The objective of this study is to determine the change in reliability from non genomic evaluations or Parent Averages to genomic evaluations. Due to recent industry popularity of genomic evaluations the California Polytechnic University, San Luis Obispo, decided to participate in the genetic movement of the dairy cattle industry. Genomic evaluations of both Holstein and Jersey cows at the Cal Poly dairy were chosen based on genetic superiority in order to possibly generate more income for the dairy and increase the herd’s popularity. Leading genomic companies such as Pfizer Animal Health, and GenSeek made genomic evaluation of the Cal Poly herd affordable by donating genomic sampling kits. Using the BovineSNP50 Bead Chip and BovineSNP6 Bead Chip, hair and blood samples were taken from the Cal Poly cows and heifers and were sent to the respected companies to generate official genomic evaluations. The data that this project focused on was the change in reliability of health traits such as Productive Life, as well as type and production traits including Net Merit Dollars, Cheese Merit Dollars, Genomic Total Performance Index, and Predicted Transmitting Ability for Type. Increases from traditional parent averages reliabilities to genomic evaluations reliabilities were obtained for all 6 core traits that were evaluated from the tested animals. In 59 Jersey’s that were tested, average reliabilities scores increased from an average of 45% to 69.61%. In addition the 51 tested Holstein females reliabilities raised from 43% to 74%. The genomic evaluations also suggest that the Cal Poly herd is genetically superior, they have two cows in the California top 100 GTPI cow and heifer lists for their respected breed. The gain in reliability of core industry traits and development of genetically superior animals of the Cal Poly herd has in turn increased their popularity of their herd, as well as potentially generating more income from its superior cows and heifers. A genomic based breeding program that Cal Poly has installed will speed up genetic progress of its herd by two years for each generation. The genomic evaluations of the Cal Poly herd will be used as a breeding tool to generate superior genomic bulls and heifers for potential future income.

The algorithm that is used for estimating the variance of genetic components is called Method R, and it will be used to analyze the correlation between Traditional Total Performance Index (TPI) to the Genomic Total Performance Index (GTPI/GJPI). The algorithm Method R, must equal 1 regardless of the sample size in order for the theory to be true (Reverter, 1994). If the computed R is greater than 1, then the variance component ration or slope is underestimated, but if it is less than 1 it is overstated (Reverter, 1994). Moreover the Method R algorithm will essentially prove that if the newly designed, chromosome based, genomic predictions are correlated with the traditional parent averages.

The methods included the development of income statements, balance sheets, and economic costs and returns in order to evaluate the profitability of the farming and processing enterprises for each business. The financial data were collected from a previous study done by Nicholson and Stephenson (2006) for the fiscal year 2003. Tabular summaries of the key information from these statements were constructed to facilitate comparisons of the farming and processing enterprises separately for the three businesses.

Results indicated that similar size operations in terms of cow numbers can have highly different production and financial outcomes. For two of the three businesses, the processing enterprise was profitable based on net income, but only one business had a positive (and small) rate of return on assets (accounting for equity capital and operator labor costs). None of the three processing businesses were profitable when the full economic costs of milk production and processing were accounted for. It is also important to note that none of the three operations had positive net incomes for both the dairy and processing enterprises, which appears to question a basic premise underlying value-added businesses. Although this study will be beneficial for the business owners and others interested in value-added operations, a more in-depth and up-to-date study would be beneficial to determine the specific factors involved in a successful value-added enterprise.

Abstract

The objective of this project was to determine if increased stress levels could affect morbidity and mortality rates in calves. The source for this study was a group of 132 calves at the Cal Poly Dairy available for observation. For each test day, calves were scored on a scale of 1-3 based on how stressed the calf was. After all the data were collected, relationships between age, sex, breed, and observation day were determined in SAS using a Proc Probit method. The effects of breed and sex were not significant in the analysis. However, one of the observation days (January 17^th, 2012) may have been significant, which led me to determine if weather affects the results. When observing the raw data, more calves scored a 2 or 3 on days when the weather changed. Although this method proved to not be very effective when determining stress levels in calves, I was able to pinpoint reasons as to why morbidity and mortality rates may increase on large dairies. Muddy, wet conditions have proven to be the source of increased morbidity because disease-causing bacteria can grow rapidly in these conditions. On days when the calf hutches were surrounded by mud, scores went up. Some practices that could be implemented to improve calf hutch conditions could be regular cleaning and keeping calves in a dry, draft-free area. Calf maintenance is crucial on any dairy to keep animals healthy and prevent economic loss.

Key words: copy number variation, growth hormone, growth hormone releasing hormone, insulin-like growth factor, insulin, single nucleotide polymorphism