• Beef Cross Breeding of Dairy and Beef Cows

      Keane, Michael G. (Teagasc, 2011-03-01)
      Summary The rationale for crossing dairy cows with beef bulls is to increase the beef productivity and value of the progeny. The proportion of dairy cows available for beef crossing is determined by the dairy herd replacement rate. The performance of cross-bred cattle is generally superior to the mean of the parent breeds because of heterosis. This is most pronounced for reproduction, maternal and calf survival traits. Crossing dairy cows with early maturing beef breeds (e.g. Angus, Hereford) has little effect on growth but improves carcass conformation and reduces feed intake. Crossing with most late maturing beef breeds also improves carcass conformation and reduces feed intake, but in addition, growth rate, kill-out proportion and carcass muscle proportion are increased. Cross breeding can have small negative effects on dam milk production, and subsequent reproduction can be impaired following a long gestation or difficult calving. There is little advantage in crossing with double muscled sire breeds (e.g. Belgian Blue, Piedmontese) compared with the larger conventional late maturing breeds (e.g. Charolais, Blonde d'Aquitaine). There are few effects of sire breed on meat quality.
    • Beef production from feedstuffs conserved using new technologies to reduce negative environmental impacts

      O'Kiely, Padraig; Crosson, Paul; Hamilton, William J.; Little, Enda; Stacey, Pamela; Walsh, Karl; Black, Alistair D; Crowley, James C.; Drennan, Michael J; Forristal, Dermot; et al. (Teagasc, 2007-12-01)
      Most (ca. 86%) Irish farms make some silage. Besides directly providing feed for livestock, the provision of grass silage within integrated grassland systems makes an important positive contribution to effective grazing management and improved forage utilisation by grazing animals, and to effective feed budgeting by farmers. It can also contribute to maintaining the content of desirable species in pastures, and to livestock not succumbing to parasites at sensitive times of the year. Furthermore, the optimal recycling of nutrients collected from housed livestock can often be best achieved by spreading the manures on the land used for producing the conserved feed. On most Irish farms, grass silage will remain the main conserved forage for feeding to livestock during winter for the foreseeable future. However, on some farms high yields of whole-crop (i.e. grain + straw) cereals such as wheat, barley and triticale, and of forage maize, will be an alternative option provided that losses during harvesting, storage and feedout are minimised and that input costs are restrained. These alternative forages have the potential to reliably support high levels of animal performance while avoiding the production of effluent. Their production and use however will need to advantageously integrate into ruminant production systems. A range of technologies can be employed for crop production and conservation, and for beef production, and the optimal options need to be identified. Beef cattle being finished indoors are offered concentrate feedstuffs at rates that range from modest inputs through to ad libitum access. Such concentrates frequently contain high levels of cereals such as barley or wheat. These cereals are generally between 14% to 18% moisture content and tend to be rolled shortly before being included in coarse rations or are more finely processed prior to pelleting. Farmers thinking of using ‘high-moisture grain’ techniques for preserving and processing cereal grains destined for feeding to beef cattle need to know how the yield, conservation efficiency and feeding value of such grains compares with grains conserved using more conventional techniques. European Union policy strongly encourages a sustainable and multifunctional agriculture. Therefore, in addition to providing European consumers with quality food produced within approved systems, agriculture must also contribute positively to the conservation of natural resources and the upkeep of the rural landscape. Plastics are widely used in agriculture and their post-use fate on farms must not harm the environment - they must be managed to support the enduring sustainability of farming systems. There is an absence of information on the efficacy of some new options for covering and sealing silage with plastic sheeting and tyres, and an absence of an inventory of the use, re-use and post-use fate of plastic film on farms. Irish cattle farmers operate a large number of beef production systems, half of which use dairy bred calves. In the current, continuously changing production and market conditions, new beef systems must be considered. A computer package is required that will allow the rapid, repeatable simulation and assessment of alternate beef production systems using appropriate, standardised procedures. There is thus a need to construct, evaluate and utilise computer models of components of beef production systems and to develop mathematical relationships to link system components into a network that would support their integration into an optimal system model. This will provide a framework to integrate physical and financial on-farm conditions with models for estimating feed supply and animal growth patterns. Cash flow and profit/loss results will be developed. This will help identify optimal systems, indicate the cause of failure of imperfect systems and identify areas where applied research data are currently lacking, or more basic research is required.
    • Bioeconomic modelling of male Holstein-Friesian dairy calf-to-beef production systems on Irish farms

      Ashfield, A.; Wallace, Michael; Prendiville, Robert; Crosson, Paul (Teagasc (Agriculture and Food Development Authority), Ireland, 2014)
      With the abolition of milk quota in 2015 and increase in the use of Holstein-Friesian sires in recent years there is predicted to be an increase in the number of male Holstein-Friesian animals available for beef production. In broad terms, farmers have two options for finishing these animals; as bulls or steers. In either case, Irish beef cattle systems are based on maximising lifetime live-weight gain from grass-based diets. Managing the relationship between the supply and demand for grazed grass is complicated in these pasture-based systems due to the seasonal variability in grass growth. The Grange Dairy Beef Systems Model (GDBSM) was used to simulate the relationship between grazed grass supply and demand and then determine the profitability of Holstein-Friesian male animals finished as bulls at 16 (B16), 19 (B19) and 22 (B22) months of age and steers at 24 (S24) months of age. Combinations of these cattle finishing options were also evaluated. The most profitable system was S24. All systems were very sensitive to variations in beef and concentrate prices and less sensitive to calf price changes with fertiliser price changes having very little effect. Bull systems were more sensitive than the steer system to variation in beef, calf and concentrate prices. There was no advantage of combination systems in terms of utilisation of grass grown or net margin.
    • Body and carcass measurements, carcass conformation and tissue distribution of high dairy genetic merit Holstein, standard dairy genetic merit Friesian and Charolais x Holstein-Friesian male cattle

      McGee, Mark; Keane, Michael G.; Neilan, R.; Moloney, Aidan P; Caffrey, Patrick J. (Teagasc, Oak Park, Carlow, Ireland, 2007)
      The increased proportion of Holstein genes in the dairy herd may have undesirable consequences for beef production in Ireland. A total of 72 spring-born calves, (24 Holstein (HO), 24 Friesian (FR) and 24 Charolais X Holstein-Friesian (CH)) were reared from calfhood to slaughter. Calves were artificially reared indoors and spent their first summer at pasture following which they were assigned to a 3 breeds (HO, FR and CH) 2 production systems (intensive 19-month bull beef and extensive 25-month steer beef) 2 slaughter weights (560 and 650 kg) factorial experiment. Body measurements of all animals were recorded at the same time before the earliest slaughter date. After slaughter, carcasses were graded and measured and the pistola hind-quarter was separated into fat, bone and muscle. HO had significantly higher values for withers height, pelvic height and chest depth than FR, which in turn had higher values than CH. HO had a longer back and a narrower chest than either FR or CH, which were not significantly different. Carcass length and depth, pistola length, and leg length were 139.2, 134.4 and 132.0 (s.e. 0.81), 52.1, 51.3 and 47.7 (s.e. 0.38), 114.4, 109.0 and 107.0 (s.e. 0.65) and 76.7, 71.9 and 71.4 (s.e. 0.44) cm for HO, FR and CH, respectively. Breed differences in pistola tissue distribution between the joints were small and confined to the distal pelvic limb and ribs. There were relatively small breed differences in the distribution of pistola muscle weight between individual muscles. Body measurements were significantly greater for animals on the intensive system (bulls) than the extensive system (steers) in absolute terms, but the opposite was so when they were expressed relative to live weight. The only significant difference in relative carcass measurements between the production systems was for carcass depth, which was lower for the intensive compared with the extensive system. Increasing slaughter weight significantly increased all carcass measurements in absolute terms but reduced them relative to weight. It is concluded that there were large differences between the breed types in body and carcass measurements, and hence in carcass shape and compactness but differences in tissue distribution were small.
    • 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.
    • 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.