I started writing about the case for smarter tech in cattle and sheep breeding programmes a while ago, and quickly realised there was more than would fit in a single blog post. In my previous post I described how technology can help us increase the pace of genetic progress, by:
- Measuring what we can’t easily see, including a range of important traits such as efficiency, emissions and disease resistance; and
- Reducing errors in recording and transcription.
There are two further areas where smart technology can and is helping:
Cut collection costs
How much does it cost to collect a phenotype for an animal?
A phenotype is the observable characteristics of an individual that result from both its genotype and the environment. When you collect sufficient phenotypic information about many individuals, you can adjust for environmental effects, and predict the genetic merit of that animals. Collecting phenotypes involves measuring details such as calving ease, weight gains, progeny survival and other characteristics of economic value to farmers and consumers.
Current technology for DNA analysis tell us more about the genetic similarity and differences between animals (their genetic relatedness) than their outright performance. There are relatively few simple gene interactions you can measure with a DNA test.
What DNA testing helps with is the challenge of recording which animals are related to each other, especially as pedigree recording gets harder with larger sets of animals. For the DNA test to be useful, it must be able to be statistically connected to animals that have had phenotypes measured.
As Dr Mike Coffey of SRUC, wrote in 2011, “In the age of the Genotype, Phenotype is king!”
Phenotyping will continue to be required. Livestock breeders will need a pool of accurate and comprehensive phenotype observations to support both new and existing breeding objectives, connected to the growing pool of genotyped animals.
Measuring animals is time-consuming and expensive: the tedious task of observing and measuring characteristics of animals, linking these to the correct animal records, and transcribing the observations into computer systems.
With the need for ongoing, and potentially more detailed phenotype recording, technology is our friend. From automated weighing and electronic identification to cameras, sensors, and deep learning, properly configured and managed technologies reduce the cost of data collection – especially for larger operations and at commercial scale.
We’ve helped several organisations organise and automate their phenotype recording, integrating electronic identification and a range of other technologies, and streaming that data back to central databases.
Better buying behaviour
What really drives buying decisions?
Ultimately livestock breeding is driven by demand. Livestock breeders focus their selection efforts on traits that drive economic performance such as:
- Birth weight and survival;
- Feed conversion efficiency and growth rates or milk production;
- Carcass characteristics or milk characteristics;
- Docility, resistance or resilience to disease;
and more. In the livestock industry, this is presented as the predicted benefit to future generations (typically termed EPDs or EBVs depending on your species, breed, and country). The EBVs or EPDs are combined into economic indexes where each is given a $ or £ weighting based on its impact in a typical farm system and usually delivered as tabular reports and graphs to buyers.
And what do buyers select on?
- In our experience, New Zealand dairy farmers make great use of the primary economic index – Breeding Worth or BW, combining that with decisions about breed and gestation length.
- In the sheep industry, breed and breeder decisions are often the primary decider. Once a breeder is selected, the numbers are used to buy the best animals one can afford.
- In the NZ and Australian beef industry, an expert tells me that for animals sold at auction, the closest purchase price correlation is with liveweight: in their opinion, animals are often valued on how big they are.
When sheep and beef farmers are presented with multiple EBVs and indexes, it can be overwhelming, and it is not surprising some farmers revert to assessing a ram visually, negating the value of genetics programmes.
I’m a great fan of Daniel Kahneman’s Thinking Fast, Thinking Slow, where he points out the challenge we have with quantifying difficult or unknown measures.
“If a satisfactory answer to a hard question is not found quickly, System 1 will find a related question that is easier and will answer it. I call the operation of answering one question in place of another substitution.” – Daniel Kahneman, Thinking Fast, Thinking Slow.
If understanding EBV’s and indexes seems difficult, you’re most likely to substitute an easier question – how good the ram looks or how knowledgeable the breeder seems – without even realising you have done so.
How can technology help here? We can use technology to make ourselves smarter – or the questions simpler. For instance, there’s potential to create a data-driven system that analyses your current farm system and recommends which economic index or other measure you should use when choosing animals. Or perhaps a tool that with a few simple selections works out how much you should spend on rams or bulls, finds those at a sale that meet your needs, and returns a ranked short list that you can use in your final decisions.
Smarter technology for livestock buyers is a key area where the industry can make real progress on the rate of genetic gain, and a strong understanding of how people make decisions will be critical to its success.