BIF 2018: Experiences with Implementation of Single-Step at American Angus, One Year In

Steve Miller


Angus Genetics Inc has four research scientists. They do single-step genomic evaluations for Angus, Canadian Angus, Charolais, Canadian Charolais, and Maine-Anjou.

Angus switched to single-step on July 7th, 2017. Miller feels like the switch to single-step was a monumental switch, should have made the Time Magazine year in review!

When breeders see bulls re-rank, they then understand was a correlation of 0.9 really means! On July 7th, Steve Miller talked to two breeders. On July 8th he was feel cool and casual like Ferris Buller. The next week, then the calls came.
"I've seen this before, in a couple of months it will all blow over" a friend told Miller. And that proved true.

The switch to single-step was kind of like the stages of grief with getting a flat tire.
Quiet phase: Listening, evaluating, asking yourself if you have a flat tire.
Expressive phase: Cussing, kicking dirt, frustrated.
Have to Move Forward phase: Fixing the tire and getting back on the road.

Communication was crucial, both before the changed occurred and phone calls after the change.

There is no way AGI would go back to the methods used before the switch to single-step. The new evaluation is that much better.

On July 7th, Angus changed to single-step. But they also made a lot of other changes to the evaluation. The changes were frequently due to the changes in the carcass model, by accounting for the selection bias in which animals had carcass and ultrasound data.

Single-step is now a brand.

Any genetic evaluaiton is only as good as the data behind it.

Genotyped database has doubled in 96 weeks. On June 16, 2018 they reached over 500,000 samples. They receive over 3,000 samples per week since November 2017.

So, after the storm of single-step passed, what questions now cause the phone to ring.
How can two flush mates have this different of EPDs?

The power in the pedigree. Creating the famous A matrix, the relationships between all of the animals in the evaluation. When we use pedigree data, we use the expected relationships between animals. But, with genomic data, we actually use the real relationships between the animals.

Recombination between paternal and maternal chromosomes cause unique chromosomes being inherited by the progeny of a bull.

We can look at 4 bulls.

Bull	Rank Whole Chromosome 6	Top Half of Chromosome	Bottom Half of Chromosome
Bull A	1	6	9
Bull B	51	7	167
Bull C	58	187	1
Bull D	183	171	184

Rank out of top 193 Sires for Birth Weight genomic value.

Look at variation in calf crop. One quarter of the variation comes from the dams. On quarter of the variation comes from the sires. One half of the variation comes from Mendelian sampling, the random shuffle of genes and chromosomes between generations.

As a breeder, we should love variation. Variation is what makes genetic progress possible.

Theory and what AGI is putting out the door matches. up.

Consider two full sib ET bulls. Pedigree says they should share 1/32 of their DNA with Shearbrooke Shoshone. But, what does the DNA say? Calf with higher birth weight EPD is 15% more related with ancestors is the pedigree with higher birth weight EPDs.

BIF 2018: How Does the Dairy Industry Handle Information?

Chuck Sattler
Vice President, Genetic Programs, Select Sires Inc.

Data is fuel for breed improvement programs. Data drives the machine. Noise in the data is like water in the fuel.

Data has value! However, individual records have very little data. We have to share data for it to achieve its value. "We are not good at investing in data. It's not sexy," Sattler said. We need to invest in data collection.

We need to share data thoughtfully. Have a written agreement and think strategically when sharing data.

Genomic evaluations are a big data success story! "We marvel at the technology that makes this all possible," he said. As much as it is a story about DNA technology, it is also a story about bring large amounts of data together. It is also a success of big data.

If we had to do it over again, dairy industry might re-think Dairy Recording Processing Centers. Dairy Recording Processing Centers control the data and sometimes the breeder's voice is not heard.

Stakeholders share data with Council Dairy Cattle Breeding, this is done guided by Material License Agreements. This shared data is used for national genetic evaluations. CDCB can share data but only with stakeholders permission.

Dairy used somatic cell score as an indirect measure of mastitis. In 2000, the genetic trend for mastitis reversed from a negative slope to a positive slope. They are now launching a direct mastitis genetic prediction that will help further reduce the incidence of mastitis.

Operations of CDCB funded by genomic evaluation user fees. Those that collaborate in providing data pay smaller genomic user fees.

Dairy industry is working on new ways of collecting data. They have become complacent and are looking for new opportunities.
One of the areas they need to improve is individual ID. Have to have unique IDs to make the data come together.
They are also working on how they use on-farm computer records in genetic evaluations. Zoetis lead the way in this by collecting data directly off the farm.

They also need to improve in harvesting and using data from automated data collection systems.

BIF 2018: Positioning for the Future of Beef Production, Bringing it All Together

John Pollak
Emeritus Professor, Cornell University

50 years is a milestone in time that provides an opportunity to reflect on accomplishments. It is also an opportunity to reset the clock.

The process for selection

• Establish a goal
• Create a breeding objective
• Collect data for traits defined in the objective
• Utilize the data to predict genetic merit
• (other steps I missed)

What was the goal to motivate selection we performed over the past 50 years?
Pollak could not identify a consistent goal over the last 50 years.

We can look at genetic trends and see that genetic change has been accomplished. Change has happened, but can we articulate the goal that lead to these changes?

What goal should motivate the selection we perform ove the next 50 years?
The temptation is to continue on perhaps the same path on before. Doing the same things better. We should avoid this.

If Pollak were to define the goal for the beef industry's breeding objective it would be increase the sustainability of beef production.

There has been inadequate consideration of reproduction, eating quality, healthfulness of beef, disease resistance, feed intake, lifetime performance, etc.

There are economically relevant traits (ERTs) and indicator traits for ERTs.

The beef industry is not one synchronized enterprise but rather is comprised of a multitude of independent businesses. In Pollak's view, this doesn't remove the value of a breeding objective, but perhaps different economic weights in different scenarios.

Genetics is driven by the seedstock segment. Can we provide incentives or subsidies to broaden the scope of a breeding objective.

The ability to collect data is going to improve over time with the develop of technology. One of the focuses of precision management is the recording of data. There are also valuable datasets, such as health data in feedlots, that are not feeding into national cattle evaluation.

Are there trends in the industry that change the value of traits that are measured?

Genomics is impacting genetic evaluations. Genomics can help us add new traits into the breeding objective.

How are we measuring success? We can look at genetic trends by monitoring change in EPDs over time. Are there alternatives? Alternative could include is the public happy with how beef is being raised. Example is green house gas emissions. Herd size has declined, production per animal has gone up, and thus green house gas emissions have gone down.

BIF 2018: Focus on Traits Not Considered

Dorian Garrick
Professor and Chief Scientist, Massey University

This is a one bull or two bull meeting. This means it cost about the profit from one or two bulls to pay for the attendence of this meeting. Beef producers need to leave this meeting with information and thoughts about how they will change and improve their operation.

We would like to think that you use index selection, but we know that you are probably using independent culling levels or phenotypic selection. However, we can look at genetic trends to see how traits have changed.

Weaning weight and yearling weights have increased over time. However, the rate at which these growth traits were changing slowed in 1990, when ultrasound carcass measures were introduced. So, Hereford breeders were still selecting for growth, but were also putting emphasis on other traits.

An average 2017-born daughter eats $57 more feed per year than an average 1980 daughter. This possibly outweighs improvement in terminal profitability. Mature weights are increasing by 10 pounds per year.

What do you measure?
Calving traits (calving ease scores and birth weight)
Early growth traits (weaning weight and yearling weight)
Reproduction
Ultrasound predictions of carcass traits
Mature Cow weights and condition scores
Actual Carcass characteristics
Actual feed intake
As we move down this list, we have a decreasing number of records.

We need to have a goal.
With that goal, what do you want to change? This is your breeding objective. A breeding objective is a list of traits (EPDs) and their economic value. Identifying the list of goals is easy. When we look at the economics value, we realize that some traits are indicator traits and not economically important.

You then need to look at the selection criteria. What traits are you measuring to produce EPDs?

You then need a breeding scheme, a dissemination system, a mating plan, and than an economic analysis. In this economic analysis we think about the overall benefits and the overall costs of this breeding program. The most expensive breeding program is likely not to be the most profitable breeding program.

So, what should our breeding objective be, what traits are we selecting?
reproduction and longevity
income over feed cost
animal welfare
environmental footprint

We have done a good job on income over feed costs (growth, marbling, calving ease, etc.) We do a very poor job on the rest of this list. The tangible traits like growth and calving ease smack us in the face when they are bad. The less tangible traits like reproduction or cow efficiency receive less intention.

Why aren't traits being adequately considered?
Not selecting on total merit indexes (e.g. for maternal systems)
Not measuring enough of the less tangible attributes
Cannot be measured

Value proposition
Among bull breeding sector
Too many animals being recorded
Not enough traits being recorded
Not being rewarded by bull buyers (price or demand for less tangible traits)
Breed association structure might be impeding innovation
-routine EPDs provided on all animals regardless of phenotypic measurement or not

How might more balanced selection occur?

• New technologies
• Subsidies by government (USDA grants are an indirect example of this)
• Local regulations
• Market requirements

New business structures to capture value (small collectives on like minded breeders)

Reproduction and Longevity
Inadequate use of puberty data
Inadequate use of post-partum anestrus interval

Feed Cost
Forage intake (behavioral aspects - walking distance - grazing time -sward selection)
Feedlot intake
Complex trait where animals can rank differently based on sex, diet, etc.

Animal welfare
Disease resistance

Environmental footprint
Urinary nitrogen excretion
Greenhouse gases
Soil Damage

New Zealand now has limits on amount of urinary nitrogen that can be excreted by a farm.
We can reduce the amount of greenhouse gases that an animal releases.

We want to move the cloud. We need to think about traits that are underrepresented (reproduction, animal welfare, environment).

We really need to improve the efficiency of beef production.
Selection is a proven and cost-effective mechanism for improvement. Needs to be based on whole-system indexes. The best way to do this would be to look at indexes and nothing else.

BIF 2018: Focus on Sustainability

Sara Place
Senior Director, Sustainable Beef Production Research, National Cattlemen's Beef Association

Does less beef mean less heat? Is meat, especially beef, not good for the planet?
We see the marketing of plant based burgers. We also see work for lab grown beef.

In the United States, agriculture and forestry are net carbon sinks (they capture carbon). In the US, beef is responsible for 2% of emissions. However, pasture is responsible for 3.9% of carbon capture. Agriculture is a net help in carbon emissions because of carbon capture! Further, carbon emissions are improving over time in agriculture.

However, the news media is not telling this story.

Emissions are not going down due to decreased consumption of beef. Emission are going down because of technology advancements. Productivity is a key driver in improving sustainability. We would need many more cattle, with much more emissions, if we produced cattle in 2017 they way we did in 1976.

If we continue on current trends, global cattle herd will increase by 7%. However, if rest of world matched rate of improvement we see in U.S. cattle herd, we would see a decrease by 27%! If rest of world matched U.S. productivity, world cattle herd would decrease by 53%!

What is the pounds of feed per pound of product for beef, chicken, and pork. Beef takes 13.8 pounds of feed per pound of product. Chicken is at 1.6 and pork at 2.5 pounds of feed. However, beef uses 1.6 pounds of human edible feed. Chicken uses 1.4 pound of human edible feed and pork uses 2.0 pounds of human edible.
However, what is the net protein contribution of these meats? In other words, how much protein does the animal eat and how much does the animal produce. Chicken and pork both eat more protein than they produce (0.85 for chicken, 0.70 for pork). Cattle contribute 2.53 pounds of protein for every pound they eat! Cattle take sunlight and turn it into protein.

Further, cattle can produce food (protein) on land that cannot be used in any other way to produce food.

A lot of feed used for beef production is used for maintenance of cattle (maintenance of cow, maintenance of growing steer).

How can we improve sustainability of beef production?
What can we take from our monogastric friends?
Focus on both components of feed to gain ratio. We are likely no where near biological efficiency of cattle. Focus on red meat yield, decrease whole industry maintenance energy costs including improved fertility rates, and avoiding extra fat.
How can we take further advantage of ruminant cattle?
Can we add more total gain on forage and reduce use of human edible grains?

Beef's sluggish response to sustainability concerns left open an opportunity for "alternative protein".

We need to tell the story of a self replicating technology that can take energy from the sun in the form of plants and turn it into protein. This technology is beef.

BIF 2018: Focus on Quality

Mark McCully
Vice President, Certified Angus Beef LLC

Within Certified Angus Beef they market over 1 billion pounds of beef and certify over 5 million cattle.

Quality can have a broad definition. For this talk, McCully will focus on Quality Grade (marbling).
Consumer satisfaction improves with high marbling. Beef with a Prime Quality Grade has a nearly 100% consumer satisfaction.
We have improved tenderness in the industry through multiple avenues (genetics, management, beef handling, beef cutting and processing). Because of improvement in tenderness, McCully feels marbling becomes even more important.

The percent of cattle that are grading Choice and Prime has increased over the past 10 years. For a long time we were increasing carcass weight with little change in quality grade. In the last ten years, we have seen a significant improvement in quality grades.

We have increased the amount of Prime beef pounds by 92.8%. We have increased Premium Choice by 72%. Select quality grades have decreased by 40%.
Percent of boxed beef sales have increased from 10% of sales to 20%.

The spread between Select and Choice is $10. The spread between Choice and Branded is $5.50. The spread between branded and CAB is $6. The spread between CAB and Prime is nearly $20. Even though there has been a 21% increase in tonnage of Choice and Prime, the spread between grades has stayed consistent. This likely reflects the strong demand for quality beef.

Yield Grade 4 and 5 discounts have decreased over time, allowing feeders to more aggressively chase Quality Grades.

Five Rivers looked at performance differences between low grading and high grading cattle. There is no difference in average daily gain, feed to gain ratio, and cost of gain. We can increase the quality of our product without sacrificing efficiency.

Is marbling a free trait? Are there unfavorable genetic correlations for other traits, including maternal traits? Right now the data says there are not unfavorable correlations and we can improve marbling without harming other traits.

Bigger supplies are allowing customer access. This is allowing retailers to promote quality beef in their advertisements. Further, ground beef is no longer quality grade neutral. Retailers are marking Prime Grade ground beef.

We have added value to the beef carcass. We have identified new ways to fabricate a carcass. More of the carcass is being marketed as a steak item, rather than a roast. This means there is increased value of marbling beyond the middle meats.

As we look at export opportunities, quality grades will be a driver of demand.

What are our industry targets?
What should they be?

	NBQA 2016 Targets	2018 Year to Date	Should be our goal?
% Prime	5	7.6	15
% Upper 2/3 Choice	35	23.3	45
% Low Choice	35	48.1	30
% Select	25	17.6	10

BIF 2018: Efficient Red Meat Production

Michael Genho
Elanco Animal Health

From the business dictionary, efficiency is "the comparison of what is actually produced or performed with what can be acheived with the same consumption of resources (money, time, labor, etc.)"

Production Metrics

• Feed Conversion Ratio
• Residual Feed Intake

What's missing?
Level of input and output.
What is the optimal within a given context?

These (FCR and RFI) fail to take economic situation into account.

Elanco has a calculator to measure the optimal days on feed.
In an example, feeding a set of cattle for 28 more days would have been more profitable because of increased margin profit from the gain of those cattle. This was true even though the feed conversion of this pen would have gotten worse over those 4 weeks.

Elanco is working to help customers move up the analytical ladder. Move from standard close outs to statistical analyses to predictive analyses.

Elanco looked at drivers of closeout profitability comparing lots to other lots in a region. The two leading drivers are in price and out price. These account for 50% of the profitability difference. The third highest was average feed conversion. It was even larger than ration price. Feed conversion is the largest production measure influencing profitability. Confounded with feed conversion is health.

Average feed conversion has stayed fairly flat over the last 17 years. However, in the last 17 years, days on feed has increased which can drive down feed conversion.
Even when breaking groups out by days of feed, feed conversion has gotten worse over the last 17 years. 

We can estimate empty body fat using back fat, carcass weight, quality grade and ribeye area. Empty body fat ranges from 24% to 34% on a lot basis. However, if we look within a lot, there is much variation within  lots of endpoint empty body fat.

So, what do conversions look like if we control for endpoint (empty body fat), sex and end weight?
We have cattle that are very good at feed conversion, quality grade and growth. Many of these lots of cattle are getting ahead of people. They are reaching their endpoint before managers realize.

Conclusions
Efficiency is best measured measured in context of what is optimal. Have to consider costs and output level.
Average feed conversion is the single largest performance driver of feedyard profit and loss (accounts for 10% of variation).
Feed conversion should be optimized within endpoint targets (empty body fat).