The use of electronic feeders in genetic improvement programs for swine

Abstract

Introduction Materials and Methods Results Discussion Implications Literature Cited CHAPTER 3. A MODEL TO ADJUST DAILY FEED INTAKE RECORDS FOR ERRORS IN DATA FROM ELECTRONIC SWINE FEEDERS Abstract Introduction Materials and Methods Results and Discussion Implications Literature Cited CHAPTER 4. A COMPARISON OF METHODS OF EDITING DATA FROM ELECTRONIC SWINE FEEDERS Abstract Introduction Materials and Methods Results and Discussion 80 Implications 90 Literature Cited CHAPTER 5. PERFORMANCE OF GROWING AND FINISHING BOARS AND GILTS FED USING ELECTRONIC VERSUS CONVENTIONAL FEEDERS Abstract Introduction 94 Materials and Methods 95 Results and Discussion 102 iv Implications 113 Literature Cited 114 CHAPTER 6. AN EVALUATION OF STRATEGIES FOR COLLECTING FEED INTAKE DATA USING ELECTRONIC FEEDERS Abstract Introduction Materials and Methods Results and Discussion Implications Literature Cited Figures CHAPTER 7. GENERAL CONCLUSIONS AND DISCUSSION Summary Literature Cited V ACKNOWLEDGEMENTS I would like to thank my major professor, Jack Dekkers, for his support and guidance. Jack went out of his way to provide professional, financial, and personal support. His input was invaluable to me. He was also a great mentor who I very much enjoyed working with. Thank you for everything Jack. I would also like to thank my committee for their help and input. I enjoyed working with each member of the committee. I would like to say a special thanks to Archie Clutter for his willingness to be on my committee and for traveling so far to do this and to Hal Stem for his help with logistic regression. The work and input from the employees at the Iowa State University swine breeding farm is greatly appreciated. Their help and input ensured the success of the research projects that were done. I really enjoyed working with them and would like to say a special thanks to

Deposition rates and accretion patterns of intramuscular fat, loin muscle area, and backfat of Duroc pigs sired by boars from two time periods1

“…A curvilinear pattern of ADG (Figure 1) was detected for pigs sired by boars from both time periods. Similar daily BW accretion rates were reported by Casey (2003) and Moeller et al (1998). As previously mentioned, results of this study for daily BW accretion are contrary to what would be expected from the genetic and phenotypic trends reported by Chen et al (2002) and Kaplon et al (1991) and may be explained by the unequal distribution of records among sexes in this study (Table 1).…”

Pig ear skin temperature and feed efficiency: Using the phase space to estimate thermoregulatory effort

“…Several indexes have been defined that combine the effect of temperature and relative humidity, adjusted for pigs of different live weights (Lucas et al, 2000). More studies are needed that measure individual temperature continuously and simultaneously in large groups, in combination with environmental and production data, such as the number of visits to feeding stations (Casey, 2003).…”

Quantitative genetic and statistical aspects of feed efficiency by analysis of the selection experiment for residual feed intake in Yorkshire pigs

“…In practice, longitudinal measurements of FI and BW data are often missing for substantial parts of growth period, including at the beginning and end. Major missing data occur when pigs are switched between electronic and commercial feeders to enlarge the test capacity because of the high expense of electronic feeders (Casey 2003;Eissen et al 1999;Schulze et al 2001;, and are caused by data errors and malfunction of electronic feeders (Casey et al 2005;Eissen et al 1998). Several studies have shown that missing FI information on different parts of the growth period has a limited effect on the accuracy of evaluating ADFI (Casey 2003;Eissen et al 1999).…”

“…Major missing data occur when pigs are switched between electronic and commercial feeders to enlarge the test capacity because of the high expense of electronic feeders (Casey 2003;Eissen et al 1999;Schulze et al 2001;, and are caused by data errors and malfunction of electronic feeders (Casey et al 2005;Eissen et al 1998). Several studies have shown that missing FI information on different parts of the growth period has a limited effect on the accuracy of evaluating ADFI (Casey 2003;Eissen et al 1999). However, there have been few studies on the effect of missing data on evaluation of feed intake and body weight curves, which requires sophisticated statistical models to inter-and extrapolate FI and BW curves for individual pigs.…”

“…The objective of this study was to evaluate direct and correlated responses to selection and to estimate genetic parameters based on the first 4 generations. Database and edit systems developed by Casey (2003) and Casey et al (2005) to handle the large amount of FI data from the FIRE ® feeders were used. The main steps in the edit procedures were to i) identify errors in each visit (a feeding event from a pig's entrance in the feeder to its exit) by 16 criteria (Casey et al, 2005) and count the number of errors of each type for each day (about 5% of visits contained at least 1 error); ii) compute error-free FI for each pig and day by summing feed consumed in visits without identified errors; iii) estimate the effect of error counts on error-free daily FI by fitting a linear mixed model to error-free daily FI observations with sex, generation by parity, and on-test weeks within generation by parity as fixed effects, variables created from the 16 error counts, body weight on that day and ADG as covariates, and pig as a random effect (Casey, 2003); iv) adjust error-free daily FI for each pig and day for feed consumed in error visits by adding estimates of covariates from step iii); v) estimate daily FI for each pig for days with missing FI data (no records or too many error visits) by fitting a quadratic regression of daily FI against on-test day for each pig; vi) compute ADFI for each pig by averaging daily FI during the test period.…”