Now showing items 1-20 of 711

    • Red clover: A promising pasture legume for Ireland

      Weldon, B. A.; O'Kiely, P. (2021-04-11)
      Red clover is considered a very productive but short lived perennial legume. Previous research has shown attractive yields for red clover in the first year after establishment (O’Kiely et al., 2006). This experiment quantified the impacts of cultivar, companion grass, harvest schedule and nitrogen fertiliser on crop yield in the sixth year after establishment, and compared these to grass receiving inorganic N fertiliser.
    • Phenotypic relationships between milk protein percentage and reproductive performance in three strains of Holstein Friesian cows in Ireland

      Yang, L; Lopez-Villalobos, N; Berry, Donagh; Parkinson, T (2021-04-11)
      The relationship between milk protein percentage and fertility in seasonal calving, dairy cattle in Ireland was quantified using a total of 584 lactation records, collected over a five-year period from experiments comparing three strains of Holstein-Friesian cows under three different feeding systems. Logistic regression analyses showed that increased protein percentage during early lactation was positively associated with the probability of a cow becoming pregnant to its first service (P <0.05). Similarly, protein percentage during the lactation had a positive (P <0.01) association with overall pregnancy rate. The results suggest that negative energy balance in early lactation or during the whole lactation causes a shortage of glucose to the udder, this restricts the synthesis of milk protein in the udder and causes a lower milk protein percentage. During negative energy balance there is also a concurrent reduction of IGF-І, LH and oestradiol secretion, which consequently delay ovarian follicular development, and hence impairs reproductive performance. In conclusion, cows with higher milk protein percentage during early lactation have a greater likelihood of becoming pregnant earlier in the breeding season, and have a higher conception rate.
    • Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods.

      Frizzarin, Maria; Gormley, I. C.; Berry, Donagh; Murphy, T. B.; Casa, A.; Lynch, A.; McParland, Sinead; Science Foundation Ireland; Department of Agriculture, Food and the Marine; 18/SIRG/5562; et al. (Elsevier for American Dairy Science Association, 2021)
      Numerous statistical machine learning methods suitable for application to highly correlated features, as exists for spectral data, could potentially improve prediction performance over the commonly used partial least squares approach. Milk samples from 622 individual cows with known detailed protein composition and technological trait data accompanied by mid-infrared spectra were available to assess the predictive ability of different regression and classification algorithms. The regression-based approaches were partial least squares regression (PLSR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO), elastic net, principal component regression, projection pursuit regression, spike and slab regression, random forests, boosting decision trees, neural networks (NN) and a post-hoc approach of model averaging (MA). Several classification methods (i.e., partial least squares discriminant analysis (PLSDA), random forests, boosting decision trees, and support vector machines (SVM)) were also used after stratifying the traits of interest into categories. In the regression analyses, MA was the best prediction method for 6 of the 14 traits investigated (a60, alpha s1 CN, alpha s2 CN, kappa CN, alpha lactalbumin, and beta lactoglobulin B), while NN and RR were the best algorithms for 3 traits each (RCT, k20, and heat stability, and a30, beta CN, and beta lactoglobulin A, respectively), PLSR was best for pH and LASSO was best for CN micelle size. When traits were divided into two classes, SVM had the greatest accuracy for the majority of the traits investigated. While the well-established PLSR-based method performed competitively, the application of statistical machine learning methods for regression analyses reduced the root mean square error when compared to PLSR from between 0.18% (kappa CN) to 3.67% (heat stability). The use of modern statistical ML methods for trait prediction from MIRS may improve the prediction accuracy for some traits.
    • Application of the TruCulture® whole blood stimulation system for immune response profiling in cattle

      O’Brien, Megan B.; McLoughlin, Rachel M.; Meade, Kieran G.; Teagasc Walsh Fellowship Programme; 0005GE (Elsevier BV, 2020-03)
      Capturing the phenotypic variation in immune responses holds enormous promise for the development of targeted treatments for disease as well as tailored vaccination schedules. However, accurate detection of true biological variation can be obscured by the lack of standardised immune assays. The TruCulture® whole blood stimulation system has now been extensively used to detect basal and induced immune responses to a range of pathogen-associated molecular patterns (PAMPs) in human peripheral blood. This study demonstrates the optimisation of this commercially available assay for systemic immune phenotyping in cattle. The early immune response in Holstein-Friesian bull calves (n = 10) was assessed by haematology, flow cytometry and cytokine expression profiling after 24 h ex-vivo PAMP (LPS, poly (I:C) and zymosan) stimulation in TruCulture® tubes. A comparative analysis was also performed with a traditional whole blood stimulation assay and cell viability using both systems was also evaluated. Results: Supernatant collected from TruCulture® tubes showed a significant increase in IL-1β and IL-8 expression compared to null stimulated tubes in response to both LPS and zymosan. In contrast, a detectable immune response was not apparent at the standard concentration of poly (I:C). Conventional whole blood cultures yielded similar response profiles, although the magnitude of the response was higher to both LPS and zymosan, which may be attributed to prokaryotic strain-specificity or batch of the stimulant used. Despite being a closed system, HIF1A expression – used as a measure of hypoxia was not increased, suggesting the TruCulture® assay did not negatively affect cell viability. This represents the first reported use of this novel standardised assay in cattle, and indicates that the concentration of poly (I:C) immunogenic in humans is insufficient to induce cytokine responses in cattle. We conclude that the low blood volume and minimally invasive TruCulture® assay system offers a practical and informative technique to assess basal and induced systemic immune responses in cattle.
    • Enrichment use in finishing pigs and its relationship with damaging behaviours: Comparing three wood species and a rubber floor toy

      Chou, Jen-Yun; D’Eath, Rick B.; Sandercock, Dale A.; O’Driscoll, Keelin; Teagasc Walsh Fellowship Programme; Department of Agriculture, Food and the Marine; Scottish Government; 14/S/871 (Elsevier BV, 2020-03)
      Environmental enrichment in pig housing is a legal requirement under current EU legislation, but some recommended loose materials may cause obstructions in fully-slatted systems. Wood is an organic material that could be compatible with slatted systems. This study investigated enrichment use in finishing pigs (three wood species and a rubber floor toy) and explored the relationship between use and damaging behaviours, and physiological and physical measures of stress and injury. Individual variation in enrichment use within pen was also investigated. Pigs (12 weeks old; week 0) were housed in 40 pens of seven pigs (n = 280). One of four different enrichment items (one spruce, larch, or beech wooden post, or rubber floor toy) was randomly assigned to each pen (10 pens/treatment). The behaviour of each individually marked pig was observed continuously from video recordings taken on six different occasions (twice during week 2, 4 and 7; 1 h per occasion). Individual tail/ear lesion and tear staining scores were recorded every 2 weeks. Saliva samples for cortisol analysis were obtained from three focal pigs per pen every 2 weeks. These focal pigs were selected based on the latency to approach the experimenter on the first sampling day and classified as ‘Approach’, ‘Neutral’ or ‘Avoid’. Carcasses were inspected for tail lesions and potential oral damage. Time spent using enrichment was higher in pigs with spruce and rubber toy than with larch and beech (P < 0.001). Spruce was used up the most quickly and was the softest of the wood species (P < 0.001). High use of spruce was not due to consistent high use by certain pigs. No treatment effect on any other behaviour was recorded, but enrichment use was positively correlated with damaging behaviours at pen level (P < 0.001). Spruce pigs had slightly more severe tail lesion scores than Beech (P < 0.05). Salivary cortisol did not differ between treatments but was higher in ‘Avoid’ than ‘Approach’ pigs (P = 0.04). No clear oral damage that could be attributed to using wood was found. By investigating enrichment use at both pen and individual level, a more complete picture was obtained of how pigs used the enrichment. Wood appears to be a safe material to use as environmental enrichment for pigs and a softer wood species was preferred by pigs with equal preference for the rubber floor toy.
    • Grazing of Dairy Cows in Europe—An In-Depth Analysis Based on the Perception of Grassland Experts

      van den Pol-van Dasselaar, Agnes; Hennessy, Deirdre; Isselstein, Johannes (MDPI AG, 2020-02-04)
      Grazing is inherently close to the nature of herbivores, but no longer applied everywhere in Europe. Therefore, the perception of grassland experts on the occurrence, importance, constraints, solutions and future of grazing of dairy cows was studied. The study builds on results from the European Grassland Federation Working Group Grazing in the period 2010–2019. Both surveys and focus group meetings were used. There is a clear trend of reduced grazing in Europe. Since grazing is valued by different stakeholders and provides many ecosystem services, solutions to the constraints to grazing must be found. Constraints can be divided into region specific constraints, farm specific constraints and farmer specific constraints. The solutions include developing new knowledge, bringing the knowledge already available to practice and rewarding farmers for grazing as a service to society. If grazing is not supported, it will further decline. However, a joined endeavour has the potential to make a significant difference in transforming grass-based production systems and stimulating grazing.
    • Reproductive efficiency and survival of Holstein-Friesian cows of divergent Economic Breeding Index, evaluated under seasonal calving pasture-based management

      O'Sullivan, Morgan; Butler, Stephen; Pierce, K. M.; Crowe, M; O'Sullivan, K; Fitzgerald, R; Buckley, F (Elsevier for American Dairy Science Association, 2020-02)
      The objective of the current study was to examine phenotypic fertility performance and survival, and to gain insight into underlying factors that may contribute to greater fertility performance in 2 divergent genetic groups (GG) of Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 4 yr. The 2 divergent GG were (1) high EBI; representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year, 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. No interaction between GG and FT was observed for any of the measures of fertility investigated. The elite cows achieved significantly greater pregnancy rate to first service (+14.9 percentage points), and significantly greater pregnancy rates after 21, 42, and 84 d of breeding (+17.3, +15.2, and +9.6 percentage points, respectively) compared with NA. The number of services per cow was fewer for elite (1.57) compared with NA (1.80). The interval from mating start date to pregnancy was significantly shorter for elite cows compared with NA. The elite cows maintained greater mean body condition score than NA throughout the study (2.91 vs. 2.72), and had greater body condition score at calving, artificial insemination, and drying off compared with NA. The elite cows had greater mean circulating concentrations of insulin-like growth factor-1 compared with NA. No significant effect was observed of GG on commencement of luteal activity, or progesterone profile variables. Greater survival to the start of fifth lactation was observed for elite cows. The elite cows were 43% less likely to be culled than NA by the beginning of the fifth lactation. The results highlight the success of the Economic Breeding Index to deliver reproductive performance and longevity consistent with industry targets across a range of seasonal pasture-based FT. The results also clearly demonstrate the potential of appropriate genetic selection to reverse negative fertility trends incurred during previous decades of selection for milk production alone.
    • Leveraging Social Network Analysis for Characterizing Cohesion of Human-Managed Animals

      Vimalajeewa, Dixon; Balasubramaniam, Sasitharan; O'Brien, Bernadette; Kulatunga, Chamil; Berry, Donagh P.; Science Foundation Ireland; Department of Agriculture, Food and the Marine; European Union; 13/1A/1977; 16/RC/3835; et al. (Institute of Electrical and Electronics Engineers (IEEE), 2019-04)
      Social network analysis (SNA) is a technique to study behavioral dynamics within a social group. In SNA, it is an open question whether it is possible to characterize animal-level behaviors by using group-level information. Also, it was believed that the combined use of SNA would provide a more comprehensive understanding of social dynamics. In light of these two factors, here we explain an approach to evaluate animal importance to a group by considering the variability in group-level structural information, which is computed by joining the animal- and group-level SNA measures node centrality and network entropy, respectively. Moreover, two other metrics, animal social interaction range and nearest-neighbor frequency matrix, which represent a social affiliation of each animal within the group, are computed to help address the general challenges in graph-based SNA and, thereby, improve the precision of animal importance measures. Finally, we derive the joint distribution of animal importance of the group in detecting atypical social behaviors. The approach is tested using tracking data of dairy cows. The reliability of the derived animal importance was superior to the already existing animal importance measures. To illustrate the usability of the animal importance metric, a simulation study was conducted to identify sick and estrus animals in a group. The social affiliation of sick cows was less when compared to healthy cows. Also, their individual distributions of animal importance were shifted toward the left of the mean of the animal importance distributions of healthy cows. Consequently, the joint distribution of animal importance of the group exhibited a bimodal distribution with a left tailored shape. The behavior of cows in estrus was opposite to that of sick cows. Moreover, with the increasing number of sick and estrus cows in the group, respectively, the group entropy decreased with larger variance and slightly increased with less variance. Therefore, the entropy-based animal importance metric has superior performances when evaluating animal importance to the group compared to the existing metrics. It can be used for generating alerts for the early detection of atypical social behaviors associated with, for instance, animal health, veterinary, and welfare.
    • Breed- and trait-specific associations define the genetic architecture of calving performance traits in cattle

      Purfield, Deirdre C; Evans, Ross D; Berry, Donagh; European Union; Science Foundation Ireland; 727213; 14/IA/2576); 16/RC/3835 (Oxford University Press (OUP), 2020-05-04)
      Reducing the incidence of both the degree of assistance required at calving, as well as the extent of perinatal mortality (PM) has both economic and societal benefits. The existence of heritable genetic variability in both traits signifies the presence of underlying genomic variability. The objective of the present study was to locate regions of the genome, and by extension putative genes and mutations, that are likely to be underpinning the genetic variability in direct calving difficulty (DCD), maternal calving difficulty (MCD), and PM. Imputed whole-genome single-nucleotide polymorphism (SNP) data on up to 8,304 Angus (AA), 17,175 Charolais (CH), 16,794 Limousin (LM), and 18,474 Holstein-Friesian (HF) sires representing 5,866,712 calving events from descendants were used. Several putative quantitative trait loci (QTL) regions associated with calving performance both within and across dairy and beef breeds were identified, although the majority were both breed- and trait-specific. QTL surrounding and encompassing the myostatin (MSTN) gene were associated (P < 5 × 10−8) with DCD and PM in both the CH and LM populations. The well-known Q204X mutation was the fifth strongest association with DCD in the CH population and accounted for 5.09% of the genetic variance in DCD. In contrast, none of the 259 segregating variants in MSTN were associated (P > × 10−6) with DCD in the LM population but a genomic region 617 kb downstream of MSTN was associated (P < 5 × 10−8). The genetic architecture for DCD differed in the HF population relative to the CH and LM, where two QTL encompassing ZNF613 on Bos taurus autosome (BTA)18 and PLAG1 on BTA14 were identified in the former. Pleiotropic SNP associated with all three calving performance traits were also identified in the three beef breeds; 5 SNP were pleiotropic in AA, 116 in LM, and 882 in CH but no SNP was associated with more than one trait within the HF population. The majority of these pleiotropic SNP were on BTA2 surrounding MSTN and were associated with both DCD and PM. Multiple previously reported, but also novel QTL, associated with calving performance were detected in this large study. These also included QTL regions harboring SNP with the same direction of allele substitution effect for both DCD and MCD thus contributing to a more effective simultaneous selection for both traits.
    • On-farm net benefit of genotyping candidate female replacement cattle and sheep

      Newton, J.E.; Berry, Donagh; Science Foundation Ireland; Department of Agriculture, Food and the Marine; European Union; 16/RC/3835; 727213 (Elsevier BV, 2020-12-07)
      The net benefit from investing in any technology is a function of the cost of implementation and the expected return in revenue. The objective of the present study was to quantify, using deterministic equations, the net monetary benefit from investing in genotyping of commercial females. Three case studies were presented reflecting dairy cows, beef cows and ewes based on Irish population parameters; sensitivity analyses were also performed. Parameters considered in the sensitivity analyses included the accuracy of genomic evaluations, replacement rate, proportion of female selection candidates retained as replacements, the cost of genotyping, the sire parentage error rate and the age of the female when it first gave birth. Results were presented as an annualised monetary net benefit over the lifetime of an individual, after discounting for the timing of expressions. In the base scenarios, the net benefit was greatest for dairy, followed by beef and then sheep. The net benefit improved as the reliability of the genomic evaluations improved and, in fact, a negative net benefit of genotyping was less frequent when the reliability of the genomic evaluations was high. The impact of a 10% point increase in genomic reliability was, however, greatest in sheep, followed by beef and then dairy. The net benefit of genotyping female selection candidates reduced as replacement rate increased. As genotyping costs increased, the net benefit reduced irrespective of the percentage of selection candidates kept, the replacement rate or even the population considered. Nonetheless, the association between the genotyping cost and the net benefit of genotyping differed by the percentage of selection candidates kept. Across all replacement rates evaluated, retaining 25% of the selection candidates resulted in the greatest net benefit when genotyping cost was low but the lowest net benefit when genotyping cost was high. Genotyping breakeven cost was non-linearly associated with the percentage of selection candidates retained, reaching a maximum when 50% of selection candidates were retained, irrespective of replacement rate, genomic reliability or the population. The genotyping breakeven cost was also non-linearly associated with replacement rate. The approaches outlined within provide the back-end framework for a decision support tool to quantify the net benefit of genotyping, once parameterised by the relevant population metrics.
    • Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid‐infrared spectra

      Vanlierde, Amélie; Dehareng, Frédéric; Gengler, Nicolas; Froidmont, Eric; McParland, Sinead; Kreuzer, Michael; Bell, Matthew; Lund, Peter; Martin, Cécile; Kuhla, Björn; et al. (Wiley, 2020-11-22)
      BACKGROUND A robust proxy for estimating methane (CH4) emissions of individual dairy cows would be valuable especially for selective breeding. This study aimed to improve the robustness and accuracy of prediction models that estimate daily CH4 emissions from milk Fourier transform mid‐infrared (FT‐MIR) spectra by (i) increasing the reference dataset and (ii) adjusting for routinely recorded phenotypic information. Prediction equations for CH4 were developed using a combined dataset including daily CH4 measurements (n = 1089; g d−1) collected using the SF6 tracer technique (n = 513) and measurements using respiration chambers (RC, n = 576). Furthermore, in addition to the milk FT‐MIR spectra, the variables of milk yield (MY) on the test day, parity (P) and breed (B) of cows were included in the regression analysis as explanatory variables. RESULTS Models developed based on a combined RC and SF6 dataset predicted the expected pattern in CH4 values (in g d−1) during a lactation cycle, namely an increase during the first weeks after calving followed by a gradual decrease until the end of lactation. The model including MY, P and B information provided the best prediction results (cross‐validation statistics: R2 = 0.68 and standard error = 57 g CH4 d−1). CONCLUSIONS The models developed accounted for more of the observed variability in CH4 emissions than previously developed models and thus were considered more robust. This approach is suitable for large‐scale studies (e.g. animal genetic evaluation) where robustness is paramount for accurate predictions across a range of animal conditions. © 2020 Society of Chemical Industry
    • 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.
    • 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

      Parmar, Puneet; Lopez-Villalobos, Nicolas; Tobin, John T.; Murphy, Eoin; McDonagh, Arleen; Crowley, Shane V.; Kelly, Alan L.; Shalloo, Laurence; Enterprise Ireland; Science Foundation Ireland; et al. (MDPI AG, 2020-07-27)
      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.
    • Fertility of frozen sex-sorted sperm at 4 × 106 sperm per dose in lactating dairy cows in seasonal-calving pasture-based herds

      Maicas, C.; Holden, S.A.; Drake, E.; Cromie, A.R.; Lonergan, P.; Butler, S.T.; Irish Dairy Levy Trust; Munster Bovine; Meat Industry Ireland; Glanbia; et al. (American Dairy Science Association, 2019-09-23)
      The objective was to evaluate the reproductive performance of frozen sex-sorted sperm at 4 × 106 sperm per dose (SexedULTRA 4M, Sexing Technologies, Navasota, TX) relative to frozen conventional sperm in seasonal-calving pasture-based dairy cows. Semen from Holstein-Friesian (n = 8) and Jersey (n = 2) bulls was used. Four of the Holstein bulls used were resident at or near a sex-sorting laboratory (Cogent, UK, or ST Benelux, the Netherlands). The remaining 6 bulls were located at studs in Ireland. For these 6 bulls, ejaculates were collected, diluted with transport medium, and couriered to Cogent in parcel shippers. Transit time from ejaculation to arrival at the sorting laboratory was 6 to 7 h. For all bulls, ejaculates were split and processed to provide frozen conventional sperm (CONV) at 15 × 106 sperm per straw and frozen sex-sorted (SS) sperm at 4 × 106 sperm per straw and used to inseminate lactating dairy cows after spontaneous estrus. Pregnancy diagnosis was performed by ultrasound scanning (n = 7,246 records available for analysis). Generalized linear mixed models were used to examine effects on pregnancy per AI (P/AI) at first artificial insemination, with sperm treatment (CONV vs. SS), bull (n = 10), and treatment × bull interaction as the fixed effects, and herd (n = 142) as a random effect. Overall, P/ AI was greater for cows inseminated with CONV than for those inseminated with SS (59.9% vs. 45.5%; 76.0% relative to CONV). This study was not designed to compare resident bulls vs. shipped ejaculates, but the magnitude of the difference between P/AI achieved by CONV and SS was apparently less for resident bulls (60.3% vs. 50.2%) than for shipped ejaculates (58.6% vs. 40.7%). We discovered a treatment × bull interaction for shipped ejaculates (P/AI ranged from 45 to 86% relative to CONV) but not for the resident bulls (P/AI ranged from 81 to 87% relative to CONV). Relative P/AI of SS compared with CONV was greater in cows with high or average fertility potential (76.1% and 78.3%, respectively) than in cows with low fertility potential (58.1%). In 33.1% of the enrolled herds, the P/AI achieved with SS was 90% or more of the P/ AI achieved with CONV; this was mainly explained by herds in which SS performed exceptionally well but CONV performed poorly. In conclusion, SS had lower overall P/AI compared with CONV; however, P/AI achieved with SS was dependent on the bull, fertility potential of the cow, and herd. Strategies to improve the P/AI with SS in seasonal-calving pasture-based lactating dairy cows require further research.
    • Associations between postpartum phenotypes, cow factors, genetic traits, and reproductive performance in seasonal-calving, pasture-based lactating dairy cows

      Rojas Canadas, E.; Herlihy, M.M.; Kenneally, J.; Grant, J.; Kearney, F.; Lonergan, P.; Butler, S.T.; Department of Agriculture, Food and the Marine; RSF 13S528 (American Dairy Science Association, 2020-01)
      The objective of this study was to evaluate associations between corpus luteum (CL) status, uterine health, body condition score (BCS), metabolic status, parity, genetic merit for fertility traits, and reproductive performance in pasture-based dairy cows managed for seasonal reproduction. First- and second-lactation (n = 2,600) spring-calving dairy cows from 35 dairy farms located in Ireland were enrolled in the study. Farms were visited every 2 wk, and animals that were at wk 3 (range: 14–27 d in milk) and wk 7 (range: 42–55 d in milk) postpartum were examined. Body condition score was measured using a 1-to-5 scale in 0.25-point increments. Transrectal ultrasound examination was performed at wk 3 and 7 postpartum to determine presence or absence of CL and ultrasound reproductive tract score (scale of G1–G4). Blood samples were collected at each visit, and the concentrations of glucose, β-hydroxybutyrate (BHB), and fatty acids (FA) were analyzed using enzymatic colorimetry. Animals were grouped into 3 BCS categories [low (≤2.5), target (2.75–3.25), and high (≥3.5)], 2 CL categories (present or absent), 2 uterine health status categories (normal or abnormal), and 3 metabolic status categories [good (high glucose, low FA and BHB), poor (low glucose, high FA and BHB), and moderate (all other combinations)]. Fisher's exact test was used to test for associations between variables and was supplemented by logistic regression. More cows with a CL at wk 7 were served during the first 21 d of the breeding period compared with cows without a CL. Cows classified as having a uterine score of G3 or G4 at wk 3 and 7 had lower odds of pregnancy establishment during the breeding period compared with animals with a uterine score of G1 or G2. Animals with low BCS at wk 7 had lower odds of pregnancy establishment than cows with a target BCS. Cows classified as having good metabolic status at both wk 3 and wk 7 had greater odds of pregnancy establishment during the first 21 d of the breeding season than those classified as having poor metabolic status. Overall, primiparous cows had greater reproductive performance than second-parity cows. Animals in the quartiles with the best predicted transmitting ability for survival and calving interval had better reproductive performance compared with animals in the other quartiles. Cows that had better genetic merit for fertility traits and good metabolic status, achieved target BCS, and had a favorable ultrasound reproductive tract score and a CL present at wk 7 postpartum had superior reproductive performance.
    • Associations between postpartum fertility phenotypes and genetic traits in seasonal-calving, pasture-based lactating dairy cows

      Rojas Canadas, E.; Herlihy, M.M.; Kenneally, J.; Grant, J.; Kearney, F.; Lonergan, P.; Butler, Stephen; Department of Agriculture, Food and the Marine; RSF13S528 (Elsevier for American Dairy Science Association, 2019-10-01)
      The objective of this study was to evaluate the associations between corpus luteum (CL) status, uterine health, body condition score (BCS), metabolic status, and parity at wk 3 and 7 postpartum in seasonal-calving, pasture-based, lactating dairy cows. The associations between those phenotypes and individual genetic traits were also evaluated. First- and second-parity spring-calving lactating dairy cows (n = 2,600) from 35 dairy farms in Ireland were enrolled. Farms were visited every 2 weeks; cows that were at wk 3 (range 14 to 27 DIM) and wk 7 (range 42 to 55 DIM) postpartum were examined. Body condition score was measured using a scale of 1 to 5 with 0.25 increments. Transrectal ultrasound examination was performed at wk 3 and 7 postpartum to determine presence or absence of CL and ultrasound reproductive tract score. Blood samples were collected at each visit and the concentrations of glucose, β-hydroxybutyrate (BHB), and fatty acids (FA) were analyzed by using enzymatic colorimetry. Cows were grouped into 3 BCS categories [low (≤2.5), target (≥2.75 and ≤3.25), and high (≥3.5)]; 2 CL status categories: (present or absent); 2 uterine health status (UHS) categories (normal and abnormal); and 3 metabolic status categories [good (high glucose, low fatty acids and BHB), poor (low glucose, high fatty acids and BHB), and moderate (all other combinations)]. Fisher's exact test was used to test associations between variables and was supplemented by logistic regression. We found associations between UHS (wk 3 and 7), BCS (wk 3 and 7), parity (wk 3 and 7) metabolic status (wk 3), and predicted transmitting ability for calving interval (PTA for CIV; wk 3) and CL status. Cows that had abnormal UHS, low BCS, primiparity, and poor metabolic status, and were in the quartile with the greatest PTA for CIV were less likely to have had CL present at wk 3 and 7 postpartum. We also found associations between CL status (wk 3 and 7), BCS (wk 3 and 7), parity (wk 3 and 7), and PTA for CIV (wk 3) and UHS. Cows that did not have a CL present had low BCS, primiparity, and that were in the quartile with greatest PTA for CIV, had a greater risk of abnormal UHS at wk 3 and 7 postpartum. We observed strong associations between CL status, UHS, BCS, metabolic status, parity, and individual genetic traits at wk 3 and 7 postpartum in seasonal-calving, pasture-based lactating dairy cows. Achieving target BCS and good metabolic status, and selecting cows based on PTA for CIV, are all expected to increase the likelihood of hastening the resumption of estrous cyclicity and enhancing uterine health during the postpartum period.
    • Milk adulteration with acidified rennet whey: a limitation for caseinomacropeptide detection by high-performance liquid chromatography

      de Pádua Alves, Érika; de Alcântara, Anna Laura D'Amico; Guimarães, Anselmo José Klaechim; de Santana, Elsa Helena Walter; Botaro, Bruno Garcia; Fagnani, Rafael; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação Nacional de Desenvolvimento do Ensino Superior Particular (Wiley, 2018-03-02)
      BACKGROUND High‐performance liquid chromatography (HPLC) is widely employed to determine the caseinomacropeptide (CMP) index and to detect milk tampering with rennet whey. Prior to HPLC analysis, CMP is subject to a trichloracetic acid isolation, causing further soluble proteins in the sample to precipitate. On this basis, we aimed to determine whether rennet whey acidification could adversely affect the HPLC sensitivity with respect to detecting this peptide. RESULTS As hypothesized, the CMP index from milk with added acidified rennet whey was, on average, half that quantified from milk with added rennet whey. Moreover, the quantum satis of acidified whey added to milk sufficient to demonstrate a HPLC CMP > 30 mg L–1 was 94% greater than that required for this threshold to be reached with rennet whey. CONCLUSION Milk tampering with acidified rennet whey may limit the analytical sensitivity of the reversed‐phase HPLC employed for the screening of CMP and, ultimately, disguise the fraudulent addition of whey to milk. © 2017 Society of Chemical Industry
    • Intra-Group Lethal Gang Aggression in Domestic Pigs (Sus scrofa domesticus)

      Camerlink, Irene; Chou, Jen-Yun; Turner, Simon P.; European Cooperation in Science and Technology; Scottish Government Strategic Research (MDPI AG, 2020-07-28)
      Intraspecific coalitional aggression is rare among all species, especially within stable social groups. We report here numerous cases of intraspecific lethal gang aggression within stable groups of domestic pigs. The objective was to describe this extreme aggression and to identify potential causes. Management data were collected from farms with (n = 23) and without (n = 19) gang aggression. From one farm, 91 victims were assessed for skin injuries and body condition score. Lethal gang aggression was significantly associated with deep straw bedding, which may be related to various other factors. Gang aggression tended to occur more in winter, and was unrelated to genetic line, breeding company, group size or feed type. It occurred equally in female-only and mixed sex groups (male-only groups were not represented), from around eight weeks of age. Injuries typically covered the whole body and were more severe on the front of the body. Victims who survived had a lower body condition score and fewer injuries than victims found dead. There are still many unknowns as to why this abnormal social behaviour occurs and it deserves further research attention, both for its applied relevance to animal welfare as for the evolutionary background of lethal gang aggression.
    • Effect of Exposure to Seminal Plasma Through Natural Mating in Cattle on Conceptus Length and Gene Expression

      Mateo-Otero, Yentel; Sánchez, José María; Recuero, Sandra; Bagés-Arnal, Sandra; McDonald, Michael; Kenny, David A.; Yeste, Marc; Lonergan, Pat; Fernandez-Fuertes, Beatriz; European Union; et al. (Frontiers Media SA, 2020-05-12)
      A growing body of evidence suggests that paternal factors have an impact on offspring development. These studies have been mainly carried out in mice, where seminal plasma (SP) has been shown to regulate endometrial gene expression and impact embryo development and subsequent offspring health. In cattle, infusion of SP into the uterus also induces changes in endometrial gene expression, however, evidence for an effect of SP on early embryo development is lacking. In addition, during natural mating, the bull ejaculates in the vagina; hence, it is not clear whether any SP reaches the uterus in this species. Thus, the aim of the present study was to determine whether SP exposure leads to improved early embryo survival and developmental rates in cattle. To this end, Day 7 in vitro produced blastocysts were transferred to heifers (12–15 per heifer) previously mated to vasectomized bulls (n = 13 heifers) or left unmated (n = 12 heifers; control). At Day 14, heifers were slaughtered, and conceptuses were recovered to assess size, morphology and expression of candidate genes involved in different developmental pathways. Additionally, CL volume at Day 7, and weight and volume of CL at Day 14 were recorded. No effect of SP on CL volume and weight not on conceptus recovery rate was observed. However, filamentous conceptuses recovered from SP-exposed heifers were longer in comparison to the control group and differed in expression of CALM1, CITED1, DLD, HNRNPDL, PTGS2, and TGFB3. In conclusion, data indicate that female exposure to SP during natural mating can affect conceptus development in cattle. This is probably achieved through modulation of the female reproductive environment at the time of mating. Keywords: seminal plasma, embryo development, corpus luteum
    • Genomic Regions Associated With Gestation Length Detected Using Whole-Genome Sequence Data Differ Between Dairy and Beef Cattle

      Purfield, Deirdre C.; Evans, Ross D.; Carthy, Tara; Berry, Donagh; European Union; Science Foundation Ireland; 727213; 14/IA/2576; 16/RC/3835 (Frontiers Media SA, 2019-11-05)
      While many association studies exist that have attempted to relate genomic markers to phenotypic performance in cattle, very few have considered gestation length as a phenotype, and of those that did, none used whole genome sequence data from multiple breeds. The objective of the present study was therefore to relate imputed whole genome sequence data to estimated breeding values for gestation length using 22,566 sires (representing 2,262,706 progeny) of multiple breeds [Angus (AA), Charolais (CH), Holstein-Friesian (HF), and Limousin (LM)]. The associations were undertaken within breed using linear mixed models that accounted for genomic relatedness among sires; a separate association analysis was undertaken with all breeds analysed together but with breed included as a fixed effect in the model. Furthermore, the genome was divided into 500 kb segments and whether or not segments harboured a single nucleotide polymorphism (SNP) with a P ≤ 1 × 10-4 common to different combinations of breeds was determined. Putative quantitative trait loci (QTL) regions associated with gestation length were detected in all breeds; significant associations with gestation length were only detected in the HF population and in the across-breed analysis of all 22,566 sires. Twenty-five SNPs were significantly associated (P ≤ 5 × 10-8) with gestation length in the HF population. Of the 25 significant SNPs, 18 were located within three QTLs on Bos taurus autosome number (BTA) 18, six were in two QTL on BTA19, and one was located within a QTL on BTA7. The strongest association was rs381577268, a downstream variant of ZNF613 located within a QTL spanning from 58.06 to 58.19 Mb on BTA18; it accounted for 1.37% of the genetic variance in gestation length. Overall there were 11 HF animals within the edited dataset that were homozygous for the T allele at rs381577268 and these had a 3.3 day longer (P < 0.0001) estimated breeding value (EBV) for gestation length than the heterozygous animals and a 4.7 day longer (P < 0.0001) EBV for gestation length than the homozygous CC animals. The majority of the 500 kb windows harboring a SNP with a P ≤ 1 × 10-4 were unique to a single breed and no window was shared among all four breeds for gestation length, suggesting any QTLs identified are breed-specific associations.