Www.optimir.eu An European project with the AWE asbl as Lead Partner WITH THE SUPPORT OF From January 2011 to September 2015.

Slides:



Advertisements
Similar presentations
The Dairy ICT Project Prof Chris Knight University of Copenhagen.
Advertisements

USE OF PREGNANCY SPECIFIC PROTEIN B TEST FOR PREGNANCY DIAGNOSIS AND ASSESMENT OF BULL FERTILITY G. Gábor, F. Tóth, N. Solymosi.
AfiWeigh ™ Automatic Cow Body Weighing System Oded Nir (Markusfeld) Consultant to SAE Afikim Dealers Meeting, Dead Sea, Israel, 2008.
Automated Mastitis Detection for Dairy Farms Amanda Sterrett & Jeffrey Bewley University of Kentucky Dairy Systems Management.
2004 H.D. Norman, A.H. Sanders,* R.H. Miller, and R.L. Powell Animal Improvement Programs Laboratory Agricutural Research Service, USDA, Beltsville, MD.
On Line Milk Analysis AfiLab. AfiLab Applications The development of AfiLab is an on going effort –Unique technology –Software applications –For Management.
Management and Supplementation Strategies to Improve Reproduction of Beef Cattle on Fescue John B. Hall Extension Beef Specialist Virginia Tech.
Fokkerij in genomics tijdperk Johan van Arendonk Animal Breeding and Genomics Centre Wageningen University.
Application of Technology Platforms to Horse Breeding
Selecting and Judging Dairy Cattle
J. B. Cole 1, P. D. Miller 2, and H. D. Norman 1 1 Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD 2 Department.
Use of cow culling to help meet compliance for somatic cell standards H. D. Norman and J. R. Wright * Animal Improvement Programs Laboratory, Agricultural.
But who will be the next GREAT one?. USA Bull Proofs * Bulls are ranked based upon their DAUGHTER’S (progeny) production and physical characteristics.
2007 Jana L. Hutchison Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD , USA
Walloon Agricultural Research Center Walloon Agricultural Research Center, Quality Department Chaussée de Namur, 24 – 5030 GEMBLOUX - Tél :++ 32 (0) 81.
December 2014 Proof Changes
Capitalizing on mid-infrared to improve nutritional and environmental quality of milk H. Soyeurt *,§, F. Dehareng **, N. Gengler *, and P. Dardenne **
George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD National Association.
John B. Cole Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD Health and.
Nutrition and Feeds for Developing Heifers and Bulls Developing heifers Developing heifers –Goal: Feeding heifers for constant wt. gain following weaning.
Genetic Evaluation and Index Changes. HA-USA Fertility Index Fertility Index =.64 x PTA Daughter Pregnancy Rate (DPR).18 x PTA Cow Conception Rate (CCR).18.
Innovation on Milk Recording New Management Indicators Decision Making and Profitability Pregnancy, Embryo loss, Ketosis, Acidosis, Methane, Energy Balance...
1. Deliberate on the draft research framework and suggest improvements Resource for implementation Attention at regional level for cross- cutting issue.
Norway (1) 2005 Status of Dairy Cattle Breeding in the United States Dr. H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service,
2003 G.R. Wiggans,* P.M. VanRaden, and J.L. Edwards Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD
AFGC Convention 2004 (1) 2004 Possibilities for Improving Dairy Cattle Performance Dr. H. Duane Norman Animal Improvement Programs Laboratory Agricultural.
R. L. Powell Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Historical.
Forage Analysis For Beef Cattle: Why, How, and So What Dr. Matt Hersom Dept. of Animal Sciences.
2007 J.B. Cole Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Overview.
2008 ADSA-ASAS Joint Annual Meeting Indianapolis, July 7-11 Genetic Parameters of Saturated and Monounsaturated Fatty Acids Estimated by Test-Day Model.
36th ICAR Session and Interbull Meeting Niagara Falls, June 2008 Potential Estimation of Minerals Content in Cow Milk Using Mid- Infrared Spectrometry.
2001 NAAB DSEC, April 2002 (1) Revision and Use of Termination Codes PAUL VANRADEN Animal Improvement Programs Laboratory Agricultural Research Service,
John B. Cole Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD Best prediction.
Rick Kohn Louise Lawrence A program to improve dairy herd nutrition using milk urea nitrogen Department of Agriculture.
J. B. Cole 1,*, P. M. VanRaden 1, and C. M. B. Dematawewa 2 1 Animal Improvement Programs Laboratory, Agricultural Research Service, USDA, Beltsville,
H.D. Norman, J.R. Wright, and R.H. Miller Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD, USA
WiggansARS Big Data Computing Workshop (1) 2013 George R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville,
Genetic and environmental factors that affect gestation length H. D. Norman, J. R. Wright, M. T. Kuhn, S. M. Hubbard,* and J. B. Cole Animal Improvement.
2007 John B. Cole USDA Animal Improvement Programs Laboratory Beltsville, MD, USA 2008 Data Collection Ratings and Best Prediction.
Multi-trait, multi-breed conception rate evaluations P. M. VanRaden 1, J. R. Wright 1 *, C. Sun 2, J. L. Hutchison 1 and M. E. Tooker 1 1 Animal Genomics.
 Milk fat composition varies with the season (summer vs. winter) but also with the milking time (AM vs. PM).  These observations could allow the diversification.
CHO Metabolism.
2006 GEORGE R. WIGGANS Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, Maryland ,
Project title: Health Impact assessment (HIA) of air-pollution- abatement action plans Koldo Cambra. Department of Health. Basque Government. Spain.
Characteristics of milk ELISA results for Johne’s disease in US dairy cows Byrem, T. M. 1 *, H. D. Norman 2 and J. R. Wright 2 1 Antel BioSystems, Lansing,
Lactation Number Effects on the Genetic Variability of the Stearoyl Coenzyme-A Desaturase 9 Activity Estimated by Test-Day Model V. M.-R. Arnould 1, N.
CRI – Spanish update (1) 2010 Status of Dairy Cattle Breeding in the United States Dr. H. Duane Norman Animal Improvement Programs Laboratory Agricultural.
John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD What direction should.
Walloon Agricultural Research Center Genetic Variability of Lactoferrin Content Predicted by MIR Spectrometry : MIR Spectrometry + Quantitative Models.
Dairy Cattle Production (95314)
Florian Grandl, Marisa Furger, Angela Schwarm, Michael Kreuzer
Micro Nutrition Role in delivering profitable outcomes for dairy farmers Peter Robson DSM Ruminant Team APAC.
3. Milk production and composition
Innovative Analytical Solutions for the Dairy Industry
The Dairy Research Foundation 2017 Symposium Ian Halliday July 2017
Individual fatty acid measurements in milk from Danish dairy cows
Heard-health-parameters Dairy Herds Calculating Workability
Lifetime Performance of Dairy Cows in Northern Ireland
The influence of nutrition and metabolic diseases on milk composition
شیر خشک Formula.
Drought and fodder crisis What cows should I cull?
Micro Nutrition Role in delivering profitable outcomes for dairy farmers Peter Robson DSM Ruminant Team APAC.
Predict and Explain Task – Absorption Spectra
Denmark – DHI technical update
Where AIPL Fits In Agricultural Research Service (ARS) is the main research arm of USDA (8,000 employees with 2,000 scientists at >100 locations) Beltsville.
Effectiveness of genetic evaluations in predicting daughter performance in individual herds H. D. Norman 1, J. R. Wright 1*, C. D. Dechow 2 and R. C.
Jan – Dec RuminOmics Connecting the animal genome, the intestinal microbiome and nutrition to enhance the efficiency of ruminant.
SusCatt Increasing productivity, resource efficiency and product quality to increase the economic competitiveness of forage and grazing based cattle.
California Dairy Overview
Automating Health & Reproductive Management of Cattle
Presentation transcript:

An European project with the AWE asbl as Lead Partner WITH THE SUPPORT OF From January 2011 to September 2015

11 milk recording organizations EUROPEAN PARTNERSHIP 1 laboratory 6 research centres and universities

Milk recordingMid Infrared spectrometry (MIR) MIR spectrum for each cow Milk composition Fat Protein Cells... Use of milk recording data for an acute management of herd and cows © Bentley

How this MIR spectrum could be used to improve the sustainability of the milk production ? Use of milk recording data for an acute management of herd and cows MIR spectrum for each cow

Use of milk recording data for an acute management of herd and cows MIR spectrumCow’s state The MIR spectrum got by analysing a milk sample of one cow may provide information on its fertility,its feeding,its health, or its environmental impact

Use of milk recording data for an acute management of herd and cows MIR spectrum Pregnant? Ready for IA?Energy balance? Methane? Acidosis?Mastitis? Utilization of the protein? Cow’s state

Pooling of the data of the Milk Recording Organizations: Data of every records, including the MIR spectra Related data on fertility, health, feeding and environment STEP 1 COMMON TRANSNATIONAL DATABASE COMMON TRANSNATIONAL DATABASE

COMMON TRANSNATIONAL DATABASE STEP 1

Development of predictive tools by the Research Centres and Universities: To find in the spectrum and within the other milk recording data some indicators of the cows’ state (fertility, health, feeding and environmental impact) STEP 2 COMMON TRANSNATIONAL DATABASE PREDICTIVE TOOLS OF THE COWS’ STATE

STEP 2 PREDICTIVE TOOLS OF COWS’ STATE Pregnancy diagnosis Ability to conceive Energy balance calculator Protein utilization calculator Sub-acute ruminal acidosis sensor Mastitis sensor Methane emissions Etc. Implementation in the form of Web application