In the real world it is highly unlikely that meat goat producers would select for a single production trait. It is more common for a number of traits to be involved in a selection plan. This is known as multiple-trait selection. The objective is to improve aggregate breeding value or net merit — breeding value for a combination of traits, within a population. The definition of aggregate breeding value suggest determining which traits are worthy of selection, but also to assign some relative value to each one. To define aggregate breeding value or net merit is to define the “best” animal, to this environment.

In many cases multiple trait selection is as much an art as it is a science. There are no hard-and-fast rules. There may be an intuitive element to application. Animal breeding purists often suggest there are three distinct approaches:

• Tandem selection. This is simply selection for one trait at a time, and then another one of those identified as being important. A very simple approach, but not particularly efficient in terms of making genetic progress. Selection for one particular trait is applied for several years until a certain level of performance is achieved; then selection is focused on another trait for a number of years. In the presence of an unfavorable correlation between two traits, a breeder might loose most of the progress made in trait #1 while improving trait #2.
• Independent culling levels or independent selection standards. Under this approach breeders set minimum standards for traits involved in multiple-trait selection. Animals being reviewed for selection or culling (not selected) using this approach are culled or are not selected if they fail to meet any one standard regardless if they have outstanding merit in any one of the other standards. A relatively simple approach, but will often result in the loss of some otherwise pretty good potential parents. Setting these standards allows the goat breeder to select simultaneously for more than one trait by applying rather simple rules. They are most appropriate when there is a clear distinction between what is acceptable and what is not. Independent culling levels are also convenient when selection occurs at different stages of an animal’s life. Kids whose weaning weights are too light are rejected at weaning. A second round of selection occurs at six to nine months of age, when decisions regarding replacement stock are being made. This approach allows the obvious choices to be made early in life and reduces the expense of maintenance. The practical use of independently culling levels takes an intuitive rather than a mathematical precise approach when setting levels or standards. If they are strictly applied, they may exclude some potentially useful animals. On the other hand, as one breeder stated, “I may loose some good ones along the way, but I will get all the bad ones”.
• Selection index. The selection index incorporates each trait of some economic importance, and weights each one according to economic value. Essentially the same methodology is used here as was used in the genetic prediction application for a single trait. The index as used here is a prediction of aggregate breeding value. The equation for an index looks something like this:

An example might be an index based on a weight of .75 for each unit of average daily gain (e.g., 0.10 pound), and a weight of .50 for each unit of estimated ribeye area (e.g., 0.1 square inch) above or below the contemporary group mean. In other words, one-tenth of a pound increase in average daily gain is worth somewhat more that a one-tenth square inch increase in ribeye area.

The practical benefit of selection indexes is that they help define breeding objectives rather precisely. The chief problem is that economic weights are difficult to determine. Economic weights require careful analysis of costs and returns and are not uniform from farm to farm. These weights must be determined locally and with the economic considerations that apply to each farm or ranch. They will also change from time to time. Selecting animals on the basis of a single index value seems appealingly simple. However getting to the point of the selection decision requires much effort and a knowledge of breeding objectives.

There is no rule that suggests the breeder must use only one or the other of these selection methods. The methods can be combined as seen fit. Computer simulation models of the future may provide meat goat breeders an opportunity to test several selection scenarios, and then make the decision of which way to go.

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