<p>Of every 10 workers in the world six work in the informal economy, while four out of every five organizations operate in the informal economy. An important sector in the informal economy is street food vending. Street food vendors not only earn their own living but provide a service to the market by making affordable food available quickly to the participants of the street market. While their role in the developing economies cannot be overlooked, not a lot has been known about them. This thesis explores street food vending in Afghanistan and Nigeria. Nigeria is used as an example for the rest of West Africa. In this thesis we will find out what crops are predominantly used by street food vendors, what are the impacts of price volatility on the profitability of street food vendors, are the vendors profitable, and how they make decisions under risk. We will be using tornado graphs, as well histograms, and cumulative density function to determine profitability and risk for street food vendors. We will also be using decision making trees to visualize how decisions are made by street food vendors.</p><p> </p>

<p>The results of previous studies generally show that organic production is more profitable than conventional production. However, as a source of these results, the trials are either of short duration or do not specifically examine the benefits during the transition period, suggesting that previous work may not have captured the full variability of crop net returns. The purpose of this study was to compare the net returns and risks of conventional, transition, and organic cropping systems using long-term crop budgets and stochastic simulations. Conventional crop rotations were represented by a corn / soybean rotation and a corn / soybean / wheat rotation. The organic crop rotation produced corn, soybean and wheat. Historical prices, crop budgets, and FINBIN data are used to develop the long-term crop budgets. The organic crop rotation included a three-year transition period. Ten-year enterprise budgets were created for each crop and rotation so that we could compare the net returns of the transition year of organic crop rotation and the year of organic production. This thesis summarizes the enterprise budget information for each crop in the conventional and organic cropping systems, and summarizes the information used for the simulation analysis. Using @ risk, differences in annual net returns to land between crop rotations were summarized. Results are as follows. First, the transition and organic cropping system was found to have higher net returns to land than the two conventional crop rotations under most of the simulation iterations. Second, the annual net returns during the transition period were relatively low. Third, the highest average annual net return was for organic corn.</p><div><br></div>

This study of the market for apples produced in Massachusetts for markets in Central America was implemented in order to identify and quantify business possibilities in that region. Apple consumption in Central America is very high and growing, with an increase of more than 100% from 2005 to 2009, from $14 million worth of apples in 2005 to $31 million in 2009. There are increased opportunities for apples from the United States to gain access to this market due to the Dominican Republic-Central American Free Trade Agreement (DR-CAFTA), enacted in 2005. This trade agreement lowers barriers and tariffs of products between the US and these countries. Apples are a very important commodity in Central America. For example, apples available for sale in El Salvador are imported from Chile, USA, Guatemala, and sometimes from Canada. In 2009, 52% of the apples imported by El Salvador were from the United States, 43% from Chile, and 4.8% from Guatemala. The majority of apples that are exported to El Salvador from the United States come from Washington State, followed by California and Oregon. During the summer of 2010, 165 consumers were surveyed and several supermarkets chains, wholesalers and local markets in El Salvador were canvassed in order to obtain information on the current apple market in El Salvador, with the goal to assess opportunities for apples from Massachusetts to enter this market. The most important attributes used by those surveyed in El Salvador when purchasing apples were quality (including taste, firmness, and size) and price. Medium and small sized apples are preferred as they are more economical for families, providing an opportunity for US growers to sell their smaller fruit that US consumer do not prefer. Delicious and gala are the varieties sold mostly. Apples are usually bought in supermarkets, fruits stalls in municipal markets, and from fruit peddlers on the street and on buses. During the Christmas holidays of 2010, another marketing survey was conducted to determine the acceptance in Central America of McIntosh apples from Massachusetts. Nearly 800 consumers were surveyed at five Wal-Mart stores in El Salvador after being given samples of McIntosh apples produced in Massachusetts. Consumers particularly liked the sweet-tart flavor, juiciness, and firmness. Due the results of these surveys, Wal-Mart Centro America Mexico expressed interest in developing a relationship with apple growers in the Northeastern United States.

<p>  </p> <p>Data is the foundation of digital agriculture. Data from a wide variety of sensors in the soil, in machinery, or from remote sensing can inform decisions including site-specific land and crop management but capitalizing on these data requires metadata that captures the full story related to production. Answers to metadata questions such as who, what, where, when, and how are often unavailable when aggregated data are analyzed. These metadata are crucial for making accurate operation and management decisions and certainly for developing AI models. Since farmers and researchers exhibit human behavior of forgetting to take notes or entering incorrect information, even with digital means, missing and erroneous records are common. To address this issue, a metadata collection Android app – Meta Ag for agricultural activities was created that automatically appends the operator’s name, time, and space information to an in-field event, and provides a user-friendly interface to gather information with more details describing which activity was done and how. Meta Ag has six main modules, including user registration, geofence construction, accessed geofence recognition, an infobot for extensive activity data collection, setting options for Infobot and data access. By design, manual data input, with automatic validation, when possible, was used for information collection. To achieve this, Meta Ag uses dynamically constructed, interactive option lists for fewer data entry errors. The collected data were stored in a Google Firebase database as central storage for multiple users. To facilitate data interoperability, stored data were made accessible in CSV and JSON format. The Android app collects extensive metadata from database interactive option lists and the infobot as a data collection wizard provides a dynamic environment for data collection in a short time with minimal manual input. The app was also able to reduce missing data as it automatically records the accessed fields and activity time in that field. The Meta-Ag app can work both as a standalone tool and an integration into any other farm information management system.</p>

California state officials have continued to warn and encourage preparedness for the growing threats of water scarcity. This puts pressure on water suppliers to develop technological and managerial solutions to alleviate the problems associated with scarcity. A recent popular management strategy for distributing water is encouraging water transfers. While there has been analyses on water transfers between large districts and agencies, little analysis has been completed for smaller scale trades, i.e. between individuals in the same water district. This analysis models an agricultural water district, based on the Berrenda Mesa Water District (BMWD). In the model, the growers in the district have the collective goal of profit maximization, and the district has the goal of maximizing revenue from agriculture. The district decides if either long term or short term transfers are allowed between growers, who themselves decide to either elect to save more water or trade more water. A game theory simulation model is used to determine the best cooperative management strategy (BCSC), which is defined as a strategy combination which is Pareto optimal and a Nash equilibrium, or Pareto optimal and there are no Nash equilibria. Ultimately, the strategy combination of the district allowing short term trades and the growers electing to sell more water is the BCSC in all tested water scarcity scenarios.

The following study assesses economic and political determinants of foreign direct investment by U.S. firms. Data from the Bureau of Economic Analysis at the U.S. Department of Commerce was used for total and food sector FDI for 35 countries from the years 2001-2008. Using these data in three econometric models, the paper examines the effect on FDI of regional trade blocs as well as political factors such as labor and credit market regulations, and transfers and subsidies. Finally, the thesis provides a comparison of each model on two dependent variables: food sector and total FDI. The study finds that management decision making for FDI differs for agribusiness firms compared to industry as a whole, especially with regards to the host country’s relative wages, language barriers, and membership in the Association of Southeast Asian Countries (ASEAN).

Bison production is an emerging retail meat industry. As demand increases, it creates opportunity for supply-side growth. However, the bison market is volatile and the potential for a drop in the value of bison makes price risk an important factor for producers. Following price risk theory, hedging opportunities for bison producers are investigated using the live cattle futures contract. For the time periods researched, there is no clear evidence that cross-hedging reduces price risk for bison producers. However, there is a possibility that after the bison industry becomes more established and consumer knowledge plays lesser of a role in prices, cross-hedging strategies will be advantageous to producers. / Master of Science

A study was conducted to determine the relationship between agribusiness self-efficacy and business related collegiate courses. One hundred eleven (N = 111) Mississippi and Tennessee secondary agricultural education teachers completed a researcher developed survey that measured agribusiness self-efficacy using 88 competencies from Mississippi and Tennessee secondary agribusiness courses. Participants rated their confidence to teach each competency using a 5 point scale with 1 as no confidence and 5 as very confident. The survey also assessed the types and number of collegiate-level business related courses completed by the participants as well as other demographic factors. Multiple linear regression, ANOVA, and Spearman's rho tests were used to assess relationships between the measured agribusiness self-efficacy and the various demographic factors. The mean agribusiness self-efficacy was 3.18 (SD = 0.788) indicating that teachers are only somewhat confident to teach agribusiness. Factor analysis divided the 88 competencies into nine themes. The overall competency and nine factor competency means were used as dependent variables. Marketing and introductory agribusiness courses loaded on most of the regression models. The number of collegiate business related courses is significantly related to participants agribusiness self-efficacy. Participants with a high GPA were found to have a significantly lower agribusiness self-efficacy as compare to lesser GPA groups. Teaching agribusiness courses increases agribusiness self-efficacy. Utilizing agribusiness textbooks and guest speakers also increases agribusiness self-efficacy. Owning a business was included in most of the agribusiness self-efficacy models. Nine of the ten regression models solely included state department of education facilitated agribusiness professional development. Years of experience was only significantly related to one of the ten dependent variables. No significant relationship was discovered between agribusiness self-efficacy and teacher age. No significant differences in agribusiness self-efficacy was discovered for education level, college major, certification type. It is recommended that universities include a marketing course along with an introductory to agribusiness course to prepare pre-service agricultural education teachers. It is also recommended that secondary agricultural education teachers maintain a professional library with agribusiness textbooks and to utilize guest speakers as needed to optimize agribusiness self-efficacy.

Small and medium-sized farms are an important demographic of the agricultural sector in the Shenandoah Valley and Chesapeake Bay watershed. Having sufficient food system infrastructure available and accessible to these farm operations is essential to help them add value to their farm products; diversify their operations and differentiate their farm and food products in an increasingly competitive and commodity-based food system. Despite its importance, however, local food systems (LFS) frequently have incorrect types or insufficient amounts of the equipment and facilities needed to support these systems. Through the use of two case studies, this study investigates current circumstances, future needs, and offers recommendations for two important components of LFS infrastructure in the Shenandoah Valley. The first study inventories and assesses existing infrastructure capacity available in the region. Using data collected from farmers, LFS organizations, and institutional foodservice organizations, a needs assessment is then completed to determine the specific amounts and types of equipment and facilities which would be needed to meet current LFS infrastructure needs. The second study explores current and potential benefits, and future challenges of a produce auction to impact Mennonite communities in the Shenandoah Valley. This analysis of the Shenandoah Valley Produce Auction (SVPA) was conducted using data obtained from both interviews and surveys. Results indicate that producers, existing infrastructure, and institutional buyers in the region would like to own, use, or rent food system infrastructure. There is unmet LFS infrastructure demand in due to the current lack of enough food cleaning, processing, packaging, and storing equipment in this area. For the SVPA, most of participants were satisfied with the auction. Buyers, however, reported that their procurement from the SVPA is limited by fluctuating prices, demand outpacing supply of produce, insufficient delivery services. Overall, food system infrastructure in general, and the SVPA in particular, were reported to have an important role in the region in supporting market access for local small and medium sized farmers, improve viability of local food system and the regional economy, and facilitating connections between consumers and their local food system. Several recommendations to strengthen the region's LFS are derived from these results. / Master of Science

Yes / Food-animal production businesses are part of a data-driven ecosystem shaped by stringent requirements for traceability along the value chain and the expanding capabilities of connected products. Within this sector, the generation of animal health intelligence, in particular, in terms of antimicrobial usage, is hindered by the lack of a centralized framework for data storage and usage. In this Perspective, we delimit the 11 processes required for evidence-based decisions and explore processes 3 (digital data acquisition) to 10 (communication to decision-makers) in more depth. We argue that small agribusinesses disproportionally face challenges related to economies of scale given the high price of equipment and services. There are two main areas of concern regarding the collection and usage of digital farm data. First, recording platforms must be developed with the needs and constraints of small businesses in mind and move away from local data storage, which hinders data accessibility and interoperability. Second, such data are unstructured and exhibit properties that can prove challenging to its near real-time preprocessing and analysis in a sector that is largely lagging behind others in terms of computing infrastructure and buying into digital technologies. To complete the digital transformation of this sector, investment in rural digital infrastructure is required alongside the development of new business models to empower small businesses to commit to near real-time data capture. This approach will deliver critical information to fill gaps in our understanding of emerging diseases and antimicrobial resistance in production animals, eventually leading to effective evidence-based policies. / This article is part of the research topic "Digital transformation of animal health data: Proceedings of the AHEAD 2017 workshop" (https://www.frontiersin.org/research-topics/5834#articles)