• Characterisation of physiological and immunological responses in beef cows to abrupt weaning and subsequent housing

      Lynch, Eilish M; Earley, Bernadette; McGee, Mark; Doyle, Sean; Teagasc Walsh Fellowship Programme; John Hume Scholarship (Biomed Central, 2010-07-20)
      Background: Weaning involves the permanent separation of the calf from the dam and has been shown to be stressful for both. The objectives of this study were to characterise the effect of i) abrupt weaning and ii) subsequent housing on the extended physiological and immunological responses of beef cows. At weaning (day (d) 0, mean age of calf (s.d.) 212 (24.5) d), cows were abruptly separated from their calves and returned to the grazing area. After 35 d at pasture, cows were housed in a slatted floor shed and offered grass silage ad libitum plus a mineral-vitamin supplement daily. Rectal body temperature was recorded and blood samples were obtained on i) d 0 (weaning), 2, 7, 14, 21, 28, 35 and subsequently on ii) d 0 (housing), 2, 7, 14 and 21 for physiological, haematological and immunological measurements. Results: Post-weaning, concentration of cortisol and dehydroepiandrosterone were unchanged (P > 0.05). Rectal body temperature, neutrophil number and neutrophil: lymphocyte ratio increased (P < 0.01) on d 2 compared with pre-weaning baseline. Lymphocyte and neutrophil number decreased (P < 0.05) on d 2 to 7 and d 7 to 21, respectively, compared with pre-weaning baseline. Interferon-γ production decreased (P < 0.05) on d 2 compared with pre-weaning baseline. An increase (P < 0.05) in acute phase proteins, fibrinogen and haptoglobin was evident on d 2 to 35 compared with pre-weaning baseline. Concentration of glucose increased on d 2 to 28, whereas non-esterified fatty acid decreased on d 2 to 35 compared with pre-weaning baseline. Post-housing, concentrations of cortisol, rectal body temperature, total leukocyte number, and glucose were unchanged (P > 0.05). On d 2 post-housing, neutrophil number and neutrophil: lymphocyte ratio increased (P < 0.05), whereas lymphocyte number and concentrations of dehydroepiandrosterone, fibrinogen and non-esterified fatty acid decreased (P < 0.05) compared with pre-housing baseline. Concentration of haptoglobin increased (P < 0.05) on d 14 to 21 post-housing. Conclusions: A transitory increase in neutrophil number and decrease in lymphocyte number, increased neutrophil:lymphocyte ratio coupled with decreased interferon-γ production, and increased concentration of acute phase proteins indicate a stress response in cows post-weaning, whereas post-housing, changes were less marked.
    • Characteristics of feed efficiency within and across lactation in dairy cows and the effect of genetic selection

      Hurley, A. M.; Lopez-Villalobos, N.; McParland, Sinead; Lewis, Eva; Kennedy, Emer; O'Donovan, Michael; Burke, Jennifer L.; Berry, Donagh; Irish Department of Agriculture, Food and the Marine; European Union (Elsevier, 2017-11-23)
      The objective of the present study was to investigate the phenotypic inter- and intra-relationships within and among alternative feed efficiency metrics across different stages of lactation and parities; the expected effect of genetic selection for feed efficiency on the resulting phenotypic lactation profiles was also quantified. A total of 8,199 net energy intake (NEI) test-day records from 2,505 lactations on 1,290 cows were used. Derived efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models. Residual energy intake (REI) was defined as NEI minus predicted energy requirements based on lactation performance; residual energy production (REP) was defined as net energy for lactation minus predicted energy requirements based on lactation performance. Energy conversion efficiency was defined as net energy for lactation divided by NEI. Pearson phenotypic correlations among traits were computed across lactation stages and parities, and the significance of the differences was determined using the Fisher r-to-z transformation. Sources of variation in the feed efficiency metrics were investigated using linear mixed models, which included the fixed effects of contemporary group, breed, parity, stage of lactation, and the 2-way interaction of parity by stage of lactation. With the exception of REI, parity was associated with all efficiency and production traits. Stage of lactation, as well as the 2-way interaction of parity by stage of lactation, were associated with all efficiency and production traits. Phenotypic correlations among the efficiency and production traits differed not only by stage of lactation but also by parity. For example, the strong phenotypic correlation between REI and energy balance (EB; 0.89) for cows in parity 3 or greater and early lactation was weaker for parity 1 cows at the same lactation stage (0.81), suggesting primiparous cows use the ingested energy for both milk production and growth. Nonetheless, these strong phenotypic correlations between REI and EB suggested negative REI animals (i.e., more efficient) are also in more negative EB. These correlations were further supported when assessing the effect on phenotypic performance of animals genetically divergent for feed intake and efficiency based on parental average. Animals genetically selected to have lower REI resulted in cows who consumed less NEI but were also in negative EB throughout the entire lactation. Nonetheless, such repercussions of negative EB do not imply that selection for negative REI (as defined here) should not be practiced, but instead should be undertaken within the framework of a balanced breeding objective, which includes traits such as reproduction and health.
    • Choice of artificial insemination beef bulls used to mate with female dairy cattle

      Berry, Donagh; Ring, S.C.; Twomey, A.J.; Evans, R.D.; Science Foundation Ireland; Department of Agriculture, Food and the Marine; 16/RC/3835 (Elsevier for American Dairy Science Association, 2020-02)
      Understanding the preferences of dairy cattle producers when selecting beef bulls for mating can help inform beef breeding programs as well as provide default parameters in mating advice systems. The objective of the present study was to characterize the genetic merit of beef artificial insemination (AI) bulls used in dairy herds, with particular reference to traits associated with both calving performance and carcass merit. The characteristics of the beef AI bulls used were compared with those of the dairy AI bulls used on the same farms. A total of 2,733,524 AI records from 928,437 females in 5,967 Irish dairy herds were used. Sire predicted transmitting ability (PTA) values and associated reliability values for calving performance and carcass traits based on national genetic evaluations from prior to the insemination were used. Fixed effects models were used to relate both genetic merit and the associated reliability of the dairy and beef bulls used on the farm with herd size, the extent of Holstein-Friesian × Jersey crossbreeding adopted by the herd, whether the herd used a technician insemination service or do-ityourself, and the parity of the female mated. The mean direct calving difficulty PTA of the beef bulls used was 1.85 units higher than that of the dairy bulls but with over 3 times greater variability in the beef bulls. This 1.85 units equates biologically to an expectation of 1.85 more dystocia events per 100 dairy cows mated in the beef × dairy matings. The mean calving difficulty PTA of the dairy AI bulls used reduced with increasing herd size, whereas the mean calving difficulty PTA of the beef AI bulls used increased as herd size increased from 75 cows or fewer to 155 cows; the largest herds (>155 cows) used notably easier-calving beef bulls, albeit the calving difficulty PTA of the beef bulls was 3.33 units versus 1.67 units for the dairy bulls used in these herds. Although we found a general tendency for larger herds to use dairy AI bulls with lower reliability, this trend was not obvious in the beef AI bulls used. Irrespective of whether dairy or beef AI bulls were considered, herds that operated more extensive Holstein-Friesian × Jersey crossbreeding (i.e., more than 50% crossbred cows) used, on average, easier calving, shorter gestationlength bulls with lighter expected progeny carcasses of poorer conformation. Mean calving difficulty PTA of dairy bulls used increased from 1.39 in heifers to 1.79 in first-parity cows and to 1.82 in second-parity cows, remaining relatively constant thereafter. In contrast, the mean calving difficulty PTA of the beef bulls used increased consistently with cow parity. Results from the present study demonstrate a clear difference in the mean acceptable genetic merit of beef AI bulls relative to dairy AI bulls but also indicates that these acceptable limits vary by herd characteristics.
    • Comparative grazing behaviour of lactating suckler cows of contrasting genetic merit and genotype

      McCabe, S.; McHugh, Noirin; O'Connell, Niamh E.; Prendiville, Robert; Department of Agriculture, Food and the Marine; RSF 13/S4/96 (Elsevier, 2018-12-04)
      The objective of this study was to determine if differences in grazing behaviour exist between lactating suckler cows diverse in genetic merit for the national Irish Replacement index and of two contrasting genotypes. Data from 103 cows: 41 high and 62 low genetic merit, 43 beef and 60 beef x dairy (BDX) cows were available over a single grazing season in 2015. Milk yield, grass dry matter intake (GDMI), cow live weight (BW) and body condition score (BCS) were recorded during the experimental period, with subsequent measures of production efficiency extrapolated. Grazing behaviour data were recorded twice in conjunction with aforementioned measures, using Institute of Grassland and Environmental Research headset behaviour recorders. The effect of genotype and cow genetic merit during mid- and late-lactation on grazing behaviour phenotypes, milk yield, BW, BCS and GDMI were estimated using linear mixed models. Genetic merit had no significant effect on any production parameters investigated, with the exception that low genetic merit had a greater BCS than high genetic merit cows. Beef cows were heavier, had a greater BCS but produced less milk per day than BDX. The BDX cows produced more milk per 100 kg BW and per unit intake and had greater GDMI, intake per bite and rate of GDMI per 100 kg BW than beef cows. High genetic merit cows spent longer grazing and took more bites per day but had a lower rate of GDMI than low genetic merit cows, with the same trend found when expressed per unit of BW. High genetic merit cows spent longer grazing than low genetic merit cows when expressed on a per unit intake basis. Absolute rumination measures were similar across cow genotype and genetic merit. When expressed per unit BW, BDX cows spent longer ruminating per day compared to beef. However, on a per unit intake basis, beef cows ruminated longer and had more mastications than BDX. Intake per bite and rate of intake was positively correlated with GDMI per 100 kg BW. The current study implies that despite large differences in grazing behaviour between cows diverse in genetic merit, few differences were apparent in terms of production efficiency variables extrapolated. Conversely, differences in absolute grazing and ruminating behaviour measurements did not exist between beef cows of contrasting genotype. However, efficiency parameters investigated illustrate that BDX will subsequently convert herbage intake more efficiently to milk production.
    • 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 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra

      Soyeurt, H.; Grelet, C.; McParland, Sinead; Calmels, M.; Coffey, M.; Tedde, A.; Delhez, P.; Dehareng, F.; Gengler, N.; European Union; et al. (American Dairy Science Association, 2020-10-22)
      Lactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an interest in quantifying this biomolecule routinely. First prediction equations proposed in the literature to predict the content in milk using milk mid-infrared spectrometry were built using partial least square regression (PLSR) due to the limited size of the data set. Thanks to a large data set, the current study aimed to test 4 different machine learning algorithms using a large data set comprising 6,619 records collected across different herds, breeds, and countries. The first algorithm was a PLSR, as used in past investigations. The second and third algorithms used partial least square (PLS) factors combined with a linear and polynomial support vector regression (PLS + SVR). The fourth algorithm also used PLS factors, but included in an artificial neural network with 1 hidden layer (PLS + ANN). The training and validation sets comprised 5,541 and 836 records, respectively. Even if the calibration prediction performances were the best for PLS + polynomial SVR, their validation prediction performances were the worst. The 3 other algorithms had similar validation performances. Indeed, the validation root mean squared error (RMSE) ranged between 162.17 and 166.75 mg/L of milk. However, the lower standard deviation of cross-validation RMSE and the better normality of the residual distribution observed for PLS + ANN suggest that this modeling was more suitable to predict the LF content in milk from milk mid-infrared spectra (R2v = 0.60 and validation RMSE = 162.17 mg/L of milk). This PLS +ANN model was then applied to almost 6 million spectral records. The predicted LF showed the expected relationships with milk yield, somatic cell score, somatic cell count, and stage of lactation. The model tended to underestimate high LF values (higher than 600 mg/L of milk). However, if the prediction threshold was set to 500 mg/L, 82% of samples from the validation having a content of LF higher than 600 mg/L were detected. Future research should aim to increase the number of those extremely high LF records in the calibration set.
    • 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 milk production from clover-based and fertilizer-N-based grassland

      Humphreys, James; Casey, I.A.; Laidlaw, A.S. (Teagasc, Oak Park, Carlow, Ireland, 2009)
      This study, conducted over four years (2003–2006), compared herbage production, nutritive value of herbage, the length of the grazing season and milk production per cow and per hectare from grassland systems based on (i) white clover (average 219 g/kg of herbage DM) (WC) receiving on average N application of 90 kg/ha (s.d. 6.4) in spring and successive 0.2 of the area over-seeded annually with white clover seed and (ii) fertilizer N (FN) input of 226 kg/ha (s.d. 9.7). The stocking density of Holstein- Friesian dairy cows on both systems was 2.0/ha 2003 and 2.2/ha in each of the following three years. There were 22 cows per system in 2003 and 24 cows per system in each of the following three years. Cows calved within a 12 week interval in spring with mean calving date in mid-February. Milk was produced until mid-December each year. Total annual herbage DM production was lower (P < 0.01) on WC than FN (0.92 of FN). There were no (P > 0.05) differences in the in vitro organic matter digestibilities of pre-grazing herbage. The crude protein concentration in pre-grazing herbage DM was higher (P < 0.001) on FN than WC: 219 and 209 (s.e. 8.4.) g/kg, respectively. There were no (P > 0.05) differences in annual production of milk per cow (mean 6524 kg; s.e. 83.9 kg), live-weight or body condition score between the two systems. There were no (P < 0.05) differences in the lengths of the grazing season, which averaged 254 days (s.e. 0.9). Although there was no difference in performance per cow, the higher herbage production indicates that a higher stocking rate and milk output per hectare was possible from FN than WC. Nevertheless, the WC swards supported an annual stocking density of 2.15/ha and a milk output of 14 t/ha.
    • 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.
    • A Comparison of the Productivity of Suckler Cows of Different Breed Composition

      Drennan, Michael J; Murphy, B.M. (Teagasc, 2006-01-01)
      The findings obtained in a comparison of 5 suckler dam breed types {Limousin x Friesian (LF), Limousin x (Limousin x Friesian) (LLF), Limousin (L), Charolais (C) and Simmental x (Limousin x Friesian) (SLF)} and their progeny through to slaughter
    • Correction to: Residual feed intake phenotype and gender affect the expression of key genes of the lipogenesis pathway in subcutaneous adipose tissue of beef cattle

      McKenna, Clare; Porter, Richard K; Keogh, Kate; Waters, Sinead M.; McGee, Mark; Kenny, David A.; Teagasc Walsh Fellowship Programme (Biomed Central, 2018-11-07)
      In the original publication of this article [1], some errors in Table 4 need to be corrected as below:
    • 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.
    • Cow welfare in grass based milk production systems

      Boyle, Laura; Olmos, G.; Llamas Moya, S.; Palmer, M.A.; Gleeson, David E; O'Brien, Bernadette; Horan, Brendan; Berry, Donagh; Arkins, S.; Alonso Gómez, M.; et al. (Teagasc, 2008-08-01)
      Under this project, aspects of pasture based milk production systems, namely different milking frequency and feeding strategies as well as genetic selection for improved fitness using the Irish Economic Breeding Index (EBI) were evaluated in terms of dairy cow behaviour, health, immune function and reproductive performance. Additionally, a typical Irish pasture based system was compared to one in which cows were kept indoors in cubicles and fed a total mixed ration for the duration of lactation in order to elucidate the perceived benefits of pasture based systems for dairy cow welfare.
    • Daily and seasonal trends of electricity and water use on pasture-based automatic milking dairy farms

      Shortall, John; O'Brien, Bernadette; Sleator, Roy D.; Upton, John; Teagasc Walsh Fellowship Programme; European Union; 2012015; SME-2012-2-314879 (Elsevier, 2017-11-15)
      The objective of this study was to identify the major electricity and water-consuming components of a pasture-based automatic milking (AM) system and to establish the daily and seasonal consumption trends. Electricity and water meters were installed on 7 seasonal calving pasture-based AM farms across Ireland. Electricity-consuming processes and equipment that were metered for consumption included milk cooling components, air compressors, AM unit(s), auxiliary water heaters, water pumps, lights, sockets, automatic manure scrapers, and so on. On-farm direct water-consuming processes and equipment were metered and included AM unit(s), auxiliary water heaters, tubular coolers, wash-down water pumps, livestock drinking water supply, and miscellaneous water taps. Data were collected and analyzed for the 12-mo period of 2015. The average AM farm examined had 114 cows, milking with 1.85 robots, performing a total of 105 milkings/AM unit per day. Total electricity consumption and costs were 62.6 Wh/L of milk produced and 0.91 cents/L, respectively. Milking (vacuum and milk pumping, within-AM unit water heating) had the largest electrical consumption at 33%, followed by air compressing (26%), milk cooling (18%), auxiliary water heating (8%), water pumping (4%), and other electricity-consuming processes (11%). Electricity costs followed a similar trend to that of consumption, with the milking process and water pumping accounting for the highest and lowest cost, respectively. The pattern of daily electricity consumption was similar across the lactation periods, with peak consumption occurring at 0100, 0800, and between 1300 and 1600 h. The trends in seasonal electricity consumption followed the seasonal milk production curve. Total water consumption was 3.7 L of water/L of milk produced. Water consumption associated with the dairy herd at the milking shed represented 42% of total water consumed on the farm. Daily water consumption trends indicated consumption to be lowest in the early morning period (0300–0600 h), followed by spikes in consumption between 1100 and 1400 h. Seasonal water trends followed the seasonal milk production curve, except for the month of May, when water consumption was reduced due to above-average rainfall. This study provides a useful insight into the consumption of electricity and water on a pasture-based AM farms, while also facilitating the development of future strategies and technologies likely to increase the sustainability of AM systems.
    • Daily and seasonal trends of electricity and water use on pasture-based automatic milking dairy farms

      Shortall, John; O'Brien, Bernadette; Sleator, Roy D.; Upton, John; Teagasc Walsh Fellowship programme; European Union; 2012015; SME-2012-2-314879 (American Dairy Science Association, 2017-11-15)
      The objective of this study was to identify the major electricity and water-consuming components of a pasture-based automatic milking (AM) system and to establish the daily and seasonal consumption trends. Electricity and water meters were installed on 7 seasonal calving pasture-based AM farms across Ireland. Electricity-consuming processes and equipment that were metered for consumption included milk cooling components, air compressors, AM unit(s), auxiliary water heaters, water pumps, lights, sockets, automatic manure scrapers, and so on. On-farm direct water-consuming processes and equipment were metered and included AM unit(s), auxiliary water heaters, tubular coolers, wash-down water pumps, livestock drinking water supply, and miscellaneous water taps. Data were collected and analyzed for the 12-mo period of 2015. The average AM farm examined had 114 cows, milking with 1.85 robots, performing a total of 105 milkings/AM unit per day. Total electricity consumption and costs were 62.6 Wh/L of milk produced and 0.91 cents/L, respectively. Milking (vacuum and milk pumping, within-AM unit water heating) had the largest electrical consumption at 33%, followed by air compressing (26%), milk cooling (18%), auxiliary water heating (8%), water pumping (4%), and other electricity-consuming processes (11%). Electricity costs followed a similar trend to that of consumption, with the milking process and water pumping accounting for the highest and lowest cost, respectively. The pattern of daily electricity consumption was similar across the lactation periods, with peak consumption occurring at 0100, 0800, and between 1300 and 1600 h. The trends in seasonal electricity consumption followed the seasonal milk production curve. Total water consumption was 3.7 L of water/L of milk produced. Water consumption associated with the dairy herd at the milking shed represented 42% of total water consumed on the farm. Daily water consumption trends indicated consumption to be lowest in the early morning period (0300–0600 h), followed by spikes in consumption between 1100 and 1400 h. Seasonal water trends followed the seasonal milk production curve, except for the month of May, when water consumption was reduced due to above-average rainfall. This study provides a useful insight into the consumption of electricity and water on a pasture-based AM farms, while also facilitating the development of future strategies and technologies likely to increase the sustainability of AM systems.
    • 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.
    • Detection of presumptive Bacillus cereus in the Irish dairy farm environment

      O'Connell, Aine; Lawton, Elaine M.; Leong, Dara; Cotter, Paul D.; Gleeson, David E; Guinane, Caitriona M.; Teagasc Walsh Fellowship Programme (Teagasc (Agriculture and Food Development Authority), Ireland, 30/01/2016)
      The objective of the study was to isolate potential Bacillus cereus sensu lato (B. cereus s.l.) from a range of farm environments. Samples of tap water, milking equipment rinse water, milk sediment filter, grass, soil and bulk tank milk were collected from 63 farms. In addition, milk liners were swabbed at the start and the end of milking, and swabs were taken from cows’ teats prior to milking. The samples were plated on mannitol egg yolk polymyxin agar (MYP) and presumptive B. cereus s.l. colonies were isolated and stored in nutrient broth with 20% glycerol and frozen at -80 °C. These isolates were then plated on chromogenic medium (BACARA) and colonies identified as presumptive B. cereus s.l. on this medium were subjected to 16S ribosomal RNA (rRNA) sequencing. Of the 507 isolates presumed to be B. cereus s.l. on the basis of growth on MYP, only 177 showed growth typical of B. cereus s.l. on BACARA agar. The use of 16S rRNA sequencing to identify isolates that grew on BACARA confirmed that the majority of isolates belonged to B. cereus s.l. A total of 81 of the 98 isolates sequenced were tentatively identified as presumptive B. cereus s.l. Pulsed-field gel electrophoresis was carried out on milk and soil isolates from seven farms that were identified as having presumptive B. cereus s.l. No pulsotype was shared by isolates from soil and milk on the same farm. Presumptive B. cereus s.l. was widely distributed within the dairy farm environment.
    • Detection of selection signatures in dairy and beef cattle using high-density genomic information

      Zhao, Fuping; McParland, Sinead; Kearney, Francis; Du, Lixin; Berry, Donagh; Department of Agriculture, Food and the Marine; Agricultural Science and Technology Innovation Program; Natural Science Foundation of China; 11/S/112; ASTIP-IAS-TS-6 (Biomed Central, 2015-06-19)
      Background Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs. Results Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (FST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the FST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global FST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection. Conclusions This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.
    • Development of a benchmarking system for Irish beef farms using data envelopment analysis

      Finneran, Eoghan; Crosson, Paul (2013)
      Agricultural extension trends have involved greater use of collaborative “discussion group” dissemination approaches. These discussion groups involve regular participatory meetings between a consistent cohort of farmers and extension practitioners with occasional input from industry and research stakeholders. In Ireland, policy change, small farm scale and low incomes are some of the factors incentivising beef farmers and industry to seek increased whole-farm income efficiency. Whole-farm comparative analysis may provide a means of identifying and explaining efficiency drivers at farm level. This article describes the development of BEEFMARK, a benchmarking model with potential to act as a tool to facilitate farmer-farmer and farmer-adviser group learning within discussion groups. BEEFMARK utilised Data Envelopment Analysis (DEA) to measure beef farm income and scale efficiency and to identify and characterise efficient peer farms which act as benchmarks for similarly structured, but lower efficiency farms. Market derived gross output (€) per livestock unit was positively associated with farm efficiency while greater overhead and concentrate feed expenditure was negatively associated with income and scale efficiency.
    • 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.