Spanish Dairy Cattle Research Articles

Characterisation of the rumen resistome in Spanish dairy cattle

BackgroundRumen microorganisms carry antimicrobial resistance genes which pose a threaten to animals and humans in a One Health context. In order to tackle the emergence of antimicrobial resistance it is vital to understand how they appear, their relationship with the host, how they behave as a whole in the ruminal ecosystem or how they spread to the environment or humans. We sequenced ruminal samples from 416 Holstein dairy cows in 14 Spanish farms using nanopore technology, to uncover the presence of resistance genes and their potential effect on human, animal and environmental health.ResultsWe found 998 antimicrobial resistance genes (ARGs) in the cow rumen and studied the 25 most prevalent genes in the 14 dairy cattle farms. The most abundant ARGs were related to the use of antibiotics to treat mastitis, metritis and lameness, the most common diseases in dairy cattle. The relative abundance (RA) of bacteriophages was positively correlated to the ARGs RA.The heritability of the RA of the more abundant ARGs ranged between 0.10 (mupA) and 0.49 (tetW), similar to the heritability of the RA of microbes that carried those ARGs. Even though these genes are carried by the microorganisms, the host is partially controlling their RA by having a more suitable rumen pH, folds, or other physiological traits that promote the growth of those microorganisms.ConclusionsWe were able to determine the most prevalent ARGs (macB, msbA, parY, rpoB2, tetQ and TaeA) in the ruminal bacteria ecosystem. The rumen is a reservoir of ARGs, and strategies to reduce the ARG load from livestock must be pursued.

Non-genetic effects affecting fertility traits in local Reggiana cattle

Submitted 2020-07-24 | Accepted 2020-09-22 | Available 2020-12-01 https://doi.org/10.15414/afz.2020.23.mi-fpap.338-346 The objectives of this study were to investigate non-genetic sources of variation of fertility in Reggiana cattle and identify the best model for future genetic analysis. Moreover, the variation of target fertility traits in the different parities and months of first service was evaluated. The investigated fertility traits were interval between calving and first insemination, interval between calving and conception, number of inseminations per conception, and calving interval. The dataset included 22,731 records of 10,502 cows, collected between 1986 and 2019. Four different models were tested: Model 1 included the fixed effects of herd-year-month of first service and parity; Model 2 separately accounted for herd-year and month of first service, in addition to parity; Model 1a and Model 2a were Model 1 and Model 2 with the addition of the effect of age at first insemination. Model 1 had an average coefficient of determination of 0.40 for the traits, and this value increased to 0.48 in Model 1a. Moving to Models 2 and 2a, the coefficient of determination dropped to average values of 0.21 and 0.27, respectively. Regarding the effect of month of first service, the best fertility performances were observed in March and April, whereas for parity effect the best performance was in third lactation. Model 1a presented the best R2 for all studied traits but data editing for age at first insemination was too strict. On the other hand, in Models 2 and 2a variance absorbed by fixed effects was low, and this resulted in potentially biased estimates. Model 1 was therefore the best trade off between data loss and predictivity. Keywords: fertility, local cattle, Reggiana, source of variation, modelling References Cavestany, D. et al. (1985). Effect of season and high environmental temperature on fertility of Holstein cattle. Journal of Dairy Science, 68(6), 1471–1478. https://doi.org/10.3168/jds.S0022-0302(85)80985-1 Forabosco, F., Mantovani, R. and Meneghini, B. (2011). European and Indigenous Cattle Breeds in Italy. Schiel & Denver Publishing Limited. Retrieved from https://books.google.it/books?id=BiA0YAAACAAJ Gandini, G. et al. (2007). Comparing local and commercial breeds on functional traits and profitability: The case of Reggiana dairy cattle. Journal of Dairy Science, 90(4), 2004–2011. https://doi.org/10.3168/jds.2006-204 Gonzalez-Recio, O. and Alenda, R. (2005). Genetic parameters for female fertility traits and a fertility index in Spanish dairy cattle. Journal of Dairy Science, 88(9), 3282–3289. https://doi.org/10.3168/jds.S0022-0302(05)73011-3 Groen, A. F. et al. (1997). Economic values in dairy cattle breeding, with special reference to functional traits. Report of an EAAP-working group. Livestock Production Science, 49(1), 1–21. https://doi.org/10.1016/S0301-6226(97)00041-9 R Core Team. (2017). R: A Language and Environment for Statistical Computing. Vienna, Austria. Schaeffer, L. R. (2018). Necessary changes to improve animal models. Journal of Animal Breeding and Genetics, 135(2), 124–131. https://doi.org/10.1111/jbg.12321 Tiezzi, F. et al. (2012). Genetic parameters for fertility of dairy heifers and cows at different parities and relationships with production traits in first lactation. Journal of Dairy Science, 95(12), 7355–7362. https://doi.org/10.3168/jds.2012-5775 Tiezzi, F. et al. (2011). Genetic analysis of fertility in the Italian Brown Swiss population using different models and trait definitions. Journal of Dairy Science, 94(12), 6162–6172. https://doi.org/10.3168/jds.2011-4661 Van Bebber, J. et al. (1997). Accounting for herd, year and season effects in genetic evaluations of dairy cattle: A review. Livestock Production Science, 51(1–3), 191–203. https://doi.org/10.1016/S0301-6226(97)00058-4

Carbon Footprint Assessment of Spanish Dairy Cattle Farms: Effectiveness of Dietary and Farm Management Practices as a Mitigation Strategy.

Simple SummaryLivestock production has been identified as an important source of greenhouse gas emissions. The current study was conducted to quantify the carbon footprint of Spanish dairy farms and to evaluate the potential of nutritional and management practices for mitigating methane emissions at farm level. The carbon footprint ranged from 0.67 to 0.98 kg CO2-eq/kg of energy corrected milk. Simulation scenarios showed that methane emissions and the carbon footprint of milk could be reduced more through management practices rather than dietary strategies. Modelling may provide policy makers, farmers and stakeholders valuable information for planning and developing strategies to reduce the carbon footprint associated with milk production. Greenhouse gas emissions and the carbon footprint (CF) were estimated in twelve Spanish dairy farms selected from three regions (Mediterranean, MED; Cantabric, CAN; and Central, CEN) using a partial life cycle assessment through the Integrated Farm System Model (IFSM). The functional unit was 1 kg of energy corrected milk (ECM). Methane emissions accounted for the largest contribution to the total greenhouse gas (GHG) emissions. The average CF (kg CO2-eq/kg of ECM) was 0.84, being the highest in MED (0.98), intermediate in CEN (0.84), and the lowest in CAN (0.67). Two extreme farms were selected for further simulations: one with the highest non-enteric methane (MED1), and another with the highest enteric methane (CAN2). Changes in management scenarios (increase milk production, change manure collection systems, change manure-type storage method, change bedding type and installation of an anaerobic digester) in MED1 were evaluated with the IFSM model. Changes in feeding strategies (reduce the forage: concentrate ratio, improve forage quality, use of ionophores) in CAN2 were evaluated with the Cornell Net Carbohydrate and Protein System model. Results indicate that changes in management (up to 27.5% reduction) were more efficient than changes in dietary practices (up to 3.5% reduction) in reducing the carbon footprint.

Analysis of foot and claw diseases/disorders in Czech Holstein cows

Received: 2018-05-07 | Accepted: 2018-05-14 | Available online: 2018-11-26 https://doi.org/10.15414/afz.2018.21.04.194-196 Foot and claw diseases/disorders from 24 545 lactations of 10 340 Holstein cows were recorded on 7 farms in the Czech Republic from 1999 to 2018. There were defined a three groups of foot and claw disorders/diseases: diseases of skin (SD), which cover digital, interdigital dermatitis and interdigital phlegmon; then disorders of the claw horn (CH) including ulcers, white line disease, horn fissures, together with double sole and overall claw diseases (OCD) ingluding all the recorded disorders. The OCD ratio observed during 1 th and 305 th days of lactation was 52.56% of all evaluated lactations. The observed ratio of SD and CH were 28.61% and 27.15%, respectively. A foot and claw disorders were defined as 0/1 occurrence per lactation, for the purposes of analyses,. Genetic parameters were estimated using by linear animal models for evaluated traits. Models included the random additive genetic effect of animal (A), the permanent environmental effect of cow (PE), fixed effects of parity, farm, year and season of calving, and age at calving as discreet variables in classes. The estimated heritability were 13.84%, 12.64% and 9.83%, 8.73% and 9.97%, for OCD, CH, SD, ulcers (U) and for dermatitis digitalis and interdigitalis (DD), respectively. Genetic correlation was 17.66% between SD and CH, whereas traits SD and DD equal high genetic similarity (98.4%). Also correlation between CH and U traits was high (92.62%). The presented results indicate to possibility of selection against foot and claw disorders/diseases for Czech Holstein population. The work was supported by the project QJ1510144 and the institutional support MZE-RO0718 of the Ministry of Agriculture of the Czech Republic. Keywords : cattle, foot and claw disorders, genetic parameters, health traits, udde References Buch, L. H., A. C. Sorensen, J. Lassen, P. Berg, J. A. Eriksson, J. H. Jakobsen, M. K. Sorensen (2011) Hygiene-related and feed-related hoof diseases show different patterns of genetic correlations to clinical mastitis and female fertility. J. Dairy Sci., 94, 1540-1551. Chapinal, N., A. Koeck, A. Sewalem, D. F. Kelton, S. Mason, G. Cramer,F. Miglior (2013) Genetic parameters for hoof lesions and their relationship with feet and leg traits in Canadian Holstein cows. J. Dairy Sci., 96, 2596-2604. Egger-Danner, C., O.K. Hansen, K. Stock, J.E. Pryce, J. Cole, N. Gengler, B. Heringstad (2013) Challenges and benefits of health data recording in the context of food chain quality, management and breeding. ICAR Technical Series. Groeneveld, E., M. Kovac, and N. Mielenz (2008) VCE User’s Guide and Reference Manual, Version 6.0. Krpalkova, L., M. Stipkova & M. Krejcova, 2016. Vliv zdravi paznehtů a urovně reprodukce na výkonnost a zisk stada dojnic. Nas chov, 76 (9), 58-63. Krupova, Z., Krupa, E., Michalickova, M., Wolfova, M., Kasarda, R. (2016) Economic values for health and feed efficiency traits of dual-purpose cattle in marginal areas. Journal of Dairy Science, ,. 99, s. 644-656. Madsen, P. , J. Jensen. 2010. DMU – a package for analysing multivariate mixed models. Version 6, release 5.0., Aarhus University, Foulum, Denmark. Perez-Cabal, M. A. ,N. Charfeddine, N. (2015) Models for genetic evaluations of claw health traits in Spanish dairy cattle. J. Dairy Sci., 98 (11), 8186-8194. Sogstad, A. M., T. Fjeldaas, O. Osteras, K. P. Forshell. (2005) Prevalence of claw lesions in Norwegian dairy cattle housed in tie stalls and free stalls. Prev. Vet. Med., 70, 191-209. van der Spek, D., J.A. van Arendonk, A.A. Vallee, H. Bovenhuis (2013) Genetic parameters for claw disorders and the effect of preselecting cows for trimming. J Dairy Sci., 96 (9), 6070-6078. van der Waaij, E. H., M. Holzhauer, E. Ellen, C. Kamphuis, G.de Jong. (2005) Genetic parameters for claw disorders in Dutch dairy cattle and correlations with conformation traits. J. Dairy Sci., 88, 3672-3678.

Descriptive study for culling and mortality in five high-producing Spanish dairy cattle farms (2006\u20132016)

BackgroundHigh turnover rate in dairy farms due to culling and mortality is associated with poor animal welfare, an increase in production costs and lower economic benefits for the dairy farm. Understanding cow elimination better would help to formulate specific prevention measures and improve the efficiency of milk production in dairy farms. Culling and mortality data from five standard high-producing dairy farms in Spain were analysed over a period of 11 years (2006–2016). Data were collected by the same veterinary team and using the same software system.ResultsSignificant between-herd differences in eliminated cows were observed for type of elimination (slaughter or death on the farm), age at elimination, cause of elimination, number of lactations and production parameters, such as total days in milk, life milk yield, litres per day of productive life and litres per day of life. Culling and mortality were higher during the hot season and for cows of second and third parities. Between-herd differences were observed. Reproductive disorders (30.2%) were the most frequent reason for elimination, with low production (23.4%) being the second most frequent reason. Accidents on the farm (7.7%) were a more frequent cause of elimination than metabolic diseases (7.2%), locomotor disorders (2.4%) and obstetrics (2.4%).ConclusionsVeterinary teams or farmers’ associations can use culling and mortality information for benchmarking cow farms if data collection and analysis is standardised for comparability. The analysis of culling and mortality information should help farmers to improve efficiency.

Effect of claw disorders on milk production, fertility, and longevity, and their economic impact in Spanish Holstein cows

The aims of this study were (1) to estimate the phenotypic association between different degrees of severity of claw disorders and production, fertility performance, and longevity in Spanish dairy cattle, and (2) to quantify its economic impact at the animal and herd level. In this study, claw data comprised 108,468 trimmings collected between 2012 and 2014 by 25 trimmers from 804 Holstein dairy herds. The claw disorders considered were the 3 most frequent disorders in Spanish dairy herds: dermatitis (DE), sole ulcer (SU), and white line disease (WL). The presence of SU or WL was associated with a significant decrease in milk production and was more important in cows in second or later lactations. A severe lesion of SU or WL lead to twice the milk losses associated with a mild lesion, ranging from 1.47 to 2.66kg/d of energy-corrected milk. The presence of SU or WL during the early lactation period was associated with more days open, fewer inseminations to get pregnant, and longer calving to first service interval (4.83 and 8.0 d longer due to mild and severe lesions of SU, respectively, and 4.94 and 17.43 d longer due to mild and severe lesions of WL, respectively). The occurrence of a case of SU or WL in first lactation had a significant effect on longevity, with severe lesions reducing up to 71 d of productive life. The cost of a mild lesion ranged from $53 to $232 per affected cow and year, whereas the cost of a severe lesion ranged from $402 to $622 per affected cow and year. The annual costs per cow for DE, SU, and WL were $10.80, $50.9, and $43.2, respectively. An average herd with 64 cows had an extra expenditure of $691/yr due to DE, $3,256/yr due to SU, and $2,765/year due to WL. Milk losses, longer calving intervals, and premature culling contributed to more than half of the costs. Therefore, providing this information to farmers could help decide on strategies to reduce the incidence of claw disorders on the farm.

Models for genetic evaluations of claw health traits in Spanish dairy cattle

Genetic parameters of 7 claw health traits from Spanish dairy cattle were estimated and the predictive ability of linear and ordinal threshold models were compared and assessed. This study included data on interdigital and digital dermatitis (DE), sole ulcer (SU), white line disease (WL), interdigital hyperplasia (IH), interdigital phlegmon (IP), and chronic laminitis (CL) collected between July 2012 and June 2013 from 834 dairy herds visited by 21 trained trimmers. An overall claw disorder (OCD) was also considered an indicator the absence or the presence of at least 1 of the 6 disorders. Claw health traits were scored as categorical traits with 3 degrees of severity (nonaffected, mild, and severe disorder). Genetic parameters were estimated by fitting both a standard linear model and an ordinal threshold animal model. Around 21% of cows had at least 1 claw disorder, and the most frequent disorders were SU, DE, WL, and CL. Heritabilities of claw disorders estimated with a linear model ranged from 0.01 (IP) to 0.05 (OCD), whereas estimates from the ordinal threshold models ranged from 0.06 to 0.39 (for IP and IH, respectively). Repeatabilities of claw health estimated with the linear model varied from 0.03 to 0.18 and estimates with the ordinal threshold model ranged from 0.33 to 0.69. The global trait OCD was correlated with all disorders, except for IH and IP when the linear model was fitted. Two different genetic backgrounds of claw disorders were found. Digital dermatitis showed positive correlations with IH and IP, whereas SU was positively correlated with WL and CL. The predictive ability of the models was assessed using mean squared error and Pearson correlation between the real observation and the corresponding prediction using cross-validation. Regardless of the claw health status, the linear model led to smaller mean squared error. However, differences in predictive ability were found when predicting nonaffected and affected animals. For most traits, healthy cows were better predicted using the threshold model, whereas the linear model fitted affected cows better. Correlations between the observed data and corresponding predictions support those results ranging from 0.01 to 0.34. Claw health traits showed enough genetic variance to be included in the selection goal for Spanish Holsteins to select animals with less susceptibility to claw health problems, and we suggest the linear model for implementing genetic evaluations of claw heath traits.

Comparison of methods for the implementation of genome-assisted evaluation of Spanish dairy cattle

The aim of this study was to evaluate methods for genomic evaluation of the Spanish Holstein population as an initial step toward the implementation of routine genomic evaluations. This study provides a description of the population structure of progeny tested bulls in Spain at the genomic level and compares different genomic evaluation methods with regard to accuracy and bias. Two Bayesian linear regression models, Bayes-A and Bayesian-LASSO (B-LASSO), as well as a machine learning algorithm, Random-Boosting (R-Boost), and BLUP using a realized genomic relationship matrix (G-BLUP), were compared. Five traits that are currently under selection in the Spanish Holstein population were used: milk yield, fat yield, protein yield, fat percentage, and udder depth. In total, genotypes from 1859 progeny tested bulls were used. The training sets were composed of bulls born before 2005; including 1601 bulls for production and 1574 bulls for type, whereas the testing sets contained 258 and 235 bulls born in 2005 or later for production and type, respectively. Deregressed proofs (DRP) from January 2009 Interbull (Uppsala, Sweden) evaluation were used as the dependent variables for bulls in the training sets, whereas DRP from the December 2011 DRPs Interbull evaluation were used to compare genomic predictions with progeny test results for bulls in the testing set. Genomic predictions were more accurate than traditional pedigree indices for predicting future progeny test results of young bulls. The gain in accuracy, due to inclusion of genomic data varied by trait and ranged from 0.04 to 0.42 Pearson correlation units. Results averaged across traits showed that B-LASSO had the highest accuracy with an advantage of 0.01, 0.03 and 0.03 points in Pearson correlation compared with R-Boost, Bayes-A, and G-BLUP, respectively. The B-LASSO predictions also showed the least bias (0.02, 0.03 and 0.10 SD units less than Bayes-A, R-Boost and G-BLUP, respectively) as measured by mean difference between genomic predictions and progeny test results. The R-Boosting algorithm provided genomic predictions with regression coefficients closer to unity, which is an alternative measure of bias, for 4 out of 5 traits and also resulted in mean squared errors estimates that were 2%, 10%, and 12% smaller than B-LASSO, Bayes-A, and G-BLUP, respectively. The observed prediction accuracy obtained with these methods was within the range of values expected for a population of similar size, suggesting that the prediction method and reference population described herein are appropriate for implementation of routine genome-assisted evaluations in Spanish dairy cattle. R-Boost is a competitive marker regression methodology in terms of predictive ability that can accommodate large data sets.

Inbreeding Depression on Female Fertility and Calving Ease in Spanish Dairy Cattle

Inbreeding depression on female fertility and calving ease in Spanish dairy cattle was studied by the traditional inbreeding coefficient (F) and an alternative measurement indicating the inbreeding rate (ΔF) for each animal. Data included records from 49,497 and 62,134 cows for fertility and calving ease, respectively. Both inbreeding measurements were included separately in the routine genetic evaluation models for number of insemination to conception (sequential threshold animal model) and calving ease (sire-maternal grandsire threshold model). The F was included in the model as a categorical effect, whereas ΔF was included as a linear covariate. Inbred cows showed impaired fertility and tended to have more difficult calvings than low or noninbred cows. Pregnancy rate decreased by 1.68% on average for cows with F from 6.25 to 12.5%. This amount of inbreeding, however, did not seem to increase dystocia incidence. Inbreeding depression was larger for F greater than 12.5%. Cows with F greater than 25% had lower pregnancy rate and higher dystocia rate (−6.37 and 1.67%, respectively) than low or noninbred cows. The ΔF had a significant effect on female fertility. A ΔF=0.01, corresponding to an inbreeding coefficient of 5.62% for the average equivalent generations in the data used (5.68), lowered pregnancy rate by 1.5%. However, the posterior estimate for the effect of ΔF on calving ease was not significantly different from zero. Although similar patterns were found with both F and ΔF, the latter detected a lowered pregnancy rate at an equivalent F, probably because it may consider the known depth of the pedigree. The inbreeding rate might be an alternative choice to measure inbreeding depression.

Mature body weight and profit selection in Spanish dairy cattle

Individual mature body weight (BW) and profit were obtained from type, milk yield, and economic data from 42,401 Spanish Holstein cows. The economic value of BW was estimated in order to consider it in the breeding goal and to compare the importance of BW to other traits related to profit. Also, relationships between predicted breeding values (BV) of BW with actual profit, functional herd life, and calving interval by regression analysis were estimated. Body weight obtained an economic value of − 0.84 euros per cow per year. Inclusion of BW in the breeding goal by considering stature in a new economic index was shown to have 10% importance in genetic merit of profit. Reliability increased from 0.33 to 0.47 with respect to the old index that only included production and longevity. A significant positive quadratic relationship between body weight BV and profit BV was found ( R 2 equals to 0.54) but heavier animals had shorter herd lives and longer calving intervals. Influence of Holstein genes and selection for production increased body weight BV and reached a plateau at year 1994, while profit BV trends were still rising. Results suggest that selection for actual profit should be made maintaining a constant BW.

Genetic Parameters for Female Fertility Traits and a Fertility Index in Spanish Dairy Cattle

Genetic correlations among female fertility traits (linear and binary) were estimated using 225,085 artificial insemination records from 120,713 lactations on 63,160 Holstein cows. Fertility traits were: calving interval, days open, a linear transformation of days open, days to first insemination, interval between first and last insemination, number of inseminations per service period, pregnancy within 56 and 90 d after first insemination, and success in first insemination. A bivariate animal model was implemented using Bayesian methods in the case of binary traits. Low heritabilities (0.02 to 0.06) were estimated for these fertility traits. Strong genetic correlations (0.89 to 0.99) were found among traits, except for days to first service, where the genetic correlation with other fertility traits ranged from −0.52 to −0.18 for binary traits, and from 0.50 to 0.82 for days to first service, calving interval, and days open. Four fertility indices were proposed utilizing information from insemination records; these indices combined one indicator of the beginning of the service period and one indicator of conception rate. Two additional indices used information from the milk-recording scheme, including calving interval and a linear transformation of days open. The fertility index composed of days to first service and pregnancy within 56 d achieved the highest genetic gain for reducing fertility cost, reducing days to first service, and reducing the number of inseminations per lactation ($8.60, −1.31 d, and −0.03 AI, respectively). This index achieved at least 15% higher genetic gain than obtained from indices with information from the milk recording scheme only (calving interval and days open).

Economic Value of Female Fertility and its Relationship with Profit in Spanish Dairy Cattle

A data file of 225,085 inseminations and 120,713 lactations from 63,160 Holstein cows was analyzed to obtain female fertility economic value according to number of inseminations per service period (INS). Fertility cost (FCOST) was included in a bioeconomic model, taking into account number of doses of semen, hormonal treatments, fertility culling cost, and delayed milk and calf sales. A profit equation was elaborated to estimate fertility cost and profit according to INS. Fertility in Spanish dairy cattle has worsened >10% over the last 14 yr. Days open have increased by about 15 d, and INS has increased from 1.7 to 2.0. A quadratic relationship was found between FCOST and INS. Similar profitability was estimated for cows who needed one or 2 INS, but when >3 INS were needed, profit decreased by >$205 (US dollars)/yr per cow. Cows that needed more INS had higher milk yield per lactation, but also had a higher culling risk and lower productive life and lifetime production, therefore, lower profit. Calving interval (CI) and INS economic values were, respectively, −$4.90 and −$67.32 (US dollars)/yr per cow and per one unit of change. The economic values of productive traits were $4.04, $1.02, and $1.19 (US dollars)/yr per cow and per one unit of change for kg protein, kg fat, and days in milk, respectively. A mature body weight economic value of −$0.67 (US dollars)/yr per cow and per kg was estimated. The relative importance of fertility traits with respect to protein was 64% for CI and 24% for INS, although the CI economic value is highly influenced by phenotypic standard deviation considered.