· Selection Intensity = percent of animals used for breeding purposes compared to the entire population · Selection Accuracy = level of accuracy in the genetic prediction used for genetic selection · Variation = diversity in genetic traits and lines in the population · Generation Interval = time between the birth of parents and the birth of their offspring Set your own Genetic Strategy 1. Set Goals – Establish what you want your herd to look like in 5-10 years 2. Calculate Replacement Needs – Determine the number of replacements desired based on the herd’s future growth plans 3. Rank Females – Genomic Testing, WMS Parent Average, Performance 4. Choose Sires – select the best bulls to use on each group of females 5. Implement the Strategy – mate sires to individual females using WMS or match groups of sires to groups of females using StrataGEN 6. Monitor Results – carefully track fertility, genetic progress, and performance to ensure compliance with Genetic Strategy goals Utilise a group of genomic sires as part of your genetic strategy. By making use of the best genomic-proven sires available, you decrease the generation interval as compared to waiting to use daughter-proven sires. You also step up the genetic selection intensity for the sires used on your farm. Daughters from genomic sires perform very close to what was expected from their sire’s initial genomic proof. Farmers who use US genetics accept the value of genomic bulls as a matter of fact and use them with confidence. This is due to the higher reliability resulting from improved genomic evaluations and accuracy in predictions. Reliability begins with having a large reference population and accurate phenotypic data from which to make the genomic predictions. Without this, genomic predictions will have low accuracy levels and greater variation will be seen in the final result. The large base population in the USA and more than 6 million genotyped animals provides a very high level of accuracy in genomic prediction. The number of farms using genomic testing as a genetic selection and management tool is on the rise globally, which further indicates farmer confidence in this technology.