Master of Agribusiness / Department of Agricultural Economics / Vincent Amanor-Boadu / Transforming Belmont Estate from a traditional agricultural production business into a profitable agri-tourism enterprise is the issue addressed in this thesis. The importance of this problem rests on the fact that the author is the general manager of this family business and needs to organize it in ways that facilitates its ability to keep growing in a rapidly changing market environment. Given the increasing positioning of Grenada as a preferred tourist destination and the increasing number of people who are responding to this positioning, the management of Belmont Estate believes that transforming this traditional agricultural production business into an agritourism business will create significant value for shareholders and stakeholders. The process of transforming the organization needs to start with a new way of envisioning it. Therefore, a strategic direction and a compelling value proposition were developed. An assessment of the business environment was conducted to develop a framework where specific strategies could be developed to support the new strategic direction that has been established. Additionally, a financial analysis that focused on the contribution of the different enterprises to the new strategic direction was conducted to assess the potential financial outcome of this effort. The results show that Belmont Estate is well-positioned to benefit from increasing tourism business in Grenada. If the management of Belmont Estate can implement the strategic plan, it can successfully transform Belmont Estate from an agricultural production business into an efficient agritourism business that not only creates value for its shareholders and stakeholders but offers a welcome diversity to Grenada’s growing tourism industry.

Master of Science / Department of Grain Science and Industry / Leland McKinney / The current forage handling equipment in the cellulosic ethanol industry is severely limited by the low bulk densities of baled and ground biomass. Low bulk densities contribute to flowability problems and lack of maximizing trailer capacities. By pelleting we can increase the bulk density and flowability characteristics of forages. The objectives of this research were to evaluate (1) the energy requirements of grinding sorghum stalks, corn stover, wheat straw and big bluestem through two different screen sizes, (2) the energy requirements of pelleting forages from the two grind sizes, and (3) the physical properties of our various end products. The two screen types were found to have significantly different energy consumptions from each other (P<.0001). The majority of the four forage types were also found to have significantly different energy consumptions for grinding from each other (P<.0001). The exception was big bluestem vs. corn (P=.2329). All of the 1/8” vs. 1/8” and 1/8” vs. 3/8” grinds were significantly different from each other (Most P<.0001 and all at least P<.05). 3/8” sorghum was significant against all other 3/8” forage types. No other comparisons were significant for 3/8” vs. 3/8” (All 3/8” sorghum P<.0001). Production rate through the 3/8” screen was almost 3 times that of the 1/8” screen (Average of 400 lb/hr vs. 150 lb/hr). The two screen types were found to have significantly different energy consumptions for pelleting from each other (P<.0001). The four forage types were also found to have significantly different energy consumptions from each other (P<.0001) while the big blue vs. wheat did not. (P=.1192). Particle length for the 1/8” grind ranged from .06 inches to .07 inches, while the 3/8” grind ranged from .08 inches to .12 inches. Pelleting increased bulk density from 6.24 lb/ft3 to 9.99 lb/ft3 for biomass grinds to 31.17 lb/ft3 to 43.77 lb/ft3 for pelleted biomass. Pellet quality ranged from 93% to 98%. A cost analysis indicated that it would take roughly $20 extra per ton for the transportation, pre-processing and storage of pelleted cellulosic biomass than whole corn. This cost is still almost half that of the cost for baled biomass.

Master of Science / Department of Agricultural Economics / Glynn T. Tonsor / The objective of this analysis is to develop econometric models for forecasting fed cattle basis as well as compare these models with historic averaging methods of forecasting basis popular in existing literature. The econometric analysis also aims to identify important determinants of fed cattle basis. Both monthly and weekly models were assessed with data provided by the Livestock Marketing Information Center. All models analyzed the three regions of Nebraska, Kansas, and Texas. Monthly historic average approaches utilized historic fed cattle futures and fed cattle cash price series from January of 1995 through December of 2010. Weekly historic average approaches utilized historic fed cattle futures and fed cattle cash prices series from June of 2001 through December 2010. Data collected post mandatory price reporting implementation in 2001 was used in all econometric models. Overall lags of fed cattle basis, the spread between the nearby live cattle futures contract and the next deferred futures contract, and seasonality regularly proved to explain much of the variation in fed cattle basis in the econometric modeling. Multiple historic average based models were examined on both monthly and weekly frequencies. Once all competing models were estimated in-sample, out-of sample testing was conducted. The forecasting errors of all weekly models were compared to determine which methods prove to be dominant forecasters of fed cattle basis. This testing suggests historic averaging methods outperform the alternate econometric models in out-of-sample work. The econometric models helped to reveal some of the important factors determining fed cattle basis, however lags in collecting data on these factors may inhibit the forecaster’s ability to use these techniques in real time. One interesting revelation in regards to historic averages is the potential of Olympic averages as forecasters. These methods have not been explored in previous academic literature but tend to perform quite well in comparison with other methods explored.

Master of Agribusiness / Department of Agricultural Economics / Kevin Dhuyvetter / This thesis was commissioned by Cooperative Producers, Inc. (CPI) of Hastings, Nebraska in order to better understand the preferences and uses of precision agriculture by customers within the company’s trade territory. With the rapid increase of precision agriculture (hardware, software, services, etc.) it is necessary to get a better understanding of what drives growers to adopt and implement precision agriculture practices. A paper survey was sent out in CPI’s monthly statements to patrons that also included instructions to be able to fill out an online survey if that was preferred. From that offering there were a total of 114 responses providing data from which several technology adoption models were estimated. Based on prior experience with precision agriculture and the development of services offered to growers, it is hypothesized that there are three primary variables influencing a grower’s decision to adopt precision agriculture. If the operation is managed by a younger grower (<40 years old), farms with a larger number of acres, and if a high percent of the operation’s acres are irrigated they will be more likely to adopt precision agriculture practices. The survey results generally revealed that younger farmers, larger farm size, and a higher percentage of irrigated acres did not increase the likelihood of utilizing precision agriculture. The questions asked in the survey were designed to provide information for the development of a tool that salespeople offering precision agriculture services could use to determine if a potential customer with be inclined to adopt and utilize precision agriculture. While some of the results were contrary to expectations they do offer insight into what type of customer adopts precision agriculture and a direction for CPI to move in order to maximize market penetration.

Master of Agribusiness / Department of Agricultural Economics / Michael Boland / Greenhouse gas (GHG) emissions and their negative effect on the environment is a growing concern in the world. It is estimated that agriculture is responsible for 7% of the total GHG emissions in the United States. Currently, environmental policies to regulate GHG are in place in different countries and are expected to increase in the future. Increased awareness about climate change by customers also represents an incentive for companies in measuring their emissions. The objective of this study is to estimate carbon dioxide-equivalent emissions from eight agribusiness retailers in Kansas. Data consisted of two years of energy inputs from the operation of the agribusiness retailers. Carbon emission coefficients were employed to determine carbon dioxide-equivalent emissions associated with the use of each energy input during their operations. Results suggest that electricity is the largest source of total carbon dioxide emissions from the retail operations followed by diesel fuel. Diesel fuel represents the main source of direct emissions and gasoline represents the second largest source of direct emissions. Emissions from the agricultural sector will not be regulated under the current American Clean Energy and Security Act of 2009 but information on their potential carbon footprint may be used in identifying specific processes where emissions could be reduced and to analyze possible climate legislation implications for their operations. If agribusinesses were to be regulated, none of the eight retailers have locations with emission levels that would be subject to the current cap and trade bill passed by the U.S. House of Representatives. But, if they were regulated and had to comply by purchasing carbon credits equal to 5 to 20% of their direct emissions, the cost would be low given estimation of future carbon prices in the literature. Even if agricultural retailers are not directly restricted, they will likely be affected by increases in energy input prices if such legislation is enacted.

Master of Agribusiness / Department of Agricultural Economics / Michael Woolverton / To meet the demand of the 2007 Energy Bill will require a new approach to ethanol production in the United States. The question persists: how can the ethanol industry in the United States produce 21 billion gallons of ethanol from cellulosic sources? This challenge will require changes in the facilities currently manufacturing ethanol, the collection and storage methods to which the Midwestern farmer is accustomed, and a drastic change in farm production practices. Several different methods of cellulosic ethanol production are being examined. One such method is to change the focus from starch based ethanol to ethanol produced by harvest, collection, and manufacture from corn cobs. Research has included surveys, development of economic models, and focus group meetings to determine the feasibility of corn cobs as a viable raw material source for cellulosic ethanol. Findings indicate that: corn cob collection is feasible for the Midwestern farmer. According to the economic models presented in this thesis, Midwestern farmers can benefit economically from the collection of corn cobs. Further, the collection of corn cobs allows for current ethanol plants to be upgraded with new technology without major change in the manufacturing processes. The focus of this research was to determine which method of corn cob collection was preferable for Midwestern corn producers.

Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / This thesis analyzes the hiring and selection processes of five Farm Credit Services (FCS) Associations within U.S. AgBank to determine the effectiveness of potential employee testing and profiling practices as a predictor of success (defined as tenure and retention) within the organization. The data provided by the five FCS Associations were used to analyze whether that the results are a successful tool in predicting the success of a potential employee. Firm managers are acutely aware of the high cost of onboarding a new employee regardless of the industry in which the firm operates. Since employee training and education often takes months, and in some cases, years, it is critical that organizations select qualified, driven, and success oriented employees so that they can minimize the cost of hiring of new employees. To select the best candidates, many firms use personality profiling examinations to determine the candidate’s fit, not only for the job, but also for the company culture. Analyzing past results can assist managers in evaluating the outcomes of the time and cost spent seeking the best employee possible. Analysis was conducted by estimating a binomial logistic regression model using the test scores for loan officer hires from five Farm Credit Associations for the time period of 1999-2009. Each of the examined character traits was an independent variable, along with variables for gender and whether the candidate was a recommended-hire. The dependent variable is whether the employee is still employed with the Farm Credit Association. Results show that while some of the independent variables are statistically significant in predicting the success of an employee, others are not. The implications therein justify the value of the predictive index as an asset to hiring managers, and also provides direction on which traits are most highly correlated with one another and with the overall composite score.

Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / The objective of this thesis is to determine if contract farming of fresh strawberries in Oceanside California is financially feasible. This is being considered as an alternative to managing the 185 acre fresh strawberry farm. The farming business is owned by a large fresh fruit marketing firm. As an independent custom grower I would not be subject to the same constraints as the marketing firm. No changes to management structure or product quality would be necessitated by this change. Assumptions for this study are specific to operating requirements for producing winter strawberries in North San Diego County in California. The cultural practices described and inputs used are considered to be usual for a well-managed commercial farm. The cost and returns are based upon actual historical data and representative of similar if not exact cultural practices and material inputs. The conceptual model used to guide the development of this study was taken from a generic feasibility study framework. It served as a controlled process to analyze the situation and determine the financial outcomes. The economic and financial viability analysis includes costs and returns per acre, monthly cash costs, sensitivity analysis, and overall profitability. The method used to assess the dimensions of viability was to weight them by evaluating key characteristics for relative strengths and weaknesses. The recommendation based upon this assessment is that the overall viability of the proposal is more than 80% and therefore merits the development of a comprehensive business plan.

Master of Agribusiness / Department of Agricultural Economics / Jason Bergtold / The dramatic changes that have taken place in the production agriculture industry in the last decade have the Long Family Partnership wanting to reassess their farm land management strategy. As land owners, they feel as though they might be missing out on profit opportunity by continuing their current lease agreements as status quo. The objective of this research is to determine the optimal land management strategy for the Partnership farm that maximizes net returns for crop production, but also taking into account input costs and risk. Three scenarios were built: (1) a Base Case of the current share-crop and cash lease Agreements; (2) the possibility of farming their own irrigated farm land and continuing to cash lease land used to produce dryland wheat; and (3) deciding to farm all the irrigated and dry land farm acreage themselves. In order to do this, a whole-farm budget spreadsheet model was generated to assess alternative land management scenarios. The difference in net returns between alternative land rental scenarios were then compared and followed by a sensitivity analysis and stochastic analysis using @RISK software. The findings concluded that there was greater potential to increase net farm income while still conservatively managing risk by investing into their own farm land, as not only owners but also as operators. The stochastic and sensitivity analysis confirmed that farming their own land was more sensitive to changes in yields, prices and input expenses. However, even in consideration of the additional risk, the probability of increasing net farm income was greater for the scenarios in which they farmed their own land.

Master of Agribusiness / Department of Agricultural Economics / Jason Bergtold / It is challenging to know when customers are satisfied or dissatisfied with a product or service. Feedback mechanisms such as surveys are frequently used to gain feedback and evaluate the customer’s perceptions of the product or service. John Deere, like most companies, takes an active role in understanding customer satisfaction, using surveys and feedback through field teams and the dealer channel. Shortcomings with this method include the need for customers to voice their complaints first, which can take a significant amount of time, delaying John Deere from providing needed service. The purpose of this research is to examine the usefulness of using primary diagnostic data collected by John Deere to assess customer satisfaction. Specifically, to examine if the number of diagnostic trouble codes (DTCs) on a John Deere 8R series row crop tractor experiences has an impact on customer satisfaction scores reported on surveys. Then determine if this data would be useful to help identify dissatisfied customers proactively. Statistical analysis and regression were used to understand the impact DTC’s have on customer satisfaction. Analysis indicates that for every 100 Total DTC’s a machine exhibits one could expect to see a 4 point reduction in overall CSI score by the customer. This information may prove valuable in being able to understand customer satisfaction more proactively.