Data from the 2001-2002 Texas A&M University Ranch to Rail Program-South were used to determine factors that influence cattle feedlot performance and profitability. Steers (n=860) were classified according to sire (SBIO) and dam (DBIO) biological groups, kill groups (KILL), and entry month (ENTRYMON). Biological groups were determined by predominant genetic make up of the sire or dam. Traits evaluated included net income (NI), feedlot average daily gain (ADG), slaughter weight (OUTWT), carcass weight (CW), fat thickness (FT), longissimus muscle area (LMA), marbling score (MS), yield grade, (YG), medicine costs (TOTMED), and carcass value (CVL). Analyses of covariance were performed to determine differences between SBIO and DBIO, KILL, and ENTRYMON, and the influence of initial feedlot weight (INWT). Sire biological type had a significant effect on NI, ADG, FT, LMA, MS, YG, and CVL. Dam biological type and KILL had significant effects on all traits excluding TOTMED. Entry month accounted for no differences. Among SBIO groups, British-sired steers exhibited greatest values for ADG (1.39 kg/d), MS (457), FT (1.45 cm), CVL ($891), and NI ($25.62). Continental-sired steers exhibited the largest LMA (97.65 cm) and lowest YG (2.51). Brahman-sired steers exhibited the lowest ADG (1.32kg/d), MS (405), CVL ($859), and NI ($-17.80). Multiple regression was performed to determine which traits had the greatest effect on CVL and NI. Independent categorical effects were SBIO, DBIO, KILL and ENTRYMON, while independent continuous effects were INWT, ADG, FT, LMA, MS and TOTMED. Both CVL and NI were influenced by CW, FT, LMA, and MS, but not by ADG, INWT, or TOTMED. Phenotypic correlation coefficients were determined among all traits. Highest correlations were present between CVL: and NI, CW, ADG, and LMA (0.80, 0.81, 0.54, and 0.49, respectively). Strong correlations were seen between ADG and CW (0.63), FT and YG (0.87) and YG and LMA (-0.51). Marbling score was moderately correlated to CVL (0.30) and NI (0.30). This study indicates that a wide variety of traits interact to determine CVL and NI in retained ownership programs, and that maximizing carcass value does not ensure increased profitability.

An expert system to predict the fertility of beef heifers was developed using the A.I. Toolkit KAPPA-PC 2.33. The knowledge base was developed from scientific literature and from a beef cattle reproduction expert. The expert system computes an evaluation age, age both at the start and end of the breeding season, and weight per day of age to classify a heifer as having either a 3LOW2, 3GOOD2, or 3EXCELLENT2 likelihood of conception. The expert system summarizes the information that is entered into the computer and creates a text file of the summary. It also gives explanations for every prediction to help identify and alleviate any problem areas that may affect a heifer1s ability to reproduce. The program requires an IBM compatible computer installed with Windows 3.13 or greater. From simulated data for purebred or crossbred British cattle, there was 72% prediction agreement between the expert system and the expert. From analysis of historical data of Hereford-Angus crossbred cattle, heifers categorized as 3LOW2 and 3GOOD2 had significantly higher observed pregnancy rates than expected for each category. There was no significant difference between observed and expected pregnancy rates for heifers in the 3EXCELLENT2 category. Pregnancy rates for post-weaning and pre-breeding evaluations for the 3LOW2 heifers were found to be lower from the combined 3GOOD2 and 3EXCELLENT2 heifers at P=.03 and P=.06 respectively. Observed successful calving rates for heifers categorized as 3LOW2, 3GOOD2, and 3EXCELLENT2 did not differ significantly from the expected calving rates for each category. / Master of Science

<p>Within the last few decades, swine breeding programs have been refined to include pork quality and novel carcass traits alongside growth, feed efficiency, and carcass leanness in the selection programs for terminal sire lines with a goal to produce high quality and efficient pork product for consumers. In order to accurately select for multiple traits at once, it becomes imperative to explore their genetic and biological architecture. The genetic architecture of traits can be explored through the estimation of genetic parameters, genome-wide association studies (GWAS), gene networks and metabolic pathways. An alternative approach to explore the genetic and biological connection between traits is based on principal component analysis (PCA), which generates novel “pseudo-phenotypes” and biological types (biotypes). In this context, the main objective of this thesis was to understand the genetic and biological relationship between three growth, eight conventional carcass, 10 pork quality, and 18 novel carcass traits included in two studies. The phenotypic data set included 2,583 records from female Duroc pigs from a terminal sire line. The pedigree file contained 193,764 animals and the genotype file included 21,344 animals with 35,651 single nucleotide polymorphisms (SNPs). The results of the first study indicate that genetic progress can be achieved for all 39 traits. In general, the heritability estimates were moderate, while most genetic correlations were generally moderate to high and favorable. Some antagonisms were observed but those genetic correlations were low to moderate in nature. Thus, these relationships can be considered when developing selection indexes. The second study showed that there are strong links between traits through their principal components (PCs). The main PCs identified are linked to biotypes related to growth, muscle and fat deposition, pork color, and body composition. The PCs were also used as pseudo-phenotypes in the GWAS analysis, which identified important candidate genes and metabolic pathways linked to each biotype. All of this evidence links valuable variables such as belly, color, marbling, and leanness traits. Our findings greatly contribute to the optimization of genetic and genomic selection for the inclusion of valuable and novel traits to improve productive efficiency, novel carcass, and meat quality traits in terminal sire lines.<br></p><p></p>