• Adding value to cull cow beef

      O'Donovan, Michael; Minchin, William; Buckley, Frank; Kenny, David A.; Shalloo, Laurence (Teagasc, 01/08/2009)
      This project addressed the prospects of increasing the value of cull cow beef and examined the potential of a number of different management and dietary strategies. In Ireland, the national cow herd contributes 350,000 animals to total beef production annually, which represents 22% of all cattle slaughtered (DAF, 2007). A dominant feature of beef production in Ireland is the disposal of cows from the dairy and beef industries, the time of year at which culling occurs influences the number of cows available for slaughter. Suitability of a cow for slaughter is generally not a consideration for dairy or beef farmers.
    • An Analysis of Abatement Potential of Greenhouse Gas Emissions in Irish Agriculture 2021-2030

      Lanigan, Gary; Donnellan, Trevor; Hanrahan, Kevin; Carsten, Paul; Shalloo, Laurence; Krol, Dominika; Forrestal, Patrick J.; Farrelly, Niall; O’Brien, Donal; Ryan, Mary; et al. (Teagasc, 2018-06-10)
      This report has been prepared by the Teagasc Working Group on GHG Emissions, which brings together and integrates the extensive and diverse range of organisational expertise on agricultural greenhouse gases. The previous Teagasc GHG MACC was published in 2012 in response to both the EU Climate and Energy Package and related Effort Sharing Decision and in the context of the establishment of the Food Harvest 2020 production targets.
    • Application of data envelopment analysis to measure technical efficiency on a sample of Irish dairy farms

      Kelly, Eoin; Shalloo, Laurence; Geary, Una; Kinsella, Anne; Wallace, Michael (Teagasc, 2012-12)
      The aim of this study was to determine the levels of technical efficiency on a sample of Irish dairy farms utilizing Data Envelopment Analysis (DEA) and to identify key management and production factors that differ between producers indentified as efficient and inefficient. DEA was used in this study to generate technical efficiency scores under assumptions of both constant returns to scale (CRS) and variable returns to scale (VRS). The average technical efficiency score was 0.785 under CRS and 0.833 under VRS. Key production characteristics of efficient and inefficient producers were compared using an analysis of variance. More technically efficient producers used less input per unit of output, had higher production per cow and per hectare and had a longer grazing season, a higher milk quality standard, were more likely to have participated in milk recording and had greater land quality compared to the inefficient producers.
    • Associating cow characteristics with mobility scores in pasture-based dairy cows

      O'Connor, Aisling; Bokkers, Eddie A.M.; de Boer, Imke J. M.; Hogeveen, Henk; Sayers, Riona; Byrne, Nicky; Ruelle, Elodie; Shalloo, Laurence; Department of Agriculture, Food and the Marine; Teagasc Walsh Fellowship Programme; et al. (Elsevier, 2019-07-10)
      The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.
    • Associating cow characteristics with mobility scores in pasture-based dairy cows

      O'Connor, Aisling; Bokkers, E.A.M.; de Boer, I.J.M.; Hogeveen, H.; Sayers, Riona; Byrne, Nicky; Ruelle, Elodie; Shalloo, Laurence; Irish Department of Agriculture, Food and the Marine; Teagasc Walsh Fellowship Programme (Elsevier for American Dairy Science Association, 2019-07-10)
      The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.
    • Associating cow characteristics with mobility scores in pasture-based dairy cows

      Bokkers, E.A.M.; de Boer, I.J.M.; Hogeveen, H.; Sayers, Riona; Byrne, N.; Ruelle, Elodie; Shalloo, Laurence; Department of Agriculture, Food and the Marine; 14 S 801 (Elsevier, 2019-09-30)
      The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.
    • Associations between paratuberculosis ELISA results and test-day records of cows enrolled in the Irish Johne's Disease Control Program

      Botaro, Bruno G.; Ruelle, Elodie; More, Simon J; Strain, Sam; Graham, David A.; O'Flaherty, Joe; Shalloo, Laurence; Department of Agriculture, Food and the Marine (Elsevier, 2017-07-12)
      The effect of the Mycobacterium avium ssp. paratuberculosis (MAP) ELISA status on test-day milk performance of cows from Irish herds enrolled in the pilot national voluntary Johne's disease control program during 2013 to 2015 was estimated. A data set comprising 92,854 cows and 592,623 complete test-day records distributed across 1,700 herds was used in this study. The resulting ELISA outcome (negative, inconclusive, and positive) of each cow within each year of the program was used to allocate the cow into different scenarios representing the MAP status. At MAPscenario1, all cows testing ELISA nonnegative (i.e., inconclusive and positive) were assigned a MAP-positive status; at MAPscenario2 only cows testing ELISA-positive were assigned a MAP-positive status; at MAPscenario3 only cows testing ELISA nonnegative (inconclusive or positive) and gathered exclusively from herds where at least 2 further ELISA nonnegative (inconclusive or positive) cows were found were assigned a MAP-positive status; at MAPscenario4 only cows testing ELISA-positive that were gathered exclusively from herds where at least 2 further ELISA-positive cows were found were assigned a MAP-positive status. Milk outputs based on test-day records were standardized for fat and protein contents (SMY) and the effect of MAP ELISA status on the SMY was estimated by a linear mixed effects model structure. The SMY mean difference recorded at test day between cows with a MAP-positive status and those with a MAP-negative status within MAPscenario1 was estimated at −0.182 kg/test day; the mean difference was −0.297 kg/test day for MAPscenario2; for MAPscenario3 mean difference between MAP-positive status and MAP test-negative cows was −0.209 kg/test day, and for MAPscenario4, the difference was −0.326 kg/test day.
    • Associations between paratuberculosis ELISA results and test-day records of cows enrolled in the Irish Johne's Disease Control Program

      Botaro, Bruno G.; Ruelle, Elodie; More, Simon J.; Strain, Sam; Graham, David A.; O'Flaherty, Joe; Shalloo, Laurence; Department of Agriculture, Food and the Marine (Elsevier for American Dairy Science Association, 2017-07-12)
      The effect of the Mycobacterium avium ssp. paratuberculosis (MAP) ELISA status on test-day milk performance of cows from Irish herds enrolled in the pilot national voluntary Johne’s disease control program during 2013 to 2015 was estimated. A data set comprising 92,854 cows and 592,623 complete test-day records distributed across 1,700 herds was used in this study. The resulting ELISA outcome (negative, inconclusive, and positive) of each cow within each year of the program was used to allocate the cow into different scenarios representing the MAP status. At MAPscenario1, all cows testing ELISA nonnegative (i.e., inconclusive and positive) were assigned a MAP-positive status; at MAPscenario2 only cows testing ELISA-positive were assigned a MAP-positive status; at MAPscenario3 only cows testing ELISA nonnegative (inconclusive or positive) and gathered exclusively from herds where at least 2 further ELISA nonnegative (inconclusive or positive) cows were found were assigned a MAP-positive status; at MAPscenario4 only cows testing ELISA-positive that were gathered exclusively from herds where at least 2 further ELISA-positive cows were found were assigned a MAP-positive status. Milk outputs based on test-day records were standardized for fat and protein contents (SMY) and the effect of MAP ELISA status on the SMY was estimated by a linear mixed effects model structure. The SMY mean difference recorded at test day between cows with a MAP-positive status and those with a MAP-negative status within MAPscenario1 was estimated at −0.182 kg/test day; the mean difference was −0.297 kg/test day for MAPscenario2; for MAPscenario3 mean difference between MAP-positive status and MAP test-negative cows was −0.209 kg/test day, and for MAPscenario4, the difference was −0.326 kg/ test day
    • Associations between paratuberculosis ELISA results and test-day records of cows enrolled in the Irish Johne's Disease Control Program

      Botaro, Bruno G.; Ruelle, Elodie; More, Simon J; Strain, Sam; Graham, David A.; O'Flaherty, Joe; Shalloo, Laurence; Department of Agriculture, Food and the Marine (Elsevier, 2017-07-12)
      The effect of the Mycobacterium avium ssp. paratuberculosis (MAP) ELISA status on test-day milk performance of cows from Irish herds enrolled in the pilot national voluntary Johne's disease control program during 2013 to 2015 was estimated. A data set comprising 92,854 cows and 592,623 complete test-day records distributed across 1,700 herds was used in this study. The resulting ELISA outcome (negative, inconclusive, and positive) of each cow within each year of the program was used to allocate the cow into different scenarios representing the MAP status. At MAPscenario1, all cows testing ELISA nonnegative (i.e., inconclusive and positive) were assigned a MAP-positive status; at MAPscenario2 only cows testing ELISA-positive were assigned a MAP-positive status; at MAPscenario3 only cows testing ELISA nonnegative (inconclusive or positive) and gathered exclusively from herds where at least 2 further ELISA nonnegative (inconclusive or positive) cows were found were assigned a MAP-positive status; at MAPscenario4 only cows testing ELISA-positive that were gathered exclusively from herds where at least 2 further ELISA-positive cows were found were assigned a MAP-positive status. Milk outputs based on test-day records were standardized for fat and protein contents (SMY) and the effect of MAP ELISA status on the SMY was estimated by a linear mixed effects model structure. The SMY mean difference recorded at test day between cows with a MAP-positive status and those with a MAP-negative status within MAPscenario1 was estimated at −0.182 kg/test day; the mean difference was −0.297 kg/test day for MAPscenario2; for MAPscenario3 mean difference between MAP-positive status and MAP test-negative cows was −0.209 kg/test day, and for MAPscenario4, the difference was −0.326 kg/test day.
    • Capturing the economic benefit of Lolium perenne cultivar performance

      McEvoy, Mary; O'Donovan, Michael; Shalloo, Laurence; Department of Agriculture, Food and the Marine (Teagasc (Agriculture and Food Development Authority), Ireland, 2011)
      Economic values were calculated for grass traits of economic importance in Irish grass-based ruminant production systems. Traits considered were those that had the greatest potential to influence the profitability of a grazing system. These were: grass dry matter (DM) yield in spring, mid-season and autumn, grass quality (dry matter digestibility; DMD), 1st and 2nd cut silage DM yield and sward persistency. The Moorepark Dairy Systems Model was used to simulate a dairy farm. Economic values were calculated by simulating the effect of a unit change in the trait of interest while holding all other traits constant. The base scenario involved a fixed herd size and land area (40 ha), and an annual DM yield of 13 t/ha. The economic values generated under the base scenario were: € 0.152/kg for DM yield in spring, € 0.030/kg for DM yield in mid-season and € 0.103/kg for DM yield in autumn; € 0.001, € 0.008, € 0.010, € 0.009, € 0.008 and € 0.006 per 1 g/kg change in DMD for the months of April to September, respectively; € 0.03/kg for 1st cut silage DM yield, € 0.02/kg for 2nd cut silage DM yield; and − € 4.961 for a 1 percent reduction in persistency. Alternative scenarios were examined to determine the sensitivity of the economic values to changes in annual DM yield, sward utilisation and a scenario where silage production was the focus of the system. The economic values were used to calculate a total merit index for each of 20 perennial ryegrass cultivars based on production data from a 3 year plot study. The rank correlation between the merit index values for the cultivars under the base scenario and the scenario involving a reduction in herbage utilisation was 1.0, while that with the scenario involving reduced annual DM yield was 0.94. It is concluded that the total merit index can be used to identify cultivars that can generate the greatest economic contribution to a grass-based production system, regardless of system or intensity of grass production.
    • A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms

      O’Brien, Donal; Judith Louise, Capper; Garnsworthy, Phil; Grainger, Chris; Shalloo, Laurence; European Union; FP7-244983 (Elsevier, 2014-01-17)
      Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity.
    • A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms

      O’Brien, D.; Capper, J.L.; Garnsworthy, P.C.; Grainger, C.; Shalloo, Laurence; European Union; FP7- 244983 (American Dairy Science Association, 2014-03)
      Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energycorrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity.
    • The challenge of sustainability for Irish Agriculture

      Richards, Karl; Hanrahan, Kevin; Shalloo, Laurence; Ryan, Mary; Finnan, John; Murphy, Pat; Lanigan, Gary (2021-08-04)
      Presentation Overview • Introduction to Johnstown Castle • Ireland’s GHG/NH3 challenge • Scenarios for future emissions (without mitigation) • Mitigation pathways • GHG • NH3 • Water quality challenge • ACP highlights • New Ag. Sustainability Support & Advisory Prog.
    • Comparative performance and economic appraisal of Holstein-Friesian, Jersey and Jersey×Holstein-Friesian cows under seasonal pasture-based management

      Prendiville, Robert; Shalloo, Laurence; Pierce, K.M.; Buckley, Frank; Department of Agriculture, Food and the Marine; RSF-06-353 (Teagasc (Agriculture and Food Development Authority), Ireland, 2011)
      The objective of this study was to provide comparative performance data for Holstein- Friesian (HF), Jersey (J) and Jersey×Holstein-Friesian (F1) cows under a seasonal pasture-based management system and to simulate the effect of cow breed on farm profitability. Data for a total of 329 lactations, from 162 (65 HF, 48 J and 49 F1) cows, were available. Milk yield was highest for HF, intermediate for F1 and lowest for J, while milk fat and protein concentrations were highest for J, intermediate for F1 and lowest for HF. Yield of fat plus protein was highest for F1, intermediate for HF and lowest for J. Mean bodyweight was 523, 387 and 466 kg for HF, J and F1, respectively. Body condition score was greater for the J and F1 compared to HF. Reproductive efficiency was similar for the HF and J but superior for the F1. The Moorepark Dairy Systems Model was used to simulate a 40 ha farm integrating biological data for each breed group. Milk output was highest for systems based on HF cows. Total sales of milk solids and, consequently, milk receipts were higher with J and F1 compared to HF. Total costs were lowest with F1 cows, intermediate with HF and highest with J. Overall farm profitability was highest with F1 cows, intermediate with HF and lowest with J. Sensitivity analysis of milk price, fat to protein price ratio and differences in cost of replacement heifers showed no re-ranking of the breed groups for farm profit.
    • A comparison of machine learning techniques for predicting insemination outcome in Irish dairy cows

      Fenlon, Caroline; O'Grady, Luke; Dunnion, John; Shalloo, Laurence; Butler, Stephen; Doherty, Michael L.; Dairy Levy Research Trust (AICS, 2016-09)
      Reproductive performance has an important effect on economic efficiency in dairy farms with short yearly periods of breeding. The individual factors affecting the outcome of an artificial insemination have been extensively researched in many univariate models. In this study, these factors are analysed in combination to create a comprehensive multivariate model of conception in Irish dairy cows. Logistic regression, Naive Bayes, Decision Tree learning and Random Forests are trained using 2,723 artificial insemination records from Irish research farms. An additional 4,205 breeding events from commercial dairy farms are used to evaluate and compare the performance of each data mining technique. The models are assessed in terms of both discrimination and calibration ability. The logistic regression model was found to be the most useful model for predicting insemination outcome. This model is proposed as being appropriate for use in decision support and in general simulation of Irish dairy cows.
    • Comparison of modelling techniques for milk-production forecasting

      Murphy, Michael D.; O’Mahony, Michéal J.; Shalloo, Laurence; French, Padraig; Upton, John (Elsevier for American Dairy Science Association, 2014-04-13)
      The objective of this study was to assess the suitability of 3 different modeling techniques for the prediction of total daily herd milk yield from a herd of 140 lactating pasture-based dairy cows over varying forecast horizons. A nonlinear auto-regressive model with exogenous input, a static artificial neural network, and a multiple linear regression model were developed using 3 yr of historical milk-production data. The models predicted the total daily herd milk yield over a full season using a 305-d forecast horizon and 50-, 30-, and 10-d moving piecewise horizons to test the accuracy of the models over long- and short-term periods. All 3 models predicted the daily production levels for a full lactation of 305 d with a percentage root mean square error (RMSE) of ≤12.03%. However, the nonlinear auto-regressive model with exogenous input was capable of increasing its prediction accuracy as the horizon was shortened from 305 to 50, 30, and 10 d [RMSE (%) = 8.59, 8.1, 6.77, 5.84], whereas the static artificial neural network [RMSE (%) = 12.03, 12.15, 11.74, 10.7] and the multiple linear regression model [RMSE (%) = 10.62, 10.68, 10.62, 10.54] were not able to reduce their forecast error over the same horizons to the same extent. For this particular application the nonlinear auto-regressive model with exogenous input can be presented as a more accurate alternative to conventional regression modeling techniques, especially for short-term milk-yield predictions.
    • The costs of seasonality and expansion in Ireland’s milk production and processing

      Heinschink, K.; Shalloo, Laurence; Wallace, Michael (Teagasc (Agriculture and Food Development Authority), Ireland, 2016-12-30)
      Ireland’s milk production sector relies on grass-based spring-calving systems, which facilitates cost advantages in milk production but entails a high degree of supply seasonality. Among other implications, this supply seasonality involves extra costs in the processing sector including elevated plant capacities and varying levels of resource utilisation throughout the year. If both the national raw milk production increased substantially (e.g. post-milk quota) and a high degree of seasonality persisted, extra processing capacities would be required to cope with peak supplies. Alternatively, existing capacities could be used more efficiently by distributing the milk volume more evenly during the year. In this analysis, an optimisation model was applied to analyse the costs and economies arising to an average Irish milk-processing business due to changes to the monthly distribution of milk deliveries and/or the total annual milk pool. Of the situations examined, changing from a seasonal supply prior to expansion to a smoother pattern combined with an increased milk pool emerged as the most beneficial option to the processor because both the processor’s gross surplus and the marginal producer milk price increased. In practice, it may however be the case that the extra costs arising to the producer from smoothing the milk intake distribution exceed the processor’s benefit. The interlinkages between the stages of the dairy supply chain mean that nationally, the seasonality trade-offs are complex and equivocal. Moreover, the prospective financial implications of such strategies will be dependent on the evolving and uncertain nature of international dairy markets in the post-quota environment.
    • Dairy product production and lactose demand in New Zealand and Ireland under different simulated milk product-processing portfolios

      Sneddon, N.W.; Lopez-Villalobos, N.; Hickson, R.E.; Davis, S.R.; Geary, Una; Garrick, Dorian J.; Shalloo, Laurence (Teagasc (Agriculture and Food Development Authority), Ireland, 2016-12-30)
      Maximising dairy industry profitability involves maximising product returns for a specific set of costs or minimising costs for a certain level of output. A strategy currently utilised by the New Zealand dairy industry to optimise the value of exports is to incorporate imported lactose along with local milk to maximise the production of whole milk powder (WMP) while complying with the Codex Alimentarius (Codex) standards, in addition to increasing the exported product for every litre of milk. This study investigated the impact of different product portfolio strategies on lactose requirements for the Irish and New Zealand dairy industries for current and predicted 2020 milk output projections. A mass balance processing sector model that accounts for all inputs, outputs and losses involved in dairy processing was used to simulate the processing of milk into WMP, skim milk powder (SMP), cheese, butter and fluid milk of different proportions. All scenarios investigated projected an increase in production and revenue from 2012 to 2020. Higher cheese production reduced industry lactose demand through whey processing, while scenarios reliant on an increase in the proportion of WMP were associated with increased lactose deficits.
    • Deriving economic values for national sheep breeding objectives using a bio-economic model

      Bohan, Alan; Shalloo, Laurence; Creighton, Philip; Berry, Donagh; Boland, T. M.; O'Brien, Aine; Pabiou, Thierry; Wall, E.; McDermott, Kevin; McHugh, Noirin; et al. (Elsevier, 2019-05-27)
      The economic value of a trait in a breeding objective can be defined as the value of a unit change in an individual trait, while keeping all other traits constant and are widely used in the development of breeding objectives internationally. The objective of this study was to provide a description of the development of economic values for the pertinent traits included in the Irish national sheep breeding objectives using a whole farm system bio-economic model. A total of fourteen traits of economic importance representing maternal, lambing, production and health characteristics were calculated within a whole farm bio-economic model. The model was parameterised to represent an average Irish flock of 107 ewes with a mean lambing date in early March, stocked at 7.5 ewes per hectare and weaning 1.5 lambs per ewe joined to the ram. The economic values (units in parenthesis) calculated for maternal traits were: €39.76 for number of lambs born (per lamb), €0.12 for ewe mature weight cull value (per kg), −€0.57 for ewe mature weight maintenance value (per kg), −€0.09 for ewe mature weight replacement value (per kg) and −€0.84 for ewe replacement rate (per%). The economic values calculated for lambing traits were: €54.84 for lamb surviving at birth (per lamb), −€0.27 and −€0.30 for direct lambing difficulty in single and multiple-bearing ewes, respectively (per%); the corresponding values for maternal single and multiple lambing difficulty (per%) were −€0.25 and −€0.27, respectively. The calculated economic values for production traits were: −€0.25 for days to slaughter (per day), €3.70 for carcass Conformation (per EUROP grade) and −€0.84 for carcass fat (per fat score). The economic values for health traits were: −€0.24 for ewe lameness (per%), −€0.08 for lamb lameness (per%), −€0.25 for mastitis (per%), −€0.34 for dag score (per dag score) and −€0.08 for faecal egg count (per 50 eggs/g). Within the two Irish breeding objectives, the terminal and replacement breeding objective, the greatest emphasis was placed on production traits across both the terminal (62.56%) and replacement (41.65%) breeding objectives. The maternal and lambing traits accounted for the 34.19% and 23.45% of the emphasis within the replacement breeding objective, respectively. Results from this study will enable the implementation of new economic values within the national terminal and replacement Irish sheep breeding objectives which highlights the traits of importance for increasing overall farm profitability.
    • Development of an efficient milk production profile of the Irish dairy Industry

      Shalloo, Laurence; Dillon, Pat; Wallace, Michael; Dairy Levy Research Trust; European Union (Teagasc, 2008-07)
      Fluctuation around milk price will be the biggest factor that the dairy industry will experience over the next number of years. This fluctuation is being driven by fluctuation on the world dairy markets. In the past, when intervention was a much bigger feature of the CAP regime, the fluctuation in world markets had little effect on the EU price. This was because the Intervention system bought product from the market when prices were depressed and placed products on the world market when the price rose. This in effect meant that the CAP regime was having a regulatory effect on the world market as well as the EU markets. An example of the type of fluctuation observed on the world market can be gleamed from the Fonterra milk price in 2006-2007 ($4.50/kg (MS) milk solid) versus 2007-2008 ($7.90/kg MS). This corresponds to a 76% increase in price in 1 year. For the Dairy Industry in Ireland to prosper under these conditions all sectors will be required to be as efficient as possible from the farm, processing and marketing sectors. This report deals with; (1) Milk payment (2) Optimum milk production systems and (3) Seasonality of milk supply. (1) Milk payment systems in Ireland currently do not adequately reward high solids quality milk. Virtually all milk payment systems include a positive constant which reward the production of volume rather than the production of protein and fat kilograms. The A+B-C system of milk payment would adequately reward the production of protein and fat while at the same time correcting for the volume related processing costs. (2) Optimum systems of milk production will be built around the maximization of grass utilization in the future. Grazed grass is the cheapest feed that can be fed to dairy cows. Stocking rates nationally are 1.74cows/Ha around the milking platform and therefore when dairy farms are expanding they should do so by increasing stocking rate. The inclusion of supplementary feeds will reduce profitability for the vast majority of dairy farmers and could only possibly lead to increases in profitability when coupled increases in stocking rate. (3) Grass based systems while substantially reducing costs at farm level result in a seasonal milk supply profile. This results in a reduced capacity utilization of the milk processing facilities as well as restricted product port folio. However the production of Winter milk will lead to significant cost increases at farm level and should only be encouraged if the specific product produced would be sufficient to cover the additional costs associated with over winter production. Within spring calving systems milk payment systems should be used to encourage an efficient milk supply profile with a mean compact calving date of mid February.