Weber, Kaitlyn Maree Dinges2022-08-022022-08-022022-08-01https://hdl.handle.net/2097/42403Chapter 1: Cattle Feeding Net Returns Simulation: A Confirmation Exercise There is great variability in cattle feeding net returns across the industry due to varying economic risk levels dependent on a multitude of cattle characteristics and attributes. There are very few simulation studies that evaluate the deterministic and stochastic influence of performance and price metric relationship between such inputs and the resulting expected net return distribution. One such study is by Dennis et al. (2018), where the authors evaluated the impact of alternative animal health treatment strategies on net returns. The objective of this study is to replicate the results from Dennis et al.’s net return simulation and approximately verify such results utilizing the KSU – Beef Farm Management Guide Spreadsheet. Utilizing the equations, deterministic and stochastic inputs, and simulated distributions in Dennis et al.’s publication, results indicated that the difference between high-risk and metaphylaxis treated cattle averaged $23.77 higher across all weight categories compared to the original publication. One glaring difference between the results for the return simulation duplication and the original results is the shift of distributions rightward along the x-axis, which represents the net returns per head in dollars per head. The KSU Beef Finishing Budget calculated net return differs from the simulation distributional mean value by as little as $11.09 per head, up to the largest difference of $93.40 per head, with three key factors accounting for much of the differences—mortality, feeding cost, and total revenue. We were able to successfully replicate the study by Dennis et al. (2018) and identify what we believe to be the key difference—the feeder cattle purchase price—between the published study and the duplication attempt, while also comparing expected net returns utilizing the KSU Beef Finishing Budget and determine the calculations attributing to the differences. Chapter 2: Net Return Distributions Across Different Pricing Mechanisms in Fed Cattle Production The cattle feeding industry has a lengthy history of being one of the most variable agricultural sectors concerning profitability (Tonsor, 2022). Price risk, production risk, and quality risk in the fed cattle industry all contribute to this profit variability of cattle placed on feed. While other studies have estimated cattle feeding net return models, this study explicitly considers the mortality rate, performance, quality, and expected net return difference between low health-risk cattle and high health-risk cattle that have been treated with metaphylaxis placed on feed using a stochastic simulation net returns framework that evaluates both live weight and grid pricing revenue methods. The results demonstrate that pen characteristics, such as entry weight, gender, and risk classification influence the mean and variability of production factors, defined as mortality, average daily gain, average feed conversion, and veterinary cost per head. The better we can predict animal health and quantify the uncertainty between low health-risk and high health-risk cattle, the more informed cattle feeders become regarding the profit variability between the two classifications of cattle given live weight and grid pricing. Due to higher transaction prices associated with healthier animals that generally have lower probabilities of morbidity and mortality, there is an incentive to buy higher health-risk cattle at a lower cost. Results further inform industry stakeholders by quantifying the price discount that high health-risk cattle must be purchased at relative to low health-risk cattle to achieve the same breakeven profit.   Chapter 3: Evaluation of Bovine Respiratory Disease Morbidity in the Feedlot and its Effect on Net Return Distributions Costs associated with morbidity are one of the most important determinants of profitability in the feedlot (Gardner et al., 1999). Bovine respiratory disease (BRD) is responsible for a large portion, approximately 75%, of feedlot morbidity and 50-80% of feedlot deaths (Edwards, 1996; Kelly & Janzen, 1986). This study models the impact of the percentage of a pen of cattle individually treated one time, two times, or three or more times for BRD on mortality, performance, and overall expected net returns per head by parameterizing production and profitability risks associated with BRD morbidity in the feedlot. This research adapts a fed cattle net returns model (Belasco et al., 2009; Dennis et al., 2018, 2020) to capture varying mortality rates and stochastic performance metrics—average daily gain, average feed conversion, and veterinary cost per head—as a function of BRD morbidity to model overall fed cattle net return risk. Results indicate that mean net returns per pen decrease as the overall percentage of animals treated within the pen increases. This is driven by a combination of things, including but not limited to, decreased animal performance due to BRD-related sickness, increased veterinary cost per head, and increased mean and standard deviation of the mortality distribution as morbidity increases.  en-US© the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).http://rightsstatements.org/vocab/InC/1.0/Bovine respiratory diseaseBRD treatmentsCattleFed cattle net returnsRisk classificationStochastic simulationDissertation