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26 BC HOLSTEIN NEWS ❆ CHRISTMAS 2020
Highlights from the Lactanet Open Industry Session
Paul Meyer, Sales Manager, WestGen
Member of Genetic Evaluation Board, pmeyer@westgen.com
 For the first time the Open Industry Sessions, hosted formerly by CDN and now Lactanet, were conducted virtually, as so many things have been this year since March. These Open Industry Sessions are normally held in April (Guelph, ON) and October (St Hyacinthe, QC) in advance of the twice-yearly Genetic Evaluation Board meetings. Normally 30 to 40 people attend, of which half are students and researchers with the other half being local breeders and AI industry personnel with a keen interest in genetics. The virtual format (with simultaneous translation) relegated geography to play a much smaller role.
What is new for December Proofs?
New Fertility trait: Resistance to Fertility Disorders
This new trait includes incidences of Cystic Ovaries, Metritis and Retained Placenta and is expressed as an RBV (˜85 to 115). Higher proof numbers would be associated with more resistance and lower frequency of the disease.
Three New Type Traits:
Locomotion and two intermediate optimum traits; Front Leg View and Udder Floor
These are traits classifiers have been collecting data on, scoring cows on, for several years now. Locomotion is scored on cows that can be viewed on the walk. Front Leg View would deviate from the mean with “K” = Knock-Kneed and “B” = Bow-Legged, while Udder Floor with “T” = Tilt and “R” = Reverse Tilt. Locomotion is positively correlated with LPI and Pro$, Udder Floor and Front Legs View are not correlated with LPI and Pro$.
Proof expression for Stature will change
Stature will begin using alpha codes since this trait is now considered to have intermediate optimum with “S” = Short and “T” = Tall, and no more signed values with “+” or “‐”.
Interpretation of Type Proof data
A resource has been created and will be made available to aid in the interpretation of descriptive type trait genetic evaluations. Interpretations provide an expected daughter average for sires with EBV=0 and per 5‐point proof change based on the group of sires in the analysis. The plan is to update this document annually every April. New traits will be added as genetic evaluations become available.
Coming Soon...
Updating Breed Phenotypic Averages for Functional Traits
The displayed breed averages have not been updated in several years and are no longer representative of the breed today as change has been occurring in these traits. It’s now creating confusion about how to interpret sire proofs and their daughter average phenotype.
Observed phenotypic trends are a reflection of many factors including improvements in management and other industry trends. These are accounted for in genetic evaluations but not in the raw breed average values displayed on the various genetic evaluation details pages. Increased sexed semen usage is one factor which would clearly expect to impact breed averages and daughter performance statistics for calving ease and calf survival.
From the last five years of Holstein calving records, compared to a male, a female calf will on average have:
•6.2% more unassisted calvings; 4.1% fewer difficult calvings from a heifer
•3.0% more unassisted calvings; 1.5% fewer difficult calvings from a cow
•3.8% greater survival rate from a first calving heifer dam
• 1.9% greater survival rate from a cow dam
It was amazing to see nearly 200 attendees on the two separate days from a broad geographical footprint spanning the Atlantic to Vancouver Island to take in these presentations. This virtual format – which is almost certain to be repeated – is a real benefit, especially for western producers for whom travelling to take in such an eastern-based session would be impractical.
Here are some of the highlights of the presentations. The next OIS session will take place in early March – producers are welcome to take in some or all to stay abreast and contribute to the discussions on our Canadian genetic evaluations.
Interpreting Sire RBV and Expected Daughter Performance
Breed averages for sires with RBV=100 provide an average expectation across all herds for the average sire. Individual bulls can still differ widely from these averages and the performance in individual herds will also vary due to many management factors, mates, etc. This does not indicate how much performance could differ by selecting a higher or lower RBV sire. Expected differences in average daughter performance per change in sire RBV is a useful additional tool and may be more informative for proof interpretation in herds where averages may be less applicable.
Breed averages have been calculated for all breeds for the functional traits that display average performance and will be updated on the Lactanet “Genetics” website.
Moving to Composite Indexes for Major Scorecard Type Traits
Lactanet plans to move to composite indexes for the major scorecard type traits and overall conformation in April 2021 for Holstein, Jersey, and Ayrshire. These will replace the current Mammary System, Feet & Legs, Dairy Strength, Rump, and Conformation genetic evaluations.
Adjusting Indexes for Specific Traits
Several type traits in the Holstein breed have been identified by the industry as deviating too far from the ideals, most notably: Stature, Rear Legs Side View, and Teat Length. Selection for Mammary System, Feet & Legs and Rump indirectly results in selection for taller cows (due to positive genetic correlations). Including a (negative) weighting on Stature in the composite indexes for Mammary System, F&L and Rump to make the composites uncorrelated with this trait can eliminate this issue. Increasing the weighting of Rear Legs Side View within the F&L composite and Teat Length within Mammary System composite can help producers avoid sires that too often leave daughters with extremely straight legs or very short rear teats.
Comparisons of Data from On-Farm Sensors and Bulk Tank Analysis
Development of an electronic DHI service (eDHI) that involves data transferred electronically and no samples sent to a DHI lab is being studied. The recent study used eDHI Sensor (32 herds with Lely robots). A DHI web application was created where DHI staff entered the results from the last three milk pickups. Validation based upon normal pickup‐to‐pickup variation followed. Fat kg/hl, protein kg/hl, true protein and SCC were evaluated including conversion to fat % and crude protein %. Validated data was used to compute the 3‐day averages and was associated to the test day and used in the calculations of herd management averages for eDHI tank. Findings included a high relationship between bulk tank and sensor test day herd averages for fat and protein percent. Sensors were found on average to measure fat % slightly higher. Only a moderate relationship between bulk tank and sensor test day herd averages for SCC were found with sensor average
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