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L. Shalloo
Teagasc, Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, P61 P302 Co. Cork, Ireland

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Journal article
Published: 16 February 2021 in Sustainability
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The aim of this study was to model the productivity, profitability and the nitrogen (N) utilisation efficiency (NUE) of two spring-calving pasture-based milk production systems differing in milking frequency and intensification levels in New Zealand. For this purpose, physical performance data from a low-intensity production system where cows were milked once per day (OAD-LI) and from a high-intensity production system where cows were milked twice per day (TAD-HI) were employed. OAD-LI cows were milked once-daily with a stocking rate (SR) of 2.1 cows/ha and fed diets with low supplementation (304 kg pasture silage/cow) with applications of 134 kg N fertiliser/ha and TAD-HI cows were milked twice-daily with a SR of 2.8 cows/ha and fed diets of higher supplementation (429 kg pasture silage and 1695 kg concentrate/cow) with applications of 87 kg N fertiliser/ha. The Moorepark Dairy System Model was used to evaluate production, economic performance and N balance on an annual basis. Despite the higher feed costs of TAD-HI as more supplementation was utilised, profitability per hectare was 16% higher because more cows were milked with a higher milk yield per cow (milking frequency) when compared to OAD-LI. At the cow level, the NUE was higher in TAD-HI (30% vs. 27%) reflecting the better balanced diet for energy and crude protein and higher milk yields as a result of milking frequency. At the farm scale the NUE was higher (38% vs. 26%) in the TAD-HI due to the losses associated with the imported feed being excluded and higher N captured in milk. These results suggest that milking frequency, the use of feed supplementation and application of N fertiliser as management tools on grazing dairy systems affect productivity, profitability and N balance. Further studies are required to find optimal stocking rates in combination with the use of supplementary feed and N fertiliser application that maximize milk production and profitability for OAD and TAD milking production systems but minimize N losses.

ACS Style

Martín Correa-Luna; Daniel Donaghy; Peter Kemp; Laurence Shalloo; Elodie Ruelle; Deirdre Hennessy; Nicolás López-Villalobos. Productivity, Profitability and Nitrogen Utilisation Efficiency of Two Pasture-Based Milk Production Systems Differing in the Milking Frequency and Feeding Level. Sustainability 2021, 13, 2098 .

AMA Style

Martín Correa-Luna, Daniel Donaghy, Peter Kemp, Laurence Shalloo, Elodie Ruelle, Deirdre Hennessy, Nicolás López-Villalobos. Productivity, Profitability and Nitrogen Utilisation Efficiency of Two Pasture-Based Milk Production Systems Differing in the Milking Frequency and Feeding Level. Sustainability. 2021; 13 (4):2098.

Chicago/Turabian Style

Martín Correa-Luna; Daniel Donaghy; Peter Kemp; Laurence Shalloo; Elodie Ruelle; Deirdre Hennessy; Nicolás López-Villalobos. 2021. "Productivity, Profitability and Nitrogen Utilisation Efficiency of Two Pasture-Based Milk Production Systems Differing in the Milking Frequency and Feeding Level." Sustainability 13, no. 4: 2098.

Journal article
Published: 27 July 2020 in Foods
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The objective of this study was to determine the effect of seasonal variation on milk composition and establish an algorithm to predict density based on milk composition to enable the calculation of season-based density conversion calculations. A total of 1035 raw whole milk samples were collected from morning and evening milking of 60 spring-calving individual cows of different genetic groups, namely Jersey, Elite HF (Holstein–Friesian) and National Average HF, once every two weeks for a period of 9 months (March–November, 2018). The average mean and standard deviation for milk compositional traits were 4.72 ± 1.30% fat, 3.85 ± 0.61% protein and 4.69 ± 0.30% lactose and density was estimated at 1.0308 ± 0.002 g/cm3. The density of the milk samples was evaluated using three methods: a portable density meter, DMA 35; a standard desktop version, DMA 4500M; and an Association of Official Agricultural Chemists (AOAC) method using 100-mL glass pycnometers. Statistical analysis using a linear mixed model showed a significant difference in density of milk samples (p < 0.05) across seasonal and compositional variations adjusted for the effects of days in milk, parity, the feeding treatment, the genetic group and the measurement technique. The mean density values and standard error of mean estimated for milk samples in each season, i.e., spring, summer and autumn were 1.0304 ± 0.00008 g/cm3, 1.0314 ± 0.00005 g/cm3 and 1.0309 ± 0.00007 g/cm3, respectively.

ACS Style

Puneet Parmar; Nicolas Lopez-Villalobos; John T. Tobin; Eoin Murphy; Arleen McDonagh; Shane V. Crowley; Alan L. Kelly; Laurence Shalloo. The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry. Foods 2020, 9, 1004 .

AMA Style

Puneet Parmar, Nicolas Lopez-Villalobos, John T. Tobin, Eoin Murphy, Arleen McDonagh, Shane V. Crowley, Alan L. Kelly, Laurence Shalloo. The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry. Foods. 2020; 9 (8):1004.

Chicago/Turabian Style

Puneet Parmar; Nicolas Lopez-Villalobos; John T. Tobin; Eoin Murphy; Arleen McDonagh; Shane V. Crowley; Alan L. Kelly; Laurence Shalloo. 2020. "The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry." Foods 9, no. 8: 1004.

Journal article
Published: 26 June 2020 in Agriculture
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Body condition scores (BCS) measure a cow’s fat reserves and is important for management and research. Manual BCS assessment is subjective, time-consuming, and requires trained personnel. The BodyMat F (BMF, Ingenera SA, Cureglia, Switzerland) is an automated body condition scoring system using a 3D sensor to estimate BCS. This study assesses the BMF. One hundred and three Holstein Friesian cows were assessed by the BMF and two assessors throughout a lactation. The BMF output is in the 0–5 scale commonly used in France. We develop and report the first equation to convert these scores to the 1–5 scale used by the assessors in Ireland in this study ((0–5 scale × 0.38) + 1.67 → 1–5 scale). Inter-assessor agreement as measured by Lin’s concordance of correlation was 0.67. BMF agreement with the mean of the two assessors was the same as between assessors (0.67). However, agreement was lower for extreme values, particularly in over-conditioned cows where the BMF underestimated BCS relative to the mean of the two human observers. The BMF outperformed human assessors in terms of reproducibility and thus is likely to be especially useful in research contexts. This is the second independent validation of a commercially marketed body condition scoring system as far as the authors are aware. Comparing the results here with the published evaluation of the other system, we conclude that the BMF performed as well or better.

ACS Style

Niall O’ Leary; Lorenzo Leso; Frank Buckley; Jonathon Kenneally; Diarmuid McSweeney; Laurence Shalloo. Validation of an Automated Body Condition Scoring System Using 3D Imaging. Agriculture 2020, 10, 246 .

AMA Style

Niall O’ Leary, Lorenzo Leso, Frank Buckley, Jonathon Kenneally, Diarmuid McSweeney, Laurence Shalloo. Validation of an Automated Body Condition Scoring System Using 3D Imaging. Agriculture. 2020; 10 (6):246.

Chicago/Turabian Style

Niall O’ Leary; Lorenzo Leso; Frank Buckley; Jonathon Kenneally; Diarmuid McSweeney; Laurence Shalloo. 2020. "Validation of an Automated Body Condition Scoring System Using 3D Imaging." Agriculture 10, no. 6: 246.

Journal article
Published: 11 April 2020 in Animals
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Accelerometer-based mobility scoring has focused on cow behaviors such as lying and walking. Accuracy levels as high as 91% have been previously reported. However, there has been limited replication of results. Here, measures previously identified as indicative of mobility, such as lying bouts and walking time, were examined. On a research farm and a commercial farm, 63 grazing cows’ behavior was monitored in four trials (16, 16, 16, and 15 cows) using leg-worn accelerometers. Seventeen good mobility (score 0), 23 imperfect mobility (score 1), and 22 mildly impaired mobility (score 2) cows were monitored. Only modest associations with activity, standing, and lying events were found. Thus, behavior monitoring appears to be insufficient to discern mildly and moderately impaired mobility of grazing cows.

ACS Style

Niall W. O’Leary; Daire. T. Byrne; Pauline Garcia; Jessica Werner; Morgan Cabedoche; Laurence Shalloo. Grazing Cow Behavior’s Association with Mild and Moderate Lameness. Animals 2020, 10, 661 .

AMA Style

Niall W. O’Leary, Daire. T. Byrne, Pauline Garcia, Jessica Werner, Morgan Cabedoche, Laurence Shalloo. Grazing Cow Behavior’s Association with Mild and Moderate Lameness. Animals. 2020; 10 (4):661.

Chicago/Turabian Style

Niall W. O’Leary; Daire. T. Byrne; Pauline Garcia; Jessica Werner; Morgan Cabedoche; Laurence Shalloo. 2020. "Grazing Cow Behavior’s Association with Mild and Moderate Lameness." Animals 10, no. 4: 661.

Discussion
Published: 20 March 2020 in Sustainability
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In temperate regions of Europe where grass grows for most of the year, grazed pasture is the lowest cost feed for milk production. Grazed pasture can make a contribution to dairy cow feeding systems in other parts of Europe, but is less important. While there are many challenges to maintaining or increasing the proportion of grazed grass in dairy cow diets, there are also opportunities to increase its contribution. Grass use and quality can be challenging for several reasons, including the cow and sward interaction, and factors influencing dry matter intake. Adapting grazing management strategies can provide opportunities for incorporating grazing and perhaps increase grazing in dairy cow milk production systems. Pasture management tools and techniques offer the opportunity to increase herbage use at grazing. While there are many benefits of grazing including economic, environmental, animal welfare and social, there are also the challenges to maintaining grazed pasture in dairy cow diets. The objective of this paper is to present an overview of the challenges and opportunities for grazing in dairy milk production systems.

ACS Style

Deirdre Hennessy; Luc Delaby; Agnes Van Den Pol-Van Dasselaar; Laurence Shalloo. Increasing Grazing in Dairy Cow Milk Production Systems in Europe. Sustainability 2020, 12, 2443 .

AMA Style

Deirdre Hennessy, Luc Delaby, Agnes Van Den Pol-Van Dasselaar, Laurence Shalloo. Increasing Grazing in Dairy Cow Milk Production Systems in Europe. Sustainability. 2020; 12 (6):2443.

Chicago/Turabian Style

Deirdre Hennessy; Luc Delaby; Agnes Van Den Pol-Van Dasselaar; Laurence Shalloo. 2020. "Increasing Grazing in Dairy Cow Milk Production Systems in Europe." Sustainability 12, no. 6: 2443.

Preprint
Published: 07 February 2020
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Development of accelerometer-based lameness (mobility) detection has focused on cow behaviors such as lying and walking. Several studies, usually small, have reported levels of accuracy up to 91%. However, there has been limited independent replication of these results. In this study, behavior measures previously identified as being associated with lameness such as lying bouts and walking time are examined in relation to mobility score. On a research farm and a commercial farm, four trials were completed with 65 grazing cows. The cows had differing mobility scores ranging from perfect mobility to impaired mobility. Behavior was monitored using leg worn accelerometers. In general, behavior and mobility associations identified in previous studies were not found. Behavior monitoring with accelerometers as a basis to classify impaired mobility in pasture-based contexts thus remains challenging.

ACS Style

Niall W. O’Leary; Daire T. Byrne; Pauline Garcia; Jessica Werner; Morgan Cabedoche; Laurence Shalloo. Grazing Cow Behavior and Lameness. 2020, 1 .

AMA Style

Niall W. O’Leary, Daire T. Byrne, Pauline Garcia, Jessica Werner, Morgan Cabedoche, Laurence Shalloo. Grazing Cow Behavior and Lameness. . 2020; ():1.

Chicago/Turabian Style

Niall W. O’Leary; Daire T. Byrne; Pauline Garcia; Jessica Werner; Morgan Cabedoche; Laurence Shalloo. 2020. "Grazing Cow Behavior and Lameness." , no. : 1.

Research article
Published: 01 January 2020 in Animal Production Science
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A resilient dairy business will be sustainable across all of the sustainability indicators, survive milk-price drops and be very profitable when milk price is high. The term resilient means able to ‘recover, respond, deal or withstand’ different internal and external challenges that may manifest themselves within the farm business from time to time. There is significant potential to increase efficiency and productivity at farm level when compared with the average farm nationally. The focus at a farm level must be about increasing grass growth and utilisation and converting that feed to milk solids (kg of milk fat and protein) sales at as low a cost as possible. Increasing labour efficiency by operating more streamlined work practices, using contractors and contract rearing of heifers will have a major impact on farm labour requirements.

ACS Style

Laurence Shalloo; Liam Hanrahan. Setting targets for the Irish dairy industry. Animal Production Science 2020, 60, 159 .

AMA Style

Laurence Shalloo, Liam Hanrahan. Setting targets for the Irish dairy industry. Animal Production Science. 2020; 60 (1):159.

Chicago/Turabian Style

Laurence Shalloo; Liam Hanrahan. 2020. "Setting targets for the Irish dairy industry." Animal Production Science 60, no. 1: 159.

Evaluation study
Published: 01 April 2018 in Journal of Neuroscience Methods
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Feeding behaviour is an important parameter of animal performance, health and welfare, as well as reflecting levels and quality of feed available. Previously, sensors were only used for measuring animal feeding behaviour in indoor housing systems. However, sensors such as the RumiWatchSystem can also monitor such behaviour continuously in pasture-based environments. Therefore, the aim of this study was to validate the RumiWatchSystem to record cow activity and feeding behaviour in a pasture-based system. The RumiWatchSystem was evaluated against visual observation across two different experiments. The time duration per hour at grazing, rumination, walking, standing and lying recorded by the RumiWatchSystem was compared to the visual observation data in Experiment 1. Concordance Correlation Coefficient (CCC) values of CCC=0.96 for grazing, CCC=0.99 for rumination, CCC=1.00 for standing and lying and CCC=0.92 for walking were obtained. The number of grazing and rumination bouts within one hour were also analysed resulting in Cohen's Kappa (κ)=0.62 and κ=0.86 for grazing and rumination bouts, respectively. Experiment 2 focused on the validation of grazing bites and rumination chews. The accordance between visual observation and automated measurement by the RumiWatchSystem was high with CCC=0.78 and CCC=0.94 for grazing bites and rumination chews, respectively. These results indicate that the RumiWatchSystem is a reliable sensor technology for observing cow activity and feeding behaviour in a pasture based milk production system, and may be used for research purposes in a grazing environment.

ACS Style

J. Werner; Lorenzo Leso; C. Umstatter; J. Niederhauser; E. Kennedy; A. Geoghegan; L. Shalloo; M. Schick; B. O’Brien. Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows. Journal of Neuroscience Methods 2018, 300, 138 -146.

AMA Style

J. Werner, Lorenzo Leso, C. Umstatter, J. Niederhauser, E. Kennedy, A. Geoghegan, L. Shalloo, M. Schick, B. O’Brien. Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows. Journal of Neuroscience Methods. 2018; 300 ():138-146.

Chicago/Turabian Style

J. Werner; Lorenzo Leso; C. Umstatter; J. Niederhauser; E. Kennedy; A. Geoghegan; L. Shalloo; M. Schick; B. O’Brien. 2018. "Evaluation of the RumiWatchSystem for measuring grazing behaviour of cows." Journal of Neuroscience Methods 300, no. : 138-146.

Review
Published: 01 January 2018 in Animal
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Precision technologies and data have had relatively modest impacts in grass-based livestock ruminant production systems compared with other agricultural sectors such as arable. Precision technologies promise increased efficiency, reduced environmental impact, improved animal health, welfare and product quality. The benefits of precision technologies have, however, been relatively slow to be realised on pasture based farms. Though there is significant overlap with indoor systems, implementing technology in grass-based dairying brings unique opportunities and challenges. The large areas animals roam and graze in pasture based systems and the associated connectivity challenges may, in part at least, explain the comparatively lower adoption of such technologies in pasture based systems. With the exception of sensor and Bluetooth-enabled plate metres, there are thus few technologies designed specifically to increase pasture utilisation. Terrestrial and satellite-based spectral analysis of pasture biomass and quality is still in the development phase. One of the key drivers of efficiency in pasture based systems has thus only been marginally impacted by precision technologies. In contrast, technological development in the area of fertility and heat detection has been significant and offers significant potential value to dairy farmers, including those in pasture based systems. A past review of sensors in health management for dairy farms concluded that although the collection of accurate data was generally achieved, the processing, integration and presentation of the resulting information and decision-support applications were inadequate. These technologies’ value to farming systems is thus unclear. As a result, it is not certain that farm management is being sufficiently improved to justify widespread adoption of precision technologies currently. We argue for a user need-driven development of technologies and for a focus on how outputs arising from precision technologies and associated decision support applications are delivered to users to maximise their value. Further cost/benefit analysis is required to determine the efficacy of investing in specific precision technologies, potentially taking account of several yet to ascertained farm specific variables.

ACS Style

L. Shalloo; M. O’ Donovan; Lorenzo Leso; J. Werner; E. Ruelle; A. Geoghegan; L. Delaby; Niall O'Leary. Review: Grass-based dairy systems, data and precision technologies. Animal 2018, 12, s262 -s271.

AMA Style

L. Shalloo, M. O’ Donovan, Lorenzo Leso, J. Werner, E. Ruelle, A. Geoghegan, L. Delaby, Niall O'Leary. Review: Grass-based dairy systems, data and precision technologies. Animal. 2018; 12 ():s262-s271.

Chicago/Turabian Style

L. Shalloo; M. O’ Donovan; Lorenzo Leso; J. Werner; E. Ruelle; A. Geoghegan; L. Delaby; Niall O'Leary. 2018. "Review: Grass-based dairy systems, data and precision technologies." Animal 12, no. : s262-s271.

Journal article
Published: 01 November 2017 in Journal of Environmental Management
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A major methodological issue for life cycle assessment, commonly used to quantify greenhouse gas emissions from livestock systems, is allocation from multifunctional processes. When a process produces more than one output, the environmental burden has to be assigned between the outputs, such as milk and meat from a dairy cow. In the absence of an objective function for choosing an allocation method, a decision must be made considering a range of factors, one of which is the availability and quality of necessary data. The objective of this study was to evaluate allocation methods to calculate the climate change impact of the economically average (€/ha) dairy farm in Ireland considering both milk and meat outputs, focusing specifically on the pedigree of the available data for each method. The methods were: economic, energy, protein, emergy, mass of liveweight, mass of carcass weight and physical causality. The data quality for each method was expressed using a pedigree score based on reliability of the source, completeness, temporal applicability, geographical alignment and technological appropriateness. Scenario analysis was used to compare the normalised impact per functional unit (FU) from the different allocation methods, between the best and worst third of farms (in economic terms, €/ha) in the national farm survey. For the average farm, the allocation factors for milk ranged from 75% (physical causality) to 89% (mass of carcass weight), which in turn resulted in an impact per FU, from 1.04 to 1.22 kg CO2-eq/kg (fat and protein corrected milk). Pedigree scores ranged from 6.0 to 17.1 with protein and economic allocation having the best pedigree. It was concluded that when making the choice of allocation method, the quality of the data available (pedigree) should be given greater emphasis during the decision making process because the effect of allocation on the results. A range of allocation methods could be deployed to understand the uncertainty associated with the decision.

ACS Style

P. Rice; D. O'Brien; L. Shalloo; N.M. Holden. Evaluation of allocation methods for calculation of carbon footprint of grass-based dairy production. Journal of Environmental Management 2017, 202, 311 -319.

AMA Style

P. Rice, D. O'Brien, L. Shalloo, N.M. Holden. Evaluation of allocation methods for calculation of carbon footprint of grass-based dairy production. Journal of Environmental Management. 2017; 202 ():311-319.

Chicago/Turabian Style

P. Rice; D. O'Brien; L. Shalloo; N.M. Holden. 2017. "Evaluation of allocation methods for calculation of carbon footprint of grass-based dairy production." Journal of Environmental Management 202, no. : 311-319.

Journal article
Published: 01 December 2016 in Irish Journal of Agricultural and Food Research
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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.

ACS Style

Nicholas Sneddon; Nicolas Lopez-Villalobos; R.E. Hickson; S.R. Davis; U. Geary; D.J. Garrick; Laurence Shalloo. Dairy product production and lactose demand in New Zealand and Ireland under different simulated milk product-processing portfolios. Irish Journal of Agricultural and Food Research 2016, 55, 126 -135.

AMA Style

Nicholas Sneddon, Nicolas Lopez-Villalobos, R.E. Hickson, S.R. Davis, U. Geary, D.J. Garrick, Laurence Shalloo. Dairy product production and lactose demand in New Zealand and Ireland under different simulated milk product-processing portfolios. Irish Journal of Agricultural and Food Research. 2016; 55 (2):126-135.

Chicago/Turabian Style

Nicholas Sneddon; Nicolas Lopez-Villalobos; R.E. Hickson; S.R. Davis; U. Geary; D.J. Garrick; Laurence Shalloo. 2016. "Dairy product production and lactose demand in New Zealand and Ireland under different simulated milk product-processing portfolios." Irish Journal of Agricultural and Food Research 55, no. 2: 126-135.

Journal article
Published: 01 December 2016 in Irish Journal of Agricultural and Food Research
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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.

ACS Style

K. Heinschink; Laurence Shalloo; M. Wallace. The costs of seasonality and expansion in Ireland’s milk production and processing. Irish Journal of Agricultural and Food Research 2016, 55, 100 -111.

AMA Style

K. Heinschink, Laurence Shalloo, M. Wallace. The costs of seasonality and expansion in Ireland’s milk production and processing. Irish Journal of Agricultural and Food Research. 2016; 55 (2):100-111.

Chicago/Turabian Style

K. Heinschink; Laurence Shalloo; M. Wallace. 2016. "The costs of seasonality and expansion in Ireland’s milk production and processing." Irish Journal of Agricultural and Food Research 55, no. 2: 100-111.

Research articles
Published: 02 January 2016 in New Zealand Journal of Agricultural Research
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The breeding goal of the New Zealand dairy industry is to improve the genetic capability of cows to convert pasture-based feed into farmer profit. The New Zealand dairy industry exports over 95% of milk produced and the most significant product by export volume is whole milk powder (WMP). The current selection objective, breeding worth (BW), will increase yields of protein and fat, potentially shifting milk composition further from the ideal composition for making WMP. This study aimed to investigate the correlated responses in lactose yield (LY), lactose percentage (LP) and protein-to-protein-plus-lactose ratio (P:P + L) from selection for BW, BW plus LY, BW plus LP and BW plus P:P + L. Selection for BW is predicted to have per-cow responses of 54.92 kg milk/year, 2.22 kg fat/year, 1.78 kg protein/year and 2.84 kg lactose/year. When lactose was included in the selection objective in the form of LY, LP or P:P + L, genetic responses ranged from −59.98 kg to 61.08 kg milk/year and from −2.67 kg to 3.70 kg lactose/year. The industry could reduce imported lactose requirements per tonne of WMP by 6%–11% by including lactose into the selection objective, compared with selection on BW alone.

ACS Style

Nw Sneddon; Nicolas Lopez-Villalobos; Sr Davis; Re Hickson; L Shalloo; Dorian Garrick; U Geary. Responses in lactose yield, lactose percentage and protein-to-protein-plus-lactose ratio from index selection in New Zealand dairy cattle. New Zealand Journal of Agricultural Research 2016, 59, 90 -105.

AMA Style

Nw Sneddon, Nicolas Lopez-Villalobos, Sr Davis, Re Hickson, L Shalloo, Dorian Garrick, U Geary. Responses in lactose yield, lactose percentage and protein-to-protein-plus-lactose ratio from index selection in New Zealand dairy cattle. New Zealand Journal of Agricultural Research. 2016; 59 (1):90-105.

Chicago/Turabian Style

Nw Sneddon; Nicolas Lopez-Villalobos; Sr Davis; Re Hickson; L Shalloo; Dorian Garrick; U Geary. 2016. "Responses in lactose yield, lactose percentage and protein-to-protein-plus-lactose ratio from index selection in New Zealand dairy cattle." New Zealand Journal of Agricultural Research 59, no. 1: 90-105.

Journal article
Published: 01 January 2016 in Animal Production Science
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The Irish dairy industry aims to increase milk production from grass-based farms following the removal of the EU milk-quota system, but is also required to minimise greenhouse gas (GHG) emissions to meet European reduction targets. Consequently, the sector is under increasing pressure to reduce GHG emissions per unit of milk, or carbon footprint (CF). Therefore, the goal of the present study was to determine the main sources of the CF of grass-based milk production and to identify mitigation strategies that can be applied to reduce farm footprints. In total, the CF of milk was estimated for 62 grass-based dairy farms in 2014. The method used to quantify GHG emissions was a life cycle assessment (LCA), independently certified to comply with the British standard for LCA (PAS 2050). The LCA method was applied to calculate annual on- and off-farm GHG emissions associated with dairy production until milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk on the basis of the economic value of dairy products and expressed per kilogram of fat- and protein-corrected milk to estimate CF. Enteric methane was the main source of the CF of milk (46%), followed by emissions from inorganic N fertilisers (16%), manure (16%) and concentrate feedstuffs (8%). The mean CF of milk from the 62 farms was 1.26 kg of CO2-eq per kilogram of fat- and protein-corrected milk, but varied from 0.98 kg to 1.67 kg as measured using the 95% confidence interval. The CF of milk was correlated with numerous farm attributes, particularly N-fertiliser, the percentage of grazed grass in the diet, and production of milk solids. Grass-based dairy farmers can significantly improve these farm attributes by increasing herd genetic merit, extending the length of the grazing season and optimising N fertiliser use and, thereby, reduce the CF of milk.

ACS Style

D. O’Brien; A. Geoghegan; K. McNamara; L. Shalloo; And. How can grass-based dairy farmers reduce the carbon footprint of milk? Animal Production Science 2016, 56, 495 .

AMA Style

D. O’Brien, A. Geoghegan, K. McNamara, L. Shalloo, And. How can grass-based dairy farmers reduce the carbon footprint of milk? Animal Production Science. 2016; 56 (3):495.

Chicago/Turabian Style

D. O’Brien; A. Geoghegan; K. McNamara; L. Shalloo; And. 2016. "How can grass-based dairy farmers reduce the carbon footprint of milk?" Animal Production Science 56, no. 3: 495.

Journal article
Published: 01 November 2015 in European Journal of Agronomy
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Modelling pasture-based systems is a challenge for modellers worldwide. However, models can play a vital role as grazing management tools and help the decision making process at farm level. The objective of this paper is to describe and evaluate the pasture-based herd dynamic milk (PBHDM) model. The PBHDM model comprises the herd dynamic milk (HDM) model and integrates it with a grazing management and a paddock sub-model. Animal intake at grazing is dependent on the animal characteristics but also on grass availability and quality. It also depends on the interactions between the animal and the grass during the defoliation process. Management of grass on farm can be regulated through different rules during the grazing season including the decision to cut some paddocks in the case of a grass surplus and to allocate supplementation in the case of a grass deficit. The PBHDM was evaluated by comparing model outputs with two grazing systems one in France and one in Ireland. For both farms the grazing season is longer than 7 months. Model outputs that were compared to the actual experimental data included milk production, pre- and post-grazing height and feed supplementation levels. These outputs were all compared on a weekly basis while paddock residence time and total grass harvested as conserved grass silage was evaluated over the grazing season as a whole. The model was capable of reproducing the two grazing systems with acceptable accuracy. It simulated the pre- and post-grazing height with a maximal difference between the actual and the simulated average height through the year of 0.4 cm. The model has a tendency to slightly over-estimate the milk production especially in autumn. However in general the model is relatively accurate with a root mean square error less than 20% for the simulated farms.

ACS Style

E. Ruelle; L. Shalloo; M. Wallace; L. Delaby. Development and evaluation of the pasture-based herd dynamic milk (PBHDM) model for dairy systems. European Journal of Agronomy 2015, 71, 106 -114.

AMA Style

E. Ruelle, L. Shalloo, M. Wallace, L. Delaby. Development and evaluation of the pasture-based herd dynamic milk (PBHDM) model for dairy systems. European Journal of Agronomy. 2015; 71 ():106-114.

Chicago/Turabian Style

E. Ruelle; L. Shalloo; M. Wallace; L. Delaby. 2015. "Development and evaluation of the pasture-based herd dynamic milk (PBHDM) model for dairy systems." European Journal of Agronomy 71, no. : 106-114.

Journal article
Published: 01 April 2015 in Journal of Dairy Science
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The objective of the current study was to quantify the effects of exposure to Salmonella, Neospora caninum, and Leptospira interrogans serovar Hardjo (L. hardjo) on dairy farm profitability and to simulate the effect of vaccination for Salmonella and L. hardjo on dairy farm profitability. The production effects associated with exposure to each of these pathogens in study herds were defined under 3 categories: (1) milk production effects, (2) reproduction effects (including culling), and (3) mortality effects. The production effects associated with exposure to Salmonella, N. caninum, and L. hardjo were incorporated into the Moorepark Dairy Systems Model. In the analysis, herds negative for exposure to Salmonella, N. caninum, and L. hardjo were assumed baseline herds, with all results presented relative to this base. In simulations examining the effect of vaccination for Salmonella and L. hardjo on farm profitability, vaccinated herds (vaccination costs included) were considered as baseline herds and results were presented relative to this base. Total annual profits in unvaccinated herds were reduced by €77.31, €94.71, and €112.11 per cow at milk prices of €0.24, €0.29, and €0.34/L, respectively, as a result of exposure to Salmonella. In the current study, herds positive for exposure to Salmonella recorded a 316-kg reduction in milk yield, whereas no association was detected between exposure to N. caninum or L. hardjo and milk production. Exposure to both N. caninum and L. hardjo was associated with compromised reproductive performance. Herds positive for exposure to N. caninum and Salmonella had greater rates of adult cow mortality and calf mortality, respectively. Vaccination for both Salmonella and L. hardjo was associated with improved performance in study herds. Exposure to N. caninum resulted in a reduction in annual farm profits of €11.55, €12, and €12.44 per cow at each milk price, whereas exposure to L. hardjo resulted in a reduction in annual farm profits of €13.83, €13.78, and €13.72 per cow at each milk price. Herds that tested positive for exposure to Salmonella and L. hardjo were compared with herds vaccinated for the respective pathogens. Herds vaccinated for Salmonella generated €67.09, €84.48, and €101.89 per cow more profit at each milk price compared with herds positive for exposure. Similarly, herds vaccinated for L. hardjo generated €9.74, €9.69, and €9.63 per cow more profit compared with unvaccinated exposed herds. However, herds that tested negative for exposure to Salmonella and L. hardjo generated additional profits of €10.22 and €4.09 per cow, respectively, compared with vaccinated baseline herds.

ACS Style

E. O’ Doherty; Riona Sayers; L. O’ Grady; Laurence Shalloo. Effect of exposure to Neospora caninum, Salmonella, and Leptospira interrogans serovar Hardjo on the economic performance of Irish dairy herds. Journal of Dairy Science 2015, 98, 2789 -2800.

AMA Style

E. O’ Doherty, Riona Sayers, L. O’ Grady, Laurence Shalloo. Effect of exposure to Neospora caninum, Salmonella, and Leptospira interrogans serovar Hardjo on the economic performance of Irish dairy herds. Journal of Dairy Science. 2015; 98 (4):2789-2800.

Chicago/Turabian Style

E. O’ Doherty; Riona Sayers; L. O’ Grady; Laurence Shalloo. 2015. "Effect of exposure to Neospora caninum, Salmonella, and Leptospira interrogans serovar Hardjo on the economic performance of Irish dairy herds." Journal of Dairy Science 98, no. 4: 2789-2800.

Journal article
Published: 01 January 2015 in Animal Production Science
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Pasture grazed in situ is one of the most competitive and sustainable feeding systems for dairy cows globally because of a low environmental footprint, the potential for excellent animal welfare and the relatively low cost in the production and utilisation of the feed. However, because of seasonal variation in grass production and inclement weather conditions, dairy cattle may have to be accommodated and/or fed off pasture. There are numerous infrastructural options for achieving this and the focus of the present paper was to review the research and discuss the merits of these alternate animal accommodation systems, focussing on the impact that they have on the environment, animal welfare and farm profitability relative to pasture-only systems. Research data showed that dairy cow welfare can be protected in a range of well managed alternative winter accommodation. In a temperate climate, such as that which pertains in Ireland, adequately fed adult cattle will not use extra feed energy to maintain body temperature when accommodated outdoors and exposed to the effects of wind, rain and low temperatures, as the heat produced from the digestion of feed is in excess of the requirement to maintain body temperature. The main welfare challenge of a wintering system in such conditions is to provide suitable lying facilities for cows to express normal lying behaviour and provide adequate feed. The primary economic focus of pasture-based systems should be to maximise the length of the grass-grazing season and, consequently, to minimise the period off paddock. Provided that body condition targets can be met, there will be minimal effect of wintering system on dairy cow productivity and the only economic differences will be in costs. The cost analysis should combine the capital costs of construction financed over its useful life and the annual operating costs, including labour.

ACS Style

Peter L French; K. O. Driscoll; B. Horan; L. Shalloo. The economic, environmental and welfare implications of alternative systems of accommodating dairy cows during the winter months. Animal Production Science 2015, 55, 838 -842.

AMA Style

Peter L French, K. O. Driscoll, B. Horan, L. Shalloo. The economic, environmental and welfare implications of alternative systems of accommodating dairy cows during the winter months. Animal Production Science. 2015; 55 (7):838-842.

Chicago/Turabian Style

Peter L French; K. O. Driscoll; B. Horan; L. Shalloo. 2015. "The economic, environmental and welfare implications of alternative systems of accommodating dairy cows during the winter months." Animal Production Science 55, no. 7: 838-842.

Journal article
Published: 01 April 2013 in International Journal of Agricultural Management
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The objectives of this study were to estimate the levels of technical and scale efficiency for a sample of pasture based Irish dairy producers, to identify the factors that contributed to reaching the optimum scale and to examine the relationship between technical and scale efficiency with farm size, intensification and specialisation. Efficiency scores were calculated using Data Envelopment Analysis (DEA). Technical efficiency was on average 0.757 under constant returns to scale (CRS), 0.799 under variable returns to scale (VRS) and scale efficiency was estimated at 0.951. Twelve per cent of the sample was operating at optimum scale (CRS). Fifty six percent of the sample was operating below optimum scale and 32% of the sample was operating above optimum scale. Overall optimum scale was associated with production systems operating with larger land area, with reduced proportion of rented land, increased amounts of hired labour, a higher quantity of quota and achieving a longer grazing season. It was also shown that increased farm size, intensification and dairy specialisation were associated with increases in technical and scale efficiency at farm level.

ACS Style

E Kelly; L Shalloo; U Geary; A Kinsella; F Thorne; M Wallace. An analysis of the factors associated with technical and scale efficiency of Irish dairy farms. International Journal of Agricultural Management 2013, 2, 149 .

AMA Style

E Kelly, L Shalloo, U Geary, A Kinsella, F Thorne, M Wallace. An analysis of the factors associated with technical and scale efficiency of Irish dairy farms. International Journal of Agricultural Management. 2013; 2 (3):149.

Chicago/Turabian Style

E Kelly; L Shalloo; U Geary; A Kinsella; F Thorne; M Wallace. 2013. "An analysis of the factors associated with technical and scale efficiency of Irish dairy farms." International Journal of Agricultural Management 2, no. 3: 149.

Journal article
Published: 04 April 2012 in The Journal of Agricultural Science
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SUMMARYThe phasing out of the European Union (EU) milk quota will create opportunities for producers to expand without the constraint of quota which has limited expansion since 1984. Therefore, it will be necessary for Irish dairy producers to become more competitive by increasing performance using the least amount of inputs per unit of output and maximizing the level of technical and economic efficiency. The objectives of the current study were to measure technical, allocative and economic efficiency, and to investigate the associations of key management, qualitative and demographic characteristics on efficiency. Efficiency scores were calculated using the non-parametric methodology data envelopment analysis (DEA). The DEA results showed that on average the sample of Irish dairy producers were not fully efficient in 2008 with technical, allocative and economic efficiency results under variable returns to scale (VRS) of 0·771, 0·740 and 0·571, respectively. In a second stage analysis, Tobit regressions were used to determine the associations of key variables with the technical, allocative and economic efficiency scores. The efficiency scores were included as dependent variables and the key independent variables were a variety of management and demographic variables. Mean calving date, number of grazing days, breeding season length, milk quality, discussion group membership and soil quality were all associated with technical and economic efficiency. Milk recording, use of artificial insemination (AI) and level of dairy specialization were associated with allocative and economic efficiency only. Age and age squared were the only significant demographic associations with the efficiency scores.

ACS Style

E. Kelly; L. Shalloo; U. Geary; A. Kinsella; F. Thorne; M. Wallace. The associations of management and demographic factors with technical, allocative and economic efficiency of Irish dairy farms. The Journal of Agricultural Science 2012, 150, 738 -754.

AMA Style

E. Kelly, L. Shalloo, U. Geary, A. Kinsella, F. Thorne, M. Wallace. The associations of management and demographic factors with technical, allocative and economic efficiency of Irish dairy farms. The Journal of Agricultural Science. 2012; 150 (6):738-754.

Chicago/Turabian Style

E. Kelly; L. Shalloo; U. Geary; A. Kinsella; F. Thorne; M. Wallace. 2012. "The associations of management and demographic factors with technical, allocative and economic efficiency of Irish dairy farms." The Journal of Agricultural Science 150, no. 6: 738-754.

Journal article
Published: 31 March 2012 in Agricultural Systems
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Life cycle assessment (LCA) is a holistic systems approach that aims to assess the environmental impacts (potential pollutants and resource use) of the production of goods and services. The aim of this study was to develop an LCA model to compare contrasting milk production systems, a seasonal pasture-based dairy farm and a confinement dairy farm. The environmental impacts considered were global warming, eutrophication, acidification, land use and non-renewable energy use. The LCA estimated on-farm, off-farm (pollutants and resources associated with the production and supply of purchased farm inputs) and total (on-farm and off-farm) environmental impacts. Environmental impacts were quantified per unit of milk and per unit area. The study only considered two research farms, because high quality data were unavailable for a large number of farms. Thus, this was not a representative LCA comparison. The genetic merit of cows modelled was similar for each system. A total mixed ration was fed in the confinement system and grazed grass was mainly fed in the grass-based system. Research data were used to confirm simulated dry matter intake (DMI) and predicted enteric CH4 output from simulated DMI. The study found that when expressed per unit of milk and per on-farm area, all total environmental impacts were greater for the confinement system compared to the grass-based system. Per total farm area (on-farm and off-farm area), all environmental impacts except global warming were lower for the grass-based system. The greater environmental impact of the confinement dairy system was due to the greater use of concentrate feed and the longer manure storage period. Scenario modelling demonstrated that there is potential to decrease the environmental impact of dairy systems, particularly the confinement system, by reducing the use of concentrate ingredients with a high environmental impact and by storing manure in solid systems. Scenario modelling also showed that assumptions regarding the carbon cycle should be clearly outlined when assessing milk production systems and that standardisation of LCA allocation procedures is required. This LCA study is one of the few to directly compare the environmental impact of a grass-based and a confinement dairy system. However direct comparisons are needed, using an LCA methodology such as described in this paper, and using data from a greater number of farms so that each system is better represented thereby ensuring a robust comparison of the two systems on a regional or national basis.

ACS Style

Donal O’Brien; Laurence Shalloo; Joe Patton; Frank Buckley; Chris Grainger; Michael Wallace. A life cycle assessment of seasonal grass-based and confinement dairy farms. Agricultural Systems 2012, 107, 33 -46.

AMA Style

Donal O’Brien, Laurence Shalloo, Joe Patton, Frank Buckley, Chris Grainger, Michael Wallace. A life cycle assessment of seasonal grass-based and confinement dairy farms. Agricultural Systems. 2012; 107 ():33-46.

Chicago/Turabian Style

Donal O’Brien; Laurence Shalloo; Joe Patton; Frank Buckley; Chris Grainger; Michael Wallace. 2012. "A life cycle assessment of seasonal grass-based and confinement dairy farms." Agricultural Systems 107, no. : 33-46.