\n<\/p>\n
Structural soundness, temperament, maturity pattern and suitability for the environment still need to be assessed by looking at the animal. An EBV cannot tell you whether you like the bull standing in front of you or whether he is physically suitable for the job.<\/p>\n
However, visual appraisal also has limits.<\/p>\n
The bull\u2019s appearance reflects his genetics as well as his age, nutrition, preparation, health and management. Looking at him cannot fully separate those effects or reveal all the genetic differences that may appear in his progeny.<\/p>\n
Objective information helps answer a different question: what differences are these animals likely to pass on?<\/p>\n
The most useful approach is not the eye versus the figures. It is using the eye and the figures together, with each providing information the other cannot.<\/p>\n
Objective data can also be used poorly.<\/p>\n
An EBV is an estimate of genetic merit, not a guarantee of an individual result. Accuracy varies according to the amount and quality of information available. Contemporary groups, pedigree, genomic information and the recording of relevant traits all influence the strength of the estimate.<\/p>\n
Indexes also do not remove the need to look at the traits underneath them. Two bulls can achieve similar index values through very different combinations of fertility, growth, carcase and mature cow traits.<\/p>\n
That is why producers should not start and finish with the headline number.<\/p>\n
Before purchasing a bull, it is worth asking:<\/p>\n
What am I trying to change in my herd?<\/p>\n<\/li>\n
Which traits are limiting performance or profitability?<\/p>\n<\/li>\n
Does this index reflect my production system and market?<\/p>\n<\/li>\n
What genetic change is this bull likely to create in his progeny?<\/p>\n<\/li>\n
Are there traits I need to hold steady while improving others?<\/p>\n<\/li>\n
Is the bull physically suitable for the females, country and joining conditions?<\/p>\n<\/li>\n<\/ul>\n
The data should help answer those questions. It should not replace them.<\/p>\n
Comments questioning the economic benefit of a trait or index should not automatically be dismissed as opposition to science. Claims about profitability should be supported by assumptions that producers can see and test against their own circumstances.<\/p>\n
At the same time, personal experience with one bull, one herd or one season is not enough to disprove a genetic evaluation. Individual outcomes are affected by many things, including nutrition, joining management, disease, female fertility and seasonal conditions.<\/p>\n
Commercial experience is important, but it becomes much more useful when it is supported by records collected across enough animals and years to separate a repeatable result from a single experience.<\/p>\n
Both the model and the anecdote should be open to examination.<\/p>\n
A comments section is not an industry survey. A small number of regular contributors can create the impression that a view is more widespread than it actually is, while producers who agree\u2014or simply have no desire to argue online\u2014often remain silent.<\/p>\n
Even so, the comments are worth reading.<\/p>\n
They highlight where the explanation has been inadequate, where claims appear too broad and where producers see a gap between the promised outcome and their commercial experience.<\/p>\n
My main lesson is that producers do not need to accept breeding information without question. They do need enough understanding to question it well.<\/p>\n
That means knowing what the figures describe, what assumptions sit behind them, where their limitations lie and how they relate to the cattle, environment and markets of an individual business.<\/p>\n
Objective data is most valuable when it helps producers make better-informed decisions\u2014not when it is treated as a substitute for experience, observation or a clearly defined breeding objective.<\/p>\n<\/div>\n