Speidel Honored With Frank H. Baker
Memorial Scholarship
SACRAMENTO, CALIF. (April 30, 2009) – Scott Speidel, research associate in breeding and genetics at Colorado State University (CSU), Fort Collins, received the 2009 Frank H. Baker Memorial Scholarship Award during the 41st Beef Improvement Federation (BIF) Research Symposium and Annual Meeting April 29-May 2, 2009, in Sacramento, Calif.
Speidel accepted the award from Robert Williams, director of breed improvement and foreign marketing for the American-International Charolais Association, Kansas City, Mo.
The late Frank H. Baker played a key leadership role in helping establish the BIF in 1968. Each year since 1994, two deserving graduate students have been recognized for their winning essays.
A California native, Speidel holds a bachelor’s degree in animal science from California State University, Fresno, and a master’s degree from the University of Arizona, Tucson. He plans to complete his doctorate this fall at CSU.
An abstract from his award-winning essay follows.
Genetic Analysis of Longitudinal Data in Beef Cattle
Currently, many different data types are collected by beef cattle breed associations for the purpose of genetic evaluation. These data points are all biological characteristics of individual animals that can be measured multiple times over an animal’s lifetime. Some traits can only be measured once on an individual animal; whereas others, such as the body weight of an animal as it grows, can be measured a multitude of times. Data such as growth often have been referred to as “longitudinal” or “infinite-dimensional” since it is theoretically possible to observe the trait an infinite number of times over the lifespan of a given individual.
The analysis of such data is not without its challenges. As a result, many different methods, each an improvement over its predecessor, have been or are beginning to be implemented in the genetic analysis of beef cattle data. These methods of analysis range from the classic repeated measures to the more contemporary suite of random regressions that use covariance functions or even splines as their basis function.
Each of the approaches has both strengths and weaknesses when it comes to the analysis of longitudinal data. Therefore, the objective of this essay is to summarize past and current genetic evaluation technology for analyzing this type of data and to review some emerging technologies beginning to be implemented in current national cattle evaluation (NCE) schemes along with their potential implications to the beef industry.
Editor’s Note: This release is provided by the Beef Improvement Federation. The 41st BIF Research Symposium and Annual Meeting was hosted by the California Beef Cattle Improvement Association (CBCIA) and the California Cattlemen’s Association (CCA). For more information, contact Kelli Toledo at 559-972-8987 or visit www.calcattlemen.org/bif2009.html.
