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GenTORE
  • Home
  • Project
    • Work Packages
    • Impact
    • Partners
    • Intranet
  • Results
    • DELIVERABLES
    • Policy Brief
    • Practice abstracts
    • Scientific papers
    • Conference communications
    • DATASETS & SOFTWARE
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      • Genomic management
      • Mitigation
      • Improved phenotyping
      • Environment
  • Stakeholders
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​

​RESULTS

GenTORE Glossary
Check our glossary defining relevant terms within the project!

Policy Brief

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Policy Brief - Precision Animal Breeding is the solution for future of livestock production and the world

Practice Abstracts

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Using scenarios to test innovative tools - SRUC
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Factors contributing to efficiency in Spanish suckler cow systems - CITA
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Understanding the challenges in European cattle production systems - FiBL and SRUC
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European dairy farms are efficient, but are they resilient? - FiBL
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The power of joining forces for better dissemination - EFFAB and EAAP
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A practical definition & tool for resilience for dairy cows - WUR
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Sensor systems availability in dairy farms - UNIPD
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C.O.W (Cow’s Own Worth) Tool - Teagasc

Articles / Papers

  • Christian Grovermann, Sylvain Quiédeville, Adrian Muller, Florian Leiber, Matthias Stolze, Simon Moakes, Does organic certification make economic sense for dairy farmers in Europe?–A latent class counterfactual analysis, Agricultural Economics, July 2021
  • Emre Karaman, Guosheng Su, Iola Croue & Mogens S. Lund, Genomic prediction using a reference population of multiple pure breeds and admixed individuals, Genetics Selection Evolution​, May 2021
  • L.Puillet, V. Ducrocq, N.C.Friggens, P.R.Amer, Exploring underlying drivers of genotype by environment interactions in feed efficiency traits for dairy cattle with a mechanistic model involving energy acquisition and allocation​, Journal of Dairy Science, May 2021
  • M. Poppe, H.A. Mulder, R.F. Veerkamp, Validation of resilience indicators by estimating genetic correlations among daughter groups and with yield responses to a heat wave and disturbances at herd level, Journal of Dairy Science, April 2021
  • M.Poppe, G.Bonekamp, M.L.van Pelt, H.A.Mulder, Genetic analysis of resilience indicators based on milk yield records in different lactations and at different lactation stages, Journal of Dairy Science, February 2021​
  • F.L. Dunne, R.D. Evans, M.M. Kelleher, S.W. Walsh and D.P. Berry, Formulation of a decision support tool incorporating both genetic and non-genetic effects to rank young growing cattle on expected market value​, Animal, February 2021
  • P. Martin, V. Ducrocq, D.G.M. Gordo, N.C. Friggens, A new method to estimate residual feed intake in dairy cattle using time series data, Animal, February 2021
  •  M. Poppe, H. A. Mulder, C. Kamphuis, R.F. Veerkamp, ​Between-herd variation in resilience and relations to herd performance, Journal of Dairy Science. 104-1, January 2021
  • Muñoz-Ulecia, E., Bernués, A., Casasús, I., Lobón, S., Olaizola, A., Martín-Collado, D., Drivers of change in mountain agriculture: A thirty-year analysis of trajectories of evolution of cattle farming systems in the Spanish Pyrenees, Agricultural Systems Volume 186, January 2021, 10298.
  • Hong A., Spiekers H., Windisch W., Götz K.-U., Ettle T., Influence of dietary energy concentration and body weight at slaughter on carcass tissue composition and beef cuts of modern type Fleckvieh (German Simmental) bulls, Meat Science, November 2020
  • E.M.M. van der Heidea, C. Kamphuis, R. F. Veerkamp, I. N. Athanasiadis, G. Azzopardi, M. L. van Pelt, B. J. Ducro, Improving predictive performance on survival in dairy cattle using an ensemble learning approach, Computers and Electronics in Agriculture, Volume 177, October 2020, 105675.
  • ​F.L. Dunne, D. P. Berry, M.M. Kelleher, R. D. Evans, S.W. Walsh and P. R. Amer (2020) An index framework founded on the future profit potential of female beef cattle to aid the identification of  candidates for culling, Journal of Animal Science, skaa334.
  • I. Lora, F. Gottardo, B. Contiero, A. Zidi, L. Magrin, M. Cassandro, and G. Cozzi (2020) A survey on sensor systems used in Italian dairy farms and comparison between performances of similar herds equipped or not equipped with sensors, Journal of Dairy Science, Vol. 103 No. 11.
  • Honig A., Spiekers H., Windisch W., Götz K.-U., Ettle T. (2020) Influence of dietary energy concentration and body weight at slaughter on carcass tissue composition and beef cuts of modern type Fleckvieh bulls, Meat Science, Volume 169 108209.
  • Deirdre C Purfield, Ross D Evans, Donagh P Berry (2020) Breed- and trait-specific associations define the genetic architecture of calving performance traits in cattle, Journal of Animal Science, Volume 98, Issue 5.
  • D.P. Berry, S.C. Ring (2020) Observed progeny performance validates the benefit of mating genetically elite beef sires to dairy females, Journal of Dairy Science, Volume103, Issue 3.​
  • M. Poppe, R.F. Veerkamp, M.L. van Pelt, H.A. Mulder (2020) ​Exploration of variance, autocorrelation, and skewness of deviations from lactation curves as resilience indicators for breeding, Journal of Dairy Science, Vol. 103, Issue 2, P. 1667-1684.
  • Newton, J., & Berry, D. (2020). On-farm net benefit of genotyping candidate female replacement cattle and sheep. Animal, 1-11.
  • I. Adriaens, N.C. Friggens, W. Ouweltjes, H. Scott, B. Aernouts, J. Statham (2020) Productive lifespan and resilience rank can be predicted from on-farm first parity sensor time series but not using a common equation across farms, Journal of Dairy Science, August 2020
  • J.B. Clasen, W.F. Fikse, M. Kargo, L. Rydhmer, E. Strandberg, S.Østergaard (2019) Economic consequences of dairy crossbreeding in conventional and organic herds in Sweden, Journal of Dairy Science, Vol. 103, Issue 1, P. 514-528.
  • Philippe FAVERDIN, Jaap VAN MILGEN, Intégrer les changements d’échelle pour améliorer l’efficience des productions animales et réduire les rejets​, INRA Productions Animales, Vol. 32 No. 2, Juni 2019​
  • ​Purfield, D.C., Evans, R.D. & Berry, D.P. (2019) Reaffirmation of known major genes and the identification of novel candidate genes associated with carcass-related metrics based on whole genome sequence within a large multi-breed cattle population. BMC Genomics 20, 720.
  • Purfield, D.C., Evans, R.D., Carthy, TR and Berry, D.P. (2019) Genomic Regions Associated With Gestation Length Detected Using Whole-Genome Sequence Data Differ Between Dairy and Beef Cattle. Front. Genet. 10:1068.​

Presentations / Abstracts

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"Decision support tools from the cradle to the grave", Teagasc and ICBF, EAAP 2020, Oral presentation, December 2020
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"Increasing duration of feed restriction", INRAE and VetAgro Sup, EAAP 2020, Oral presentation, December 2020
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"Between-herd variation in cow resilience" - WUR, EAAP 2020, Oral presentation, December 2020
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"Genetic change of resilience within and between lactations in dairy cattle" - WUR, EAAP 2020, Oral presentation, December 2020

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WUR, WIAS Annual Conference, Oral Presentation, Feb 2020
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LfL, VDLUFA Congress, Abstract, Sept 2019
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WUR, 2nd International Precision Dairy Farming Conference, Oral Presentation, June 2019
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CITA, ADSA 2020, Presentation, "Milk fatty acid profiles of beef cows in response to a short feed restriction during lactation", June 2020

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LfL, ISRP, Abstract, Sep 2019
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UdL-CITA, EAAP August 2019, Poster Presentation
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Noldus, EAAP 2019, Oral Presentation, August 2019
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WUR, EC-PLF 2019, Oral Presentation, August 2019

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FiBL, EAAP 2019, IMAGE-CDB Session, Oral Presentation, August 2019
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CITA, EAAP 2019, Oral Presentation, August 2019
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EAAP 2019, CITA, Poster Presentation, August 2019
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INRAE & RAFT, EAAP 2018

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WUR & Viking Genetics, EAAP 2018
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WUR, EAAP 2018
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CITA, EAAP 2018
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UNIPD, EAAP 2018
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GenTORE is a Horizon 2020 project running from 1 June 2017 to 31 May 2022. This research received funding from the European Union's H2020 Research and Innovation Program under agreement No. 727213. Privacy Policy
  • Home
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