 23, 2020, peak-late production) and period 2 (April 12, 2021, to May 19, 2021, early-peak production) from a sample of 16 herringbone and 10 rotary commercial Irish dairy farms. Milking efficiency was evaluated on each farm using 3 key performance indicators: (1) cows milked per hour (cows/h), (2) cows milked per operator per hour (cows/h per operator), and (3) liters of milk harvested per hour (L/h). Milking efficiency key performance indicators were calculated using "total process time," defined as the time between the first cow entering the holding yard and the end of the cleaning process. Average herd sizes for herringbone and rotary farms were 180 and 425 cows, respectively. Average system sizes for herringbone and rotary farms were 20 and 50 clusters, respectively. For herringbone farms, the average milking efficiency was 94 cows/h, 73 cows/h per operator, and 1,012 L/h, whereas rotary farms achieved an average milking efficiency of 170 cows/h, 132 cows/h per operator, and 1,534 L/h. Parlor size was strongly correlated with milking efficiency (cows/h) for herringbone parlors (0.91) but was only moderately correlated for rotary parlors (0.50). Hence, we documented the effect of parlor size on milking efficiency is relative to parlor type. Cluster utilization values on herringbone farms were 5 cows/cluster per h, 4 cows/cluster per operator per h, and 51 L/cluster per h, which were 67%, 33%, and 65% greater than rotary farms, respectively. We found for both herringbone and rotary farms hourly cow throughput (cows/h, cows/h per operator) were greatest during period 1 and that the volume of milk harvested per hour (L/h) was greatest for period 2. Thus, we documented an inverse seasonal relationship between hourly rates of cows milked and milk harvested. We observed that for herringbone farms, milking efficiency (cows/h, L/h) had a strong positive correlation (0.75, 0.74) with the levels of automation use. However, the minimal variation in automations used among rotary farms made it difficult to evaluate their effect on milking efficiency. Similarly, we found that the effect of automations on milking efficiency was dependent on parlor type. On average, a second operator at milking for both herringbone (H) and rotary (R) farms increased values for cows/h (+19%, H; +34%, R) and L/h (+21%, H; +12%, R) but lowered values for cows/h per operator (−35%, H; −12%, R). The holistic methodology applied in this study allowed us to add novel data to the literature by quantifying the effects of seasonality, the number of operators present at milking, and parlor automation use on milking efficiency across 2 parlor types. [ABSTRACT FROM AUTHOR]

Globally, the majority of dairy cows are milked twice a day (TAD); however, in pasture-based production systems, such as in Ireland, the idea of milking once a day (OAD) is being considered for reasons such as improved work-life balance. The immediate effects within a lactation, as well as the multilactation consequences of OAD, compared with TAD milking, require understanding. The objective of this randomized experiment was to compare OAD and TAD milking, over a 3-yr period, by examining the differences in milk production and composition, body weight (BW), body condition score (BCS), dry matter intake (DMI), udder characteristics, locomotion score, and milking time. Over the 3-yr period, 83 cows were enrolled in the experiment; 32, 44, and 48 cows in yr 1, 2, and 3 of the experiment, respectively. Each year, 23% of the herds were primiparous animals, while the remainder were second lactation or greater in parity. All cows were milked in the morning at 0700 h; only cows milked TAD were milked a second time each day at 1600 h. Cows rotationally grazed pastures for the duration of the lactating period and were housed during the nonlactating period. Milking cows OAD reduced cumulative milk yield by 26%, and milk solids yield (kg of fat + kg of protein) by 21%, across the 3 yr of the experiment when compared with cows milked TAD which produced 4,126 and 365 kg/cow, respectively. A contributory factor to the reduced production was a shorter lactation length (9.7 d) of the cows milked OAD compared with TAD (294 d). Milk fat percent of cows milked TAD was similar for all 3 yr of the study (5.05%), whereas milk fat percent of the cows milked OAD increased year on year, with each year being greater than the previous year (5.02%, 5.32%, and 5.70% for yr 1, 2, and 3; respectively). Milk protein percent was greater (+0.19%) for cows milked OAD compared with TAD which was 3.78%. Compared with cows milked TAD, total DMI for cows milked OAD was 22% less at the start of lactation (<167 d), but as the lactation progressed (>167 d) we observed no difference in DMI between treatments. Similar to the literature, milking cows OAD significantly increased average somatic cell score, both during (+16%) and at the end of lactation (+19%), compared with milking cows TAD which were 4.69 and 4.79, respectively. We detected positive aspects associated with OAD milking such as greater BW, BCS, and fertility performance. Milking OAD reduced both milking time per cow per day (reductions ranged from 34% in the first 4 mo of lactation to 43% during mo 5–9 of lactation) and milking time per liter of milk (−3.5 s/L) throughout lactation, leading to less labor inputs on-farm which can have positive implications for farmer work-life balance. The significant time saving and potential savings in costs (e.g., electricity) need to be considered in conjunction with the milk production reduction when considering OAD milking for the entire lactation. [ABSTRACT FROM AUTHOR]

The objective of this study was to quantify the effects of different milk flow-rate switch-point settings on milking duration, somatic cell count (SCC), strip milk, teat condition, and milk yield in a grass-based system in a long-term experiment. Much work has already been conducted providing strong support for significant reduction in milking duration without effects on yield through increasing the flow-rate switch-point at which vacuum to the milking cluster ceases and the cluster is removed from the cow by means of a retracting cord. However, in practice many farms have not adopted this labor-saving technology on the basis that it may increase milk SCC. Recent research on commercial Irish dairy herds identified the contagious mastitis-causing pathogen Staphylococcus. aureus as the most prevalent pathogen detected. Staph. aureus could have a cyclical shedding pattern which would inhibit detection at certain time points. Therefore, to reliably assess the effect of milk flow-rate switch-points on SCC, a long-term study was required, consisting of multiple observations on cow-level SCC. The present study filled this gap in knowledge by informing on any effect that ceasing milking at different flow rates may have on milking duration and SCC levels, particularly with regard to spring calving grass-based systems. Four treatments, consisting of milk flow-rate switch-points increasing from 0.2 kg/min to 0.8 kg/min in steps of 0.2 kg/min, were deployed for 31 wk to cows at the Teagasc Research Centre at Moorepark, Ireland. The effect of treatment on daily milking duration was significant. The milking duration for a milk flow-rate switch-point of 0.8 kg/min was 95 s (14%) shorter than for 0.2 kg/min. We did not find a significant effect of increasing the milk flow-rate switch-point from 0.2 to 0.8 kg/min on milk yield or SCC in this long-term study. We did find a significant effect of week of experiment on milk SCC, whereby the SCC of the cows on the experiment increased similarly among treatment groups as lactation progressed. A significant reduction in dead time (time from cluster attachment to reach a milk flow rate of 0.2 kg/min) was also noted as the milk flow-rate switch-point increased. On average, reductions in dead time contributed 12% to the overall reductions in milking duration. Similarly, reductions in low flow time (time from a flow rate of 0.2 kg/min to cluster detachment at the end of milking) contributed 26% to the overall reductions in milking duration. Reductions in dead time and low flow time played a greater role in reducing p.m. milking duration rather than a.m. milking duration due to the milking interval practiced on the research farm. [ABSTRACT FROM AUTHOR]

Subclinical mastitis in cows affects their health, well-being, longevity, and performance, leading to reduced productivity and profit. Early prediction of subclinical mastitis can enable dairy farmers to perform interventions to mitigate its effect. The present study investigated how well predictive models built using machine learning techniques can detect subclinical mastitis up to 7 d before its occurrence. The data set used consisted of 1,346,207 milk-day (i.e., a day when milk was collected on both morning and evening) records spanning 9 yr from 2,389 cows producing on 7 Irish research farms. Individual cow composite milk yield and maximum milk flow were available twice daily, whereas milk composition (i.e., fat, lactose, protein) and somatic cell count (SCC) were collected once per week. Other features describing parity, calving dates, predicted transmitting ability for SCC, body weight, and history of subclinical mastitis were also available. The results of the study showed that a gradient boosting machine model trained to predict the onset of subclinical mastitis 7 d before a subclinical case occurs achieved a sensitivity and specificity of 69.45 and 95.64%, respectively. Reduced data collection frequency, where milk composition and SCC were recorded only every 15, 30, 45, and 60 d was simulated by masking data, to reflect the frequency of recording of this data on commercial dairy farms in Ireland. The sensitivity and specificity scores reduced as recording frequency reduced with respective scores of 66.93 and 80.43% when milk composition and SCC were recorded just every 60 d. Results demonstrate that models built on data that could be recorded routinely available on commercial dairy farms, can achieve useful predictive ability of subclinical mastitis even with reduced frequency of milk composition and SCC recording. [ABSTRACT FROM AUTHOR]

Automatic cluster removers (ACR) operate by ceasing vacuum to the cluster and detaching the milking unit from the udder by means of a retracting cord once the milk flow has decreased to a predefined level (i.e., the milk flow rate switch-point). There is a large body of literature on this topic indicating that increasing the flow rate switch-point (e.g., from 0.2 kg/min to 0.8 kg/min at the udder level) is effective in reducing milking duration while having little effect on milk yield or milk somatic cell count (SCC). However, despite these findings many farms still use a switch-point of 0.2 kg/min because it is believed that emptying the udder completely at each milking is a prerequisite for good dairy cow management, especially in relation to maintaining a low milk SCC. However, there may be additional undocumented benefits in terms of cow comfort to increasing the milk flow rate switch-point, because the low milk flow period at the end of milking is a high-risk time for inducing teat-barrel congestion. The objective of this study was to quantify the effect of 4 milk flow rate switch-point settings on cow comfort, milking duration, and milk yield. In this study, we applied 4 treatments consisting of different milk flow rate switch-points to cows in a crossover design in a spring calving grass based dairy herd in Ireland. The treatments were (1) MFR0.2, where the cluster was removed at a milk flow rate of 0.2 kg/min; (2) MFR0.4, where the cluster was removed at 0.4 kg/min; (3) MFR0.6, where the cluster was removed at 0.6 kg/min, and (4) MFR0.8, where the cluster was removed at 0.8 kg/min. Milking parameters were recorded by the parlor software and leg movements (i.e., kicks or steps) during milking were recorded with an accelerometer. These data were used as a proxy for cow comfort during milking. The results of this study showed significant differences in cow comfort across treatments, as indicated by cow stepping during milking, for a.m. milkings, but these differences were not detected for p.m. milkings, possibly because a.m. milkings were longer than p.m. milkings due to a 16:8 h milking interval on the research farm. Differences tended to distinguish the 2 lower-flow switch-point settings with greater leg movement against the 2 higher-flow switch-point settings with less leg movement during milking. The effect of treatment (milk flow rate switch-point) on daily milking duration was significant. The milk duration for MFR0.8 was 89 s (14%) shorter than MFR0.2. There was no significant effect of treatment on SCC in this study. [ABSTRACT FROM AUTHOR]

Milk recording is a critical tool in dairy farming, providing individual cow information. When used effectively, this data contributes to on-farm productivity, herd health management decisions and supports prudent veterinary prescribing of antimicrobials. Although an industry and government priority, uptake has been relatively slow in Ireland. This multi-methods, three-part study aimed to gain a comprehensive understanding of the benefits to farm performance, and factors driving uptake of milk recording on Irish dairy farms. It involved an economic analysis of N=516 farms from 2008–2019, a workshop with N=26 stakeholders and an online survey of N=197 non-milk-recording farmers. Quantitative and qualitative data were analysed using econometric models and thematic analysis respectively. Results were synthesised using the COM-B model to gain a deeper understanding of what drives the target behaviour. The study revealed that agricultural education, farm location, farm specialisation in dairy and membership of a farmer discussion group were the main factors influencing uptake of milk recording. Milk recording was associated with a €39.04/cow increase in gross margin, a 177.58 litres/cow increase in milk yield and a reduction of 13,450 cells/ml in bulk milk tank somatic cell count readings. Infrastructural constraints, cost, lack of benefits and workload were the most reported perceived barriers to milk recording by farmers. The Behaviour Change Wheel illustrates how to utilise findings and systematically develop future interventions to increase milk recording uptake. This study highlights the importance of a multi-methods approach to agricultural technology adoption and the need for evidence-based methodology when developing behaviour change interventions. [ABSTRACT FROM AUTHOR]

This article explores therelationship among farm‐level productivity growth, scale, and greenhouse gas (GHG) emission intensity during a time period of significant agricultural policy change affecting Ireland's dairy industry. Specifically, we focus on the 2015 EU milk quota abolition, which initiated major dairy expansion in Ireland. We use a representative sample of Irish dairy farms from 2000 to 2017, that includes data on farm specific GHG emissions. Based on this detailed farm level panel data set, we estimate productivity with a control function approach. We then apply fixed effects and dynamic panel data methods to explore the implications of productivity and scale on GHG emission intensity. Our findings indicate that increased productivity is negatively associated with GHG emission intensity, which changes with distinct milk quota abolition phases. Overall, our findings are important for understanding the relationship between policy reforms and GHG emissions in agriculture, and how to improve agricultural mitigation strategies. [ABSTRACT FROM AUTHOR]

A longer grazing season can lower the costs of pasture‐based dairy production. Accumulating herbage during autumn increases herbage mass available for grazing in late autumn and the following spring but results in higher pre‐grazing herbage mass (PGHM). This could affect sward nutritive value and milk production. The effects of accumulating herbage during autumn on the length of the grazing season, nutritive value, milk production and the supply of herbage mass in the following spring (opening) were examined at systems scale in this study. The dataset was 60 grazing systems from systems comparisons conducted between 2001 and 2018 with spring‐calving dairy herds (mean stocking rate 2.4 cows ha−1) at Solohead Research Farm, Ireland. Herbage mass accumulated per system was measured as average herbage mass (AHM; herbage mass >4 cm; average of all paddocks). A higher PGHM (1,783 vs. 1,445 kg dry matter [DM] ha−1, p < 0.001, standard error of the mean [SEM] 32.5) and peak AHM (highest AHM; 1,345 vs. 1,139 kg DM ha−1, p = 0.002, SEM 39.2) during late summer and autumn (1 August to end of grazing season [closing]) did not affect herbage nutritive value or milk production (p > 0.05). Each increase in peak AHM of 100 kg DM ha−1 increased days at pasture per cow in late summer and autumn by 2.2 ± 0.44 (p < 0.001, partial R2 = 0.46) and increased closing AHM by 46 ± 6.5 kg DM ha−1 (p < 0.001, partial R2 = 0.42). Opening AHM in February increased with closing AHM (p < 0.001, R2 = 0.41). Accumulating herbage during late summer and autumn facilitated a longer grazing season while not impacting on milk production. [ABSTRACT FROM AUTHOR]

Internationally, consumer dissatisfaction with cow-calf separation at birth has led to increased interest in alternative calf-rearing methods, specifically cow-calf contact (CCC) systems. The objectives of this preliminary study were to estimate whether CCC could be incorporated into an Irish spring-calving, pasture-based system, and to investigate the effects on cow milk production and health. Three systems were compared: the conventional Irish system (CONV;18 cows), cow and calf were separated < 1 h postbirth, cows were pasture-based and milked twice-a-day; a full-time access system (FT;14 cows), cow and calf were allowed constant, unrestricted access, were pasture-based, and cows were milked twice-a-day; and a part-time access system (PT;18 cows), cow and calf had unrestricted access when indoors at night, cows grazed outdoors by day while calves remained indoors, and cows were milked once-a-day in the morning. Cows were blocked and balanced across the three systems by previous lactation machine milk yield (MMY), BW, and body condition score (BCS). Following an 8-week CCC period, all calves were weaned (FT and PT underwent a 7-d gradual weaning and separation process) and all cows were milked twice-a-day. Cow MMY was recorded daily and milk composition was recorded weekly; milk data were analysed from weeks 1 to 8 (CCC period), weeks 9 to 35 (post-CCC period), and weeks 1 to 35 (cumulative lactation). Cow BW and BCS were taken weekly for weeks 1-12, and at the end of the lactation. During the CCC period, all systems differed (P < 0.001) in MMY (mean ± SEM; 24.0, 13.6, and 10.3 ± 0.50 kg/d for CONV, FT, and PT cows, respectively). After the CCC period, CONV MMY (20.2 ± 0.48 kg/d) remained higher (P < 0.001) than the FT (16.6 kg/d) and PT cows (15.7 kg/d). The FT and PT cows yielded 24 and 31% less in cumulative lactation MMY and 26 and 35% less in cumulative lactation milk solids yield, respectively, compared to CONV (5 072 ± 97.0 kg and 450 ± 8.7 kg). During the CCC period, somatic cell score was higher (P = 0.030) in PT cows (5.15 ± 0.118) compared to FT cows (4.70 ± 0.118), while CONV (4.94 ± 0.118) were inconclusive to both. The PT cows (523 ± 4.9 and 520 ± 6.8 kg) were heavier than the CONV (474 ± 4.9 and 479 ± 6.8 kg) and FT (488 ± 4.9 and 487 ± 6.8 kg) cows at week 4 and week 8 (both P < 0.001). The PT cows had higher BCS than CONV and FT at all observed times. This preliminary research suggests that although CCC was incorporated without impacting cow health, the two CCC systems investigated negatively affected cow production., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Global land resources are over-exploited and natural habitats are declining, often driven by expanding livestock production. In Ireland, pastureland for grazing cattle and sheep account for circa 60% of terrestrial land use. The agriculture, forestry and other land use sector (AFOLU) is responsible for 44% of national greenhouse gas (GHG) emissions. A new Grassland Animal response Model (GLAM) was developed to relate livestock-cohort grass and feed requirements to farm-grassland system areas, enhancing environmental assessment of prospective AFOLU configurations. Although land conversion targets are often well-defined, they tend to lack a clear definition of where land sparing can occur. Through analyses of 10 scenarios of milk and beef production and management strategies, we found that displacing beef cows with dairy cows can increase national protein output while sparing up to 0.75 million ha (18%) of grassland (albeit with a minor increase in overseas land requirement for additional concentrate feed). Reducing slaughter age, increasing exports of male dairy calves and increasing grassland use efficiency on beef farms each achieved between 0.19 and 0.32 million ha of land sparing. Sexed semen to achieve more favourable male-female birth ratios had a minor impact. GHG emissions, ammonia emissions and nutrient leaching were only reduced substantially when overall cattle numbers declined, confirming the need for cattle reductions to achieve environmental objectives. Nonetheless, application of GLAM shows potential for improved grass and cattle management to spare good quality land suitable for productive forestry and wetland restoration. This change is urgently needed to generate scalable carbon dioxide removals from the land sector in Ireland, and globally. [Display omitted] • GLAM models land requirements of changing herd dynamics in livestock systems. • Land & environmental impacts of protein output vary in cattle production strategies. • Up to 18% of Irish grassland can be spared without reducing total protein production. • GHG emission reductions across studied scenarios fall far short of climate targets. • Translating bio-physical potential to reality will require careful policy intervention. [ABSTRACT FROM AUTHOR]

Zero-grazing (ZG; the mechanical harvesting and feeding of fresh grass) is increasingly used in grass-based milk production systems alongside conventional grazing. It allows farmers to supply fresh grass from land parcels that are outside of the main grazing block during seasonal shortages and periods when climatic conditions limit animal grazing opportunities. The objective of this study was to establish an understanding of current ZG practices on Irish dairy farms, to capture farmer perceptions on the implementation of this management practice, and to identify farmer knowledge requirements on ZG. An online survey was distributed and completed by 130 dairy farmers who use or have used ZG. Zero-grazing was used alongside conventional grazing by 92% of respondents. These farms were particularly fragmented, with between 1 and 14 separate land blocks. Respondents felt ZG helped them overcome fragmentation, increase grass use, and extend grass feeding in spring and autumn. However, extra cost and time input associated with ZG were recognized as key challenges. The majority of respondents rated current technical information available on ZG in the Republic of Ireland as "poor" or "very poor," and knowledge deficits were identified in the areas of cost analysis, grass management and productivity, cow productivity, cow health and nutrition, and soil fertility. [ABSTRACT FROM AUTHOR]

The diet of dairy cows in Ireland traditionally changes abruptly from predominantly pasture silage before calving to grazed perennial ryegrass immediately after calving. This potentially leads to problems with adaptation of microbes in the rumen with consequences of reduced intake and ultimately lower milk production. This experiment aimed to determine if introducing first-lactation dairy cows to perennial ryegrass herbage in the final weeks of pregnancy, thus eliminating a major dietary change at calving, could improve the adaptation process, potentially increasing dry matter intake (DMI) and milk production in early lactation. Three weeks prior to their expected calving date, 14 spring calving dairy cows were assigned to one of two treatments (n = 7): pasture silage pre-partum and perennial ryegrass herbage post-partum, or perennial ryegrass herbage both pre- and post-partum. Treatment diets were fed for 11 (±7) d pre-partum and for 14 (±0) d post-partum. For both treatments, DMI increased post-partum, but there was no difference between treatments, pre- or post-partum (5.9 and 8.8 kg DM/cow per day, respectively). There were no differences in milk yield or composition between the treatments. Body condition score declined following parturition but there were no differences between treatments. Plasma non-esterified fatty acids, glucose and β-hydroxybutyrate were also unaffected by treatment but did indicate a state of negative energy balance in early lactation. The results of this experiment suggest that pre-partum adaptation to perennial ryegrass herbage would not benefit milk production in first-lactation dairy cows in early lactation in Irish dairy farms employing this system. [ABSTRACT FROM AUTHOR]

Antibody-detecting tests for Mycobacterium avium ssp. paratuberculosis (MAP) have low sensitivity and imperfect specificity for detection of infection. Sensitivity increases as the disease progresses. Aside from infection status and stage of disease, several factors affect test performance. These factors have not yet been studied in dairy cows producing lower volumes of milk with higher solids concentration, such as those managed in low-input, pasture-based production systems. Furthermore, the effect of correcting for these associations on individual and herd test status is also unknown. The first objective of this study was to examine the relationship between MAP antibody response in milk and milk yield, somatic cell count (SCC), fat and protein contents, and stage of lactation in dairy cows enrolled in the national Johne's Disease Control Programme (JDCP) in Ireland. The second objective was to examine the effect of correcting the antibody response for these associations on the test status of individual cows and herds, given that individual tests are often used to define a herd's status. Data were extracted for herds in the JDCP from January 2014 to December 2015 inclusive, consisting of 42,657 milk recordings from 18,569 cows across 187 dairy herds. Two linear regression models were constructed to investigate the association between log-transformed MAP sample-to-positive ratio and milk recording data and in primi- and multiparous cows. Days in milk was modeled as a B-spline in each model, and cow and herd were included as random effects. Across both models, natural log-transformed MAP antibody response was negatively associated with milk yield, positively associated with protein and fat production, and had a curvilinear association with log-transformed SCC. The association between MAP antibody response and days in milk varied over the course of the lactation. However, when combined, these variables explained only 5.1% of the variation in the antibody response of the population. After correcting for these associations, 93 multiparous cows and 20 primiparous cows changed category (negative, suspect, or positive). When considered at the herd-test level, out of a total of 531 herd tests, 1 herd changed from negative to positive, and 5 herds changed from positive to negative. This study provides useful information to aid in the interpretation of antibody results for herds testing animals for the presence of MAP infection. At an overall population level, correction of the serological response for non-disease-associated factors has the potential to change the status of only a small number of cows. At the herd level, the proportion of herds changing status was minimal. However, depending on the implications of a herd-level serological diagnosis, consideration should be given to correcting for these non-disease-associated variables within the context of national JD control programs. [ABSTRACT FROM AUTHOR]

The cow-side diagnosis of reproductive tract disease (RTD) involves identifying the presence of purulent vaginal discharge (PVD) and ultrasonographic endometritis (UE). The objectives of our study were to obtain prevalence estimates for RTD diagnosed by 2 methods (PVD and UE scoring) and to investigate the risk factors for increased probability of RTD if these methods are used in isolation or in combination. Our retrospective observational cohort study tested the hypothesis that RTD assessed by 2 methods would have similar risk factors, and that those would be mainly cow- and calving-related factors. We analyzed data from 5,049 pre-breeding examinations (PBE) from 2,460 spring-calved cows on 8 farms between 2014 and 2018. Cow-related details assessed were days in milk at PBE, breed, lactation number, dry period length, body condition score at calving and PBE, 305-d milk yield, predicted transmitting ability for production and fertility, the presence of a corpus luteum at PBE, and positive diagnosis the previous year. Calving details assessed were type of sire, calf sex, twinning, stillbirth, calving difficulty score, and retained fetal membranes. We conducted statistical analyses using 4 multivariable logistic regression models to identify the risk of RTD diagnosed by (1) PVD in isolation, (2) UE in isolation, (3) the presence of either PVD or UE; and (4) the presence of both PVD and UE. We accounted for herd, cow, and year as random effects in all 4 models. The overall prevalence of RTD in models 1, 2, 3, and 4 were 7.5, 6.7, 11.6, and 2.6%, respectively. Days in milk at PBE, the interaction between days in milk and retained fetal membranes, twinning, and the predicted transmitting ability for calving interval were consistently significant risk factors for positive scores in all 4 models. Considerable calving difficulty [adjusted odds ratio (AOR) = 13.64], Holstein Friesian dam breed (AOR = 2.58), first lactation (AOR = 2.39), and body condition score at PBE (AOR = 1.64) were risk factors for a positive PVD score but not for a positive UE score. Fifth lactation (AOR = 1.69), a beef-sired calf (AOR = 1.46), and the absence of a corpus luteum at PBE (AOR = 1.57) were risk factors for a positive UE score but not for a positive PVD score. These results support the hypothesis that most of the risk factors for PVD and UE are the same but some are distinctly different, implying that in some instances the 2 methods diagnose separate components of the RTD complex. [ABSTRACT FROM AUTHOR]

Nutrient management on grazed grasslands is of critical importance to maintain productivity levels, as grass is the cheapest feed for ruminants and underpins these meat and milk production systems. Many attempts have been made to model the relationships between controllable (crop and soil fertility management) and noncontrollable influencing factors (weather, soil drainage) and nutrient/productivity levels. However, to the best of our knowledge not much research has been performed on modeling the interconnections between the influencing factors on one hand and nutrient uptake/herbage production on the other hand, by using data-driven modeling techniques. Our paper proposes to use predictive clustering trees (PCT) learned for building models on data from dairy farms in the Republic of Ireland. The PCT models show good accuracy in estimating herbage production and nutrient uptake. They are also interpretable and are found to embody knowledge that is in accordance with existing theoretical understanding of the task at hand. Moreover, if we combine more PCT into an ensemble of PCT (random forest of PCT), we can achieve improved accuracy of the estimates. In practical terms, the number of grazings, which is related proportionally with soil drainage class, is one of the most important factors that moderates the herbage production potential and nutrient uptake. Furthermore, we found the nutrient (N, P, and K) uptake and herbage nutrient concentration to be conservative in fields that had medium yield potential (11 t of dry matter per hectare on average), whereas nutrient uptake was more variable and potentially limiting in fields that had higher and lower herbage production. Our models also show that phosphorus is the most limiting nutrient for herbage production across the fields on these Irish dairy farms, followed by nitrogen and potassium. [ABSTRACT FROM AUTHOR]

Cows’health is the foundation of large scale dairy farm’development. How to monitor cows accurately and management efficiently is important to the development of scale dairy farm. In the spring of 2018, 17 high-yielding Holstein lactation cows were selected from the same group of Anxing dairy farm in Hulin city for experimental study. The sample cows’average weight (500±50) kg and lactation age (203±83) days. The average daily milk yield of each cow was (30±2) kg. Materials selected for this experiment include lactating cows, computers, cow collars (MooMonitor+, Dairymaster, Ireland), data base stations, and amazon cloud storage terminal. The cows and computer were provided by Anxing dairy farm. The cow collar and data base station were provided by Dairy Master company in Ireland, and the cow collar is equipped with the MEMS (micro electro-mechanical system) accelerometer, according to the principle of accelerometer sensor technology, big data clustering analysis was carried out for the time of acceleration changes in different directions, and the position of cows was tracked through RFID tags to monitor the activity behavior of cows. Refer to the number of samples selected by domestic and foreign scholars related to cow feeding behavior, ruminant behavior, reclining and resting behavior and estrus behavior. From April 1, 2018 to May 31, 2018, Dairymaster’s Moonmonitor + information collection system was used to monitor and collect test data of 17 cows’behavior time every day (24h) in Anxing dairy farm, and physical health conditions of the cows were recorded the worker at the same time, such as mastitis, lameness, diarrhea and trauma. During the test period, test data were downloaded from the cloud data storage server through the monitor system at 08:00 am every day for 61 days. The data collection interval was 24 h, the downloaded data includes the rest time (min/24 h), rumination time (min/24 h) and feeding time (min/24 h) of the cows, and 1 037 data records were obtained. And 937 data were randomly selected as training data set, one hundred data were randomly selected as validation data to verify the model prediction. Then, binary logistic regression analysis method and statistical analysis software SPSS23.0 were used to study the collected data. In order to meet the binary logistic regression analysis conditions, the different behaviors time were converted into classification variables. The independent variables of binomial Logistic regression model were entered by force method. The entry criteria of variables was α<0.05, and the exclusion standard was α>0.1. The results showed that: 1) The behavior time changed differently in different cows, and the average rest time changed greatly. The average rest time during abnormal behavior period increased by 25.7% compared with that during normal behavior period. Compared with the normal behavior period, the ruminant time and feeding time during abnormal behavior period decreased by 12.7% and 2.3%, respectively. 2) The behavior time of healthy Holstein lactation cows was normally distributed, with an average rest time of 300-600 min, ruminant time of 400-700 min and feeding time of 200-400 min per day (24 h). The behavior time of abnormal cows was distributed discreetly without obvious distribution rule. 3) Rest time and feeding time are the main influencing factors of the prediction model, among which feeding time had a greater influence on the prediction probability of the model than rest time. When other conditions remain unchanged, the prediction probability change of abnormal behavior of cows increased by 4.2 times for one additional unit of feeding time. Compared with the results of human visual observation, the prediction accuracy of the model was 91%. Therefore, the paper can provide a reference for scientific and accurate management of modern large-scale dairy farms. [ABSTRACT FROM AUTHOR]

• The model predicted annual farm-level electricity consumption to within 10.4%. • The model predicted catchment-level electricity consumption to within 5.0%. • Electricity use per litre reduced as herd size and milk production increased. • Electricity savings due to milk pre-cooling reduced as farm size increased. This 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. [ABSTRACT FROM AUTHOR]

In Ireland, milk is primarily produced using a spring-calving grass-based system, with the use of concentrate supplementation mainly when pasture availability and quality are reduced. In the autumn, when cows are in late lactation, reduced pasture productivity results in reduced milk yield and altered milk composition. Nitrogen utilization efficiency also reduces as lactation progresses. Concentrate supplementation has been found to increase milk production and reduce nitrogen (N) excretion, as high-N grass is usually replaced by a lower-N supplement; however, there is a paucity of information with regard to the optimum type of supplementation in late lactation. Therefore, the objective of this research is to investigate the effect of different concentrate supplementation types, based on barley or maize, on milk production, dry matter intake (DMI), rumen fermentation, and N excretion in late-lactation, spring-calving, grazing dairy cows. Thirty-six Holstein Friesian dairy cows were blocked on days in milk (185 DIM) and balanced for parity, pre-experimental milk yield, milk composition, and body condition score. Cows were randomly assigned to 1 of 3 dietary treatments in a randomized complete block design (n = 12). The 3 treatments consisted of a perennial ryegrass-based pasture-only (PO) treatment and pasture plus either of 2 supplementary concentrates, based on barley (PB) or maize (PM). The diets were fed for a 14-d acclimatization period and then for a further 63-d experimental period. Cows offered PO had a lower daily milk yield (15.1 kg) than PB (18.2 kg) or PM (16.8 kg). Similarly, PO had lower daily milk solids yield (1.46 kg) than PB or PM (1.68 and 1.53 kg, respectively). Cows offered PB had a greater milk yield and higher fat and protein yields than those offered PM. Offering PB increased total DMI (19.5 kg) compared with PO (17.7 kg), and milk response to concentrates was also greater for PB compared with PM (1.21 vs. 0.71 kg of milk per kg of concentrate). Cows offered PB had increased N in milk compared with PO. In conclusion, concentrate supplementation based on barley or maize resulted in increased milk and milk solids yield compared with offering PO. Cows offered barley had a greater response to concentrates and increased milk and milk solids yield in comparison to maize and showed increased N partitioning in milk compared with PO. A barley-based concentrate increased total DMI compared with PO. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the effect of treating cows with teat sealant only compared with antibiotic plus teat sealant at drying off on weekly somatic cell count, potential intramammary infection, and milk production across the entire subsequent lactation. In 3 research herds in the south of Ireland, cows with SCC that did not exceed 200,000 cells/mL in the previous lactation (LowSCC) were randomly assigned to 1 of 2 treatments at drying off: internal teat sealant alone (ITS) or antibiotic plus teat sealant (AB+ITS). Cows with SCC that exceeded 200,000 cells/mL in the previous lactation were treated with AB+ITS and included in the analyses as a separate group (HighSCC). Weekly individual animal composite SCC records were available for 654 cow lactations and were transformed to somatic cell scores (SCS) for the purpose of analysis. Data were divided into 3 data sets to represent records obtained (1) up to 35 DIM, (2) up to 120 DIM, and (3) across the lactation. Foremilk secretions were taken from all quarters at drying off, at calving, 2 wk after calving, and in mid-lactation and were cultured to detect the presence of bacteria. The LowSCC cows treated with ITS alone had higher daily milk yield (0.67 kg/d) across lactation compared with LowSCC cows treated with AB+ITS. The LowSCC cows treated with ITS alone had higher SCS in early, up to mid, and across lactation compared with LowSCC cows treated with AB+ITS. We detected no difference in weekly SCS of LowSCC cows treated with ITS alone and SCS of HighSCC cows. The least squares means back-transformed SCC across lactation of the LowSCC cows treated with ITS alone, LowSCC cows treated with AB+ITS, and HighSCC cows were 41,523, 34,001, and 38,939 cells/mL respectively. The odds of LowSCC cows treated with ITS alone having bacteria present in their foremilk across lactation was 2.7 (95% confidence interval: 1.91 to 3.85) and 1.6 (1.22 to 2.03) times the odds of LowSCC cows treated with AB+ITS and of HighSCC cows treated with AB+ITS, respectively. In this study, Staphylococcus aureus was the most prevalent pathogen isolated from the population. Recategorizing the threshold for LowSCC cows as ≤150,000 cells/mL or ≤100,000 cells/mL in the previous lactation had no effect on the results. The results indicate that herds with good mastitis control programs may use ITS alone at dry-off in cows with SCC <200,000 cells/mL across lactation with only a small effect on herd SCC. [ABSTRACT FROM AUTHOR]

In 2015, the milk quota system that is in place in Europe is to be abolished, instigating an increase in milk production. This increase will aid in addressing the world's ever growing demand for food, but will incur increased stresses on the environmental impact and sustainability of the dairy industry. In this paper, an environmental life cycle assessment, which is performed in order to estimate the global warming potential (GWP) associated with 11 dairy products in the Republic of Ireland, is presented. The primary aim of the study is to examine the GWP associated with the processing of raw milk into the various products. However, the GWP contribution from dairy farms producing the raw milk is also included. Therefore, the system boundary utilised in this study is cradle-to-processing factory gate (dairy, farm, raw milk transportation and dairy processing). Furthermore, when performing the analysis, the 11 dairy products are clustered into 6 product groups: fluid milk (whole milk, skimmed and semi-skimmed milk); butter; cheese; cream; milk powders (buttermilk powders, whole milk powders, skimmed milk powders, and chocolate crumb); and whey powders (whey powders and proteins). The total GWP was calculated for each product group and mass allocation was used to derive the GWP of each product within that group. Data from 12 companies (18 dairy processing plants), which account for approximately 92% of the cow's milk processed in the Republic of Ireland, was used in this study to accurately assess the Irish dairy processing industry. From the analysis, it was found that raw milk production accounted for between 80.8% and 97.3% of the total GWP, depending on the amount of raw milk per kg of product. Additionally, raw milk transportation accounted for approximately 0.4% of the GWP, with the remainder contributed by the processing phase. The main contributor to GWP in the processing phase was direct energy use within the plant (electricity, natural gas and other fuel), which accounts for between 91 and 98% of the GWP, depending on the product. Furthermore, even though raw milk production is the most significant contributor to the total GWP of each dairy product, it was observed that energy use and water consumption in the processing phase were of the same magnitude as that of the production phase. [ABSTRACT FROM AUTHOR]

The environmental status of many European estuaries has improved in recent years as a result of the implementation of a range of different legislative measures. Better municipal waste water treatment and a reduction in the application of inorganic and organic fertiliser to agricultural lands are the main reasons for these improvements. It is anticipated, however, that the ending of the EU milk quota in 2015, and the proposed enlargement of the European dairy sector will lead to a market-driven increase in milk production through an increase in animal numbers and higher productivity. This new production is likely to lead to an increase in pressures with the potential to impact on the quality of surface waters, including estuarine waters. In this paper we focus on the Blackwater estuary in southern Ireland which has seen a marked improvement in water quality due to a reduction in riverine nutrient inputs of phosphorus and nitrogen. A bio-physical model is used to test nutrient-input scenarios likely to represent the range of nutrient loadings that may arise as a result of increased agricultural production. The outputs from these different scenarios are used to assess if recent improvements in estuarine water quality will be undermined or even negated by the proposed expansion of the Irish dairy sector. Appropriate management options to address these potential impacts are discussed. [ABSTRACT FROM AUTHOR]

The abolition of the milk quota system that was in place in Europe was abolished in 2015, which instigated an immediate increase in milk production in many European countries. This increase will aid in addressing the world's ever growing demand for food, but will incur increased stresses on the environmental impact and sustainability of the dairy industry. In this study, an environmental life cycle assessment was performed in order to estimate the environmental impacts associated with the manufacture of milk powder and butter in the Republic of Ireland. A farm gate to processing factory gate analysis, which includes raw milk transportation, processing into each product and packaging, is assessed in this study. Operational data was obtained from 5 dairy processing factories that produce milk powder (4 of which also produce butter). Results for each environmental impact category are presented per kilogram of product. Energy consumption (raw milk transportation and on-site electrical and thermal energy usage) contributes, on average, 89% and 78% of the total global warming potential, for milk powder and butter respectively, for the life cycle stages assessed. Similarly, energy consumption contributes, on average, 86% and 96% of the total terrestrial acidification potential for milk powder and butter respectively, for these life cycle stages. Emissions associated with wastewater treatment contribute approximately 10% and 40% to the total freshwater eutrophication potential and marine eutrophication potential, respectively, for both milk powder and butter production. In addition, packaging materials also has a significant contribution to these environmental impact categories for butter production. Results were also presented for three milk powder products being manufactured by the factories surveyed: skim milk powder, whole milk powder and full fat milk powder. The analysis presented in this paper helps to identify opportunities to reduce the environmental impacts associated with post-farm processing of milk powder and butter. [ABSTRACT FROM AUTHOR]

A 3 year (2009–2011) study found a mean N balance of 166 kg N/ha, P balance of 4.93 kg P/ha, N use efficiency of 0.24, P use efficiency of 0.71, and net profit of €598/ha on 19 Irish dairy farms. The increase in mean net profit with mean milk receipts and the decrease with mean expenditure on chemical fertilisers imply that increasing milk receipts while optimising the use of chemical fertiliser input can be an effective strategy to increase net profit. Mean net profit was not directly related to mean N and P balances or N and P use efficiencies. However, there was an indirect link between net profit and N and P use efficiencies, as indicated through significant relationships between N and P use in the form of chemical fertilisers and feeds and the associated expenditures on chemical fertilisers and feeds. The increase of mean expenditure on feeds (concentrate, forages) with mean SR (stocking rate) and feed N input highlights the importance of matching SR with the feed imports on grass-based dairy farms, when there is limited availability of grassland area. This can be an effective strategy to control expenditure on feeds, with potential positive impact on net profit. Results of the sensitivity analysis indicated that milk price was the main driver for changes in net profit in high and low milk price situations investigated across nine price scenarios. The decrease in mean (51.4 l/kg N) N-eco-efficiency (milk produced per kilogram N balance) with mean fertiliser N input (190 kg N/ha) implies that efficient on-farm N management is needed to achieve increases in milk production and reduce N balance per unit product (litre milk). Potential fertiliser N replacement values of €317/ha for the spring and €64/ha for summer slurry application may represent strong incentives for farmers to make increased use of organic fertilisers, as part of overall on-farm N management. This can have positive impacts on farm nutrient use efficiency and farm net profit. Eight farms exceeding the limit of 2 livestock units (LU)/ha, imposed through the Nitrates Directive, had 1.63 times higher net profit compared with the remainder, which justified the cost of compliance associated with being in derogation. The results of this study generally indicate that Irish dairy farms, as low-input production systems, have the potential to improve both economic (as indicated by net profit per hectare) and environmental (as indicated by N and P balances per hectare, N and P use efficiencies and N-eco-efficiency) sustainability. [ABSTRACT FROM AUTHOR]

In the last decade and a half, emerging vector-borne diseases have become a substantial threat to cattle across Europe. To mitigate the impact of the emergence of new diseases, outbreaks must be detected early. However, the clinical signs associated with many diseases may be nonspecific. Furthermore, there is often a delay in the development of new diagnostic tests for novel pathogens which limits the ability to detect emerging disease in the initial stages. Syndromic Surveillance has been proposed as an additional surveillance method that could augment traditional methods by detecting aberrations in non-specific disease indicators. The aim of this study was to develop a syndromic surveillance system for Irish dairy herds based on routinely collected milk recording and meteorological data. We sought to determine whether the system would have detected the 2012 Schmallenberg virus (SBV) incursion into Ireland earlier than conventional surveillance methods. Using 7,743,138 milk recordings from 730,724 cows in 7037 herds between 2007 and 2012, linear mixed-effects models were developed to predict milk yield and alarms generated with temporally clustered deviations from predicted values. Additionally, hotspot spatial analyses were conducted at corresponding time points. Using a range of thresholds, our model generated alarms throughout September 2012, between 4 and 6 weeks prior to the first laboratory confirmation of SBV in Ireland. This system for monitoring milk yield represents both a potentially useful tool for early detection of disease, and a valuable foundation for developing similar tools using other metrics. [ABSTRACT FROM AUTHOR]

While the impending review of the European Union (EU) Common Agricultural Policy (CAP) is set to have an impact on all farming sectors across Europe, particularly transformative change is sought by policies relating to dairy farmers. EU milk quota abolition in 2015 will fundamentally revise the terms of dairy production, transitioning from policies of subsidy and protection to a scenario where farmers will produce milk on the open market. Dairy quota abolition essentially represents an economic but also socio-cultural disruption for a sizeable cohort of farmers, requiring adaptation to more market-driven production strategies. Agricultural policy-makers in EU member states are demonstrably preparing for this imminent change and dairy farmers are considering and strategising their responses at farm-level. Our focus in this paper is the interplay between quota abolition and farm-level decision-making in the pre-abolition period. Drawing from a broader mixed-methodological and multi-disciplinary research project, this paper uses qualitative narrative analysis to identify the key determinants arising in dairy farmers' decision-making processes. How are farmers currently strategising their responses to dairy quota deregulation? Using the qualitative Biographic Narrative Interpretive Method (BNIM), we examine the range of factors determining how a particular group of dairy farmers are strategising their positions on the impending open dairy market. Our analysis highlights how, in the advent of a deregulated dairy production regime, dairy farmers are carefully deliberating their responses at farm level, drawing from policy and market related information, their own personal speculations, and conventional wisdom shared with other members of the farming community. We find that the dairy farmers are influenced not only by motivations to increase productivity and scale but by a tenacious approach to farm sustainability and resilience that is informed by past experiences of farming and seeks to preserve and promote socio-cultural farming values. The paper is of particular interest to policy makers and academics interested in the interchange between policy and farmer behaviour, particularly in the context of current CAP reform. [ABSTRACT FROM AUTHOR]

The article presents the study on the role of genetics in dairy cow fertility in Ireland. The study involved dairy cows in winter milk herds which were examined for milk production and fertility sub-index. Also examined is the method to increase herd genetic merit for fertility, assessment of the genetic merit of a dairy herd, and breeding for high-fertility.

Reducing electricity consumption in Irish milk production is a topical issue for 2 reasons. First, the introduction of a dynamic electricity pricing system, with peak and off-peak prices, will be a reality for 80% of electricity consumers by 2020. The proposed pricing schedule intends to discourage energy consumption during peak periods (i.e., when electricity demand on the national grid is high) and to incentivize energy consumption during off-peak periods. If farmers, for example, carry out their evening milking during the peak period, energy costs may increase, which would affect farm profitability. Second, electricity consumption is identified in contributing to about 25% of energy use along the life cycle of pasture-based milk. The objectives of this study, therefore, were to document electricity use per kilogram of milk sold and to identify strategies that reduce its overall use while maximizing its use in off-peak periods (currently from 0000 to 0900 h). We assessed, therefore, average daily and seasonal trends in electricity consumption on 22 Irish dairy farms, through detailed auditing of electricity-consuming processes. To determine the potential of identified strategies to save energy, we also assessed total energy use of Irish milk, which is the sum of the direct (i.e., energy use on farm) and indirect energy use (i.e., energy needed to produce farm inputs). On average, a total of 31.73 MJ was required to produce 1 kg of milk solids, of which 20% was direct and 80% was indirect energy use. Electricity accounted for 60% of the direct energy use, and mainly resulted from milk cooling (31%), water heating (23%), and milking (20%). Analysis of trends in electricity consumption revealed that 62% of daily electricity was used at peak periods. Electricity use on Irish dairy farms, therefore, is substantial and centered around milk harvesting. To improve the competitiveness of milk production in a dynamic electricity pricing environment, therefore, management changes and technologies are required that decouple energy use during milking processes from peak periods. [ABSTRACT FROM AUTHOR]

Change in lifetime milk yield is an important component of the cost of diseases in dairy cows. Knowledge of the likelihood and scale of potential savings through disease prevention measures is important to evaluate how much expenditure on control measures is rational. The aim of this study was to assess the association between somatic cell count (SCC) at 5 to 30 d in milk during parity 1 (SCC1), and lifetime milk yield for cows in Irish dairy herds. The data set studied included records from 53,652 cows in 5,922 Irish herds. This was split into 2 samples of 2,500 and 3,422 herds at random. Linear models with lifetime milk yield and first-lactation milk yield as the outcomes and random effects to account for variation between herds were fitted to the data for the first sample of herds; data for the second sample were used for cross-validation. The models were developed in a Bayesian framework to include all uncertainty in posterior predictions and parameters were estimated from 10,000 Markov chain Monte Carlo simulations. The final model was a good fit to the data and appeared generalizable to other Irish herds. A unit increase in the natural logarithm of SCC1 was associated with a median decrease in lifetime milk yield of 864 kg, and a median decrease in first-lactation milk yield of 105 kg. To clarify the meaning of the results in context, microsimulation was used to model the trajectory of individual cows, and evaluate the expected outcomes for particular changes in the herd-level prevalence of cows with SCC1 >400,000 cells/mL. Differences in mean lifetime milk yield associated with these changes were multiplied by an estimated gross margin for each cow to give the potential difference in milk revenue. Results were presented as probabilities of savings; for example, a 75% probability of savings of at least €97 or €115/heifer calved into the herd existed if the prevalence of cows with SCC1 ≥400,000 cells/ mL was reduced from ≥20 to <10 or <5%, respectively, and at least €71/heifer calved into the herd if the prevalence of cows with SCC1 ≥400,000 cells/mL was reduced from ≥10 to <5%. The results indicate large differences in lifetime milk yield, depending on SCC early in the first lactation and the findings can be used to assess where specific interventions to control heifer mastitis prepartum are likely to be cost effective. [ABSTRACT FROM AUTHOR]

Ireland plays a key role in contributing to the global supply of dairy produce, and increasing international demand, as well as the abolition of milk quotas in the European Union in 2015, present opportunities for the Irish milk industry. Improving milk quality is required to maximize these opportunities. National action on milk quality is spearheaded by Animal Health Ireland, yet the potential for collective action at an industry level is undermined by the inability of individual stakeholders to accept responsibility for action. In-depth qualitative interviews were conducted with n = 12 stakeholder representatives. The theoretical concepts of collective action (i.e., when a group of people with a shared interest undertake some kind of voluntary common action in pursuit of that shared interest) is applied to understanding the results and identifying a collective way forward. Though consensus is apparent on the need to improve milk quality, differences exist about individual responsibility and the best way to achieve higher quality standards. The propensity for collective action is undermined by shifting responsibility to other stakeholders, stakeholder positions, trust concerns, and concerns over the commitment of other stakeholders to cooperate. Understanding how collective action works provides Animal Health Ireland with a knowledge framework in which to build stakeholder consensus. The paper concludes with practical examples of how Animal Health Ireland continues to apply this understanding by bringing individual stakeholders together to achieve milk quality improvement. [ABSTRACT FROM AUTHOR]

Given the imminent removal of milk quota in 2015, EU dairy farmers will be able to expand production without purchasing milk quota rights for the first time in 30 years. This paper uses Irish National Farm Survey data to simulate the expansion capacity of Irish dairy farms. Specifically, the likelihood of achieving the 50% increase in production target published in the Irish Government's Food Harvest 2020 Report is explored. Potential milk output is estimated accounting for structural change and the economic viability of production under three price scenarios for 2020. In addition, the number of new entrants that would be required to meet the 50% target is calculated. The results indicate that the 50% output volume growth target set in the Food Harvest report will be difficult to achieve and that future potential milk output depends importantly on the rate of structural change and productivity growth as well as on real milk prices in 2020. A regional analysis reveals that relative to other regions, the south has the greatest expansion capacity. This suggests that quota removal could cause significant regional restructuring of milk production, which is likely to present some challenges to the dairy processing sector. [ABSTRACT FROM AUTHOR]

The objective of this study was to compare the biological and economic efficiencies of 2 likely future pasture-based systems of milk production differing in overall stocking rate and concentrate supplementation level on a wetland drumlin soil in the Border Midlands Western region of Ireland. Physical performance data were obtained from a 3-yr systems comparison at Ballyhaise College, Co. Cavan, comparing 2 production systems: a high grass (HG) system (578 kg of concentrate/ cow at 2.45 livestock units per hectare) and a high intensity (HI) system (1,365 kg of concentrate/cow at 2.92 livestock units/ha). Animal production data were analyzed using a mixed model, with feed system, year, and parity included as fixed effects in the final model. Feed system had a significant effect on all yield variables with higher yields in the HI system. Production system had no significant influence on reproductive performance. The Moorepark Dairy Systems Model, a stochastic budgetary simulation model, was used to simulate a model farm integrating biological data from each feed system to identify the economic effect of each system at 3 future milk prices of 22, 27, and 33 euro cents per liter (€c/L). Two economic scenarios were investigated within the model: scenario 1 (S1) assumed fixed cow numbers (n = 55 cows) and scenario 2 (S2) assumed fixed land area (n = 40 ha). At a milk price of 27 or 33 €c/L, profit per cow, per kilogram of milk solids, and per hectare were similar for HG and HI in S1 and higher for HI in S2. At a milk price of 22 €c/L, all systems were unprofitable, with increased losses realized in the HI system (both S1 and S2) compared with the HG system. Pasture-based systems of milk production in the northern region of Ireland are capable of highly efficient and profitable milk production. Moreover, the efficacy of increased supplementation to remove the constraints of pasture seasonality will depend on the cost of supplementation and the price paid for additional milk produced. [ABSTRACT FROM AUTHOR]

A nutritional evaluation of an Irish dairy herd indicated gross overfeeding of late lactation cows, over-conditioning of cows at parturition and a high rate of body condition loss in early lactation. Metabolisable-energy based nutritional modelling software was used to guide recommended dietary changes to prevent excessive condition gain in late lactation. Immediately following the implementation of the changes there was an unexpected reduction in performance affecting both milk yield and protein concentration. An investigation into the poor performance revealed underestimation of peak milk yield; over-estimation of maize silage quality; a large difference in the concentrate being fed compared to the concentrate recommended, and failure of the blend of concentrate ingredients to maintain the intended proportions in the in-parlour feeding system. The estimated maximum cumulative effect of these errors was to cause undersupply of energy and protein in the recommended diet of 16% and 3% respectively to cows in early lactation. Use of a net-energy nutritional model would have indicated a requirement for a higher energy supply in this case. This report highlights the challenges in obtaining accurate on-farm data for use in dairy cow nutritional models. [ABSTRACT FROM AUTHOR]

The provision of grass for early spring grazing in Ireland is critical for spring calving grass-based milk production systems. This experiment investigated the effect of a range of autumn closing dates (CD), on herbage mass (kg DM ha−1), leaf area index (LAI) and tiller density (m−2) during winter and early spring. Thirty-six grazing paddocks, closed from 23 September to 1 December 2007, were grouped to create five mean CD treatments – 29 September, 13 October, 27 October, 10 November, 24 November. Herbage mass, tiller density and LAI were measured every 3 weeks from 28 November 2007 to 20 February 2008; additionally, herbage mass was measured prior to initial spring grazing and tiller density was measured intermittently until September 2008. Delaying CD until November significantly ( P < 0·05) reduced herbage mass (by approximately 500 kg DM ha−1) and LAI (by approximately 0·86 units) in mid-February. On average, 35% of herbage mass present on swards on 20 February was grown between 28 November and 30 January. LAI was positively correlated with herbage mass ( R2 = 0·78). Herbage mass increased by approximately 1000 kg DM ha−1 as spring grazing was delayed from February to April. Tiller density increased from November to February, although it did fluctuate, and it was greatest in April (9930 m−2). This experiment concludes that in the south of Ireland adequate herbage mass for grazing in early spring can be achieved by delaying closing to early mid-October; swards required for grazing after mid-March can be closed during November. [ABSTRACT FROM AUTHOR]

Abstract: This study describes the relationship between bovine tuberculosis (TB) and milk yield in TB-infected dairy herds in Ireland. The study had two objectives: to determine whether cows detected as TB reactors (and thus subject to immediate slaughter) were likely to be the higher milk-producing cows, and to determine whether subclinical TB infection was associated with reduced milk production at or around the time of disclosure (detection). All Irish dairy herds restricted from trading between the 1st June 2004 and the 31st May 2005 as a result of two or more TB reactors by the Single Intradermal Comparative Tuberculin Test (SICTT) were considered for study. The data consisted of 419 herds. Data were collected on all TB reactors and a random sample of 5 non-reactor cows in these herds: a data set of 4340 cows (2342 TB reactors and 1998 non-reactors). Previous milk data for the cows were taken into consideration and thus all lactations on a cow were analysed together with the years of lactations. There was an inherent hierarchical structure in the data, with lactations nested within cows and cows within herds and thus a linear mixed model with two random effects was used to describe the data. The results of this study showed that for all lactations and years under investigation, milk yield was significantly lower for TB reactor cows, with differences ranging from 120kg (2003, lactation 3) to 573kg (2001, lactation 1), when compared to the non-reactor cows. [Copyright &y& Elsevier]

The degree of relatedness was studied in 3 dairy cow populations from Great Britain (GBR), Italy (ITA), and Ireland (IRL) by using cows born from 2003 to 2006. Effective population size, inbreeding coefficient (F), and average relationship in the top and bottom 4,000 cows ranked on a profit index value (PIV) or milk yield evaluations were studied. Average inbreeding was approximately 2% in GBR and ITA, was 1% in IRL, but was slightly more than 2% when the joint pedigree was used. The average F for the joint population was 10 to 15% higher than estimates averaged across the 3 populations, reflecting the increased completeness of pedigree information in the joint pedigree. Effective population size in the joint pedigree was approximately 12% lower than estimates within the individual countries. The average genetic relationships for the top 4,000 PIV cows were not markedly different from those based on milk evaluation in GBR and ITA, but were approximately 2% lower in IRL. This was due to the use of an index with less weight on production traits in IRL compared with GBR and ITA. However, selection of the top 4,000 cows on PIV reduced the degree of relatedness across the 3 countries. The use of common sires accounted for most of the relatedness across the 3 countries, more than did the use of related sires or common foreign dams. [ABSTRACT FROM AUTHOR]

Johne's disease (JD) is caused by infection with the organism Mycobacterium avium spp. paratuberculosis, leading to chronic diarrhoea and ill thrift in adult cattle. JD is considered to adversely affect farm performance and profitability. This retrospective case study was undertaken on a single commercial dairy herd in the south west of Ireland. Animal production records were interrogated to assess the effect of JD on milk yield (total kg per lactation), somatic cell count (the geometric mean over the lactation), reasons for culling, cull price and changes in herd parity structure over time. JD groups were defined using clinical signs and test results. One control animal was matched to each case animal on parity number and year. Specific lactations (clinical, pre-clinical and test-positive only) from 1994 to 2004 were compared between JD case and control cows. A significantly lower milk yield (1259.3 kg/lactation) was noted from cows with clinical JD in comparison to their matched control group. Clinical anim als had an average cull price of £516 less than animals culled without signs of clinical disease. In contrast, little effect was noted for sub-clinical infections. These direct effects of JD infections, in combination with increased culling for infertility and increasing replacement rates, had a negative impact on farm production. Results from this study provide preliminary information regarding the effects of JD status on both herd and animal-level performance in Ireland. [ABSTRACT FROM AUTHOR]

Abstract: Little is known about the association between age at first calving and subsequent performance in seasonal calving dairy production systems where grazed grass constitutes the majority of the basal diet. The objective of this study was to quantify, using the Irish national database, the association between age at first calving and subsequent milk production, calving performance, fertility and survival in grazing, seasonal-calving Holstein–Friesian dairy cows. Median age at first calving from a population of 196,120 animals varied from 751 to 764 days across the years 2000 to 2006, inclusive while age at first calving ranged from 660 days to 1156 days. A frequency distribution of age at first calving revealed a large peak coinciding with approximately 24 and a smaller peak at approximately 36 months of age. Associations with age at first calving were undertaken on between 6338 and 50,786 animals. First lactation 305-day yield of milk, fat and protein decreased almost linearly by 55.5 kg, 0.6 kg and 2.3 kg, respectively for each month earlier at first calving. Although heifers calving younger for the first time had a greater likelihood of requiring some assistance at calving there was no association between age at first calving and risk of severe assistance at first calving. Age at first calving was associated with survival to second, third, fourth and fifth parity with no association with survival to sixth parity; heifers calving at 24 months of age had generally the greatest odds of survival to older parities with heifers calving at approximately 3 years of age having lower odds. [Copyright &y& Elsevier]

A dairy cow system simulator, Dairy_sim, designed for assessing the interaction of climate and management on dairy cow production, based on rotational grass grazing, was further developed by integrating a soil water model. The soil water model was based on the concept of soil water deficits, and influenced the growth of grass herbage in the simulator when there was an excess of water over field capacity and when water content in the soil was approaching wilting point. The soil water model was tested using baseline meteorological data (1961–1990) and then the system simulation was parameterized and tested for poorly drained soils using data from a research farm in the west of Ireland. After testing, the effects of regional differences in climate on system management on well- and poorly drained soils were compared. Down-scaled Global Climate Model (GCM) data for the baseline years (1961–1990) were used for this purpose. These data resulted in slightly more favourable weather than that recorded. It was found that the simulator was capable of generating results in good agreement with published data for dairy production on poorly drained soils. The regional analysis showed dairy farms on well-drained soils out-performed their equivalents on poorly drained soils and, in general, were able to sustain higher stocking rates by 0·6–0·9 cows ha−1. Dry matter production was around 1·5–3 t ha−1 greater per annum on well-drained soils compared to poorly drained soils. The simulator, Dairy_sim, also captured a large difference in the requirement for housing and forage between the well and poorly drained soils. The simulation model can now be used to evaluate interactions between soils, systems and weather, and is thus a more useful tool for developing practical advice and for evaluating the impacts of possible climate change. [ABSTRACT FROM AUTHOR]

The objective of this study was to detect abnormal recordings of milk yield, fat concentration and protein concentration in Irish milk-recorded data. The data consisted of 14,956 records from both commercial and experimental herds with 92% of the recordings recorded manually and the remainder recorded electronically. The method used in this paper was a modified version of the method employed by the Animal Improvement Programs Laboratory in Maryland, USA and conformed with the guidelines outlined by the International Committee of Animal Recording. The results illustrate the effectiveness of detecting abnormal recordings in Irish milk records. The method described in this paper, defines the upper and lower limits for each production trait and these limits along with the slope parameters were used to determine if a recording was abnormal or not. Three percent of milk yield recordings, 5% of fat concentration recordings and less than 1% of protein concentration recordings were found to be abnormal. The proportion of values declared abnormal in manually recorded and electronically recorded data were examined and found to be significantly different for fat concentration. [ABSTRACT FROM AUTHOR]

The objective of this study was to estimate genetic parameters for grass dry matter intake (DMI), energy balance (EB), and cow internal digestibility (IDG) in grazing Holstein-Friesian dairy cows. Grass DMI was estimated up to 4 times per lactation on 1,588 lactations from 755 cows on 2 research farms in southern Ireland. Simultaneously measured milk production and BW records were used to calculate EB. Cow IDG, measured as the ratio of feed and fecal concentrations of the natural odd carbon-chain n-alkane pentatriacontane, was available on 583 lactations from 238 cows. Random regression and multitrait animal models were used to estimate residual, additive genetic and permanent environmental (co)variances across lactations. Results were similar for both models. Heritability for DMI, EB, and IDG across lactation varied from 0.10 [8 days in milk (DIM)] to 0.30 (169 DIM), from 0.06 (29 DIM) to 0.29 (305 DIM), and from 0.08 (50 DIM) to 0.45 (305 DIM), respectively, when estimated using the random regression model. Genetic correlations within each trait tended to decrease as the interval between periods compared increased for DMI and EB, whereas the correlations with IDG in early lactation were weakest when measured midlactation. The lowest correlation between any 2 periods was 0.10, -0.36, and -0.04 for DMI, EB, and IDG, respectively, suggesting the effect of different genes at different stages of lactations. Eigenvalues and associated eigenfunctions of the additive genetic covariance matrix revealed considerable genetic variation among animals in the shape of the lactation profiles for DMI, EB, and IDG. Genetic parameters presented are the first estimates from dairy cows fed predominantly grazed grass and imply that genetic improvement in DMI, EB, and IDG in Holstein-Friesian cows fed predominantly grazed grass is possible. [ABSTRACT FROM AUTHOR]

The article presents a perspective on issues concerning the decline in diary herd fertility in Ireland and other countries. It has been concluded that the decline in dairy herd fertility internationally has highlighted the limited impact of traditional veterinary approaches to herd fertility. The core role of the veterinarian remains individual animal examinations. However, it must be supplemented with systematic herd fertility investigation and veterinarian-led herd fertility management.