Routine Activity Theory and Farm Equipment Theft: A Macro-Level Approach

Though a handful of studies have explored the relationship between farm characteristics and theft of farm equipment, all have been focused at the micro level. Put differently, they have sought to determine whether a relationship exists between likelihood of theft victimization and the characteristics (e.g., size, location) of individual farming operations. The current study builds upon this work by seeking to determine whether county-level factors (in line with the routine activity theory framework) serve to influence the incidence of farm equipment theft within counties. Data are derived from the National Incident-Based Reporting System, the Census of Agriculture and the United States Census of the Population. Results are on the whole supportive of the theory's application to the problem and suggest that macro-level investigations constitute a worthwhile approach to better understanding agricultural victimization.

Lighting and Marking of Agricultural Equipment on Highways: Summary of ASAE Standard S279.18

Agricultural vehicles on public roads can pose risks to their drivers and to drivers of other vehicles. Proper lighting and marking increase visibility of the farm equipment. This 6-page publication summarizes agricultural equipment lighting and marking standards. Written by Serap Gorucu, Charles Brown, and Carol Lehtola, and published by the UF/IFAS Department of Agricultural and Biological Engineering, revised February 2021.

The Impact of Financial Factors on the After-Sales Service of Agricultural Machinery: A Case Study of Chinese Agricultural Machinery in South Africa

Compared to other countries, the level of agricultural mechanization in Africa and South Africa is relatively low. Among the factors that influence agricultural mechanization, after-sales service of agricultural machinery is among the most significant. On the other hand, financial resources primarily impact on improvement and enhancement of after-sales service of farm equipment. In this paper, a questionnaire was employed as the method of quantitative data collection to assist in the analysis of data from 739 respondents in the Chinese context. Due to the Covid-19 pandemic in 2020 (Mmbengwa & Qin, 2020), no questionnaires were collected from South Africa for the purposes of this paper. A standard multiple regression analysis (MRA) was utilized to analyze the data collected from the structured questionnaires. Evidence from this study suggests that combining these financial resource factors has a major effect (F2 = 0.802) on the after-sales service of farm equipment. The high scores obtained for economic factors and analyzed in this study mean that, to a large extent, these have a major impact on China’s after-sales service for agricultural machinery in South Africa.

Examining the Association Between Age and Tractor Driving Performance Measures Using a High-Fidelity Tractor Driving Simulator

Highlights This study uses a new tractor driving simulator to examine the impact of age on perception response time in an emergency braking situation. The results demonstrate increased risk for crash among older farm equipment operators. Abstract. Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S. In the agriculture industry, where tractor-related incidents are the leading cause of occupational fatality, fatal crashes occur more frequently among senior farm equipment operators (FEOs) than younger FEOs. This study examined the association between age and driving performance among FEOs using a simulated driving environment. We demonstrated that older FEOs have longer perception response times when encountering an incurring semi-truck during a simulated drive than younger FEOs. These results persisted when adjusted for selected medical diagnoses and medications, tractor generation, and tractor horsepower. However, due to the small sample size and limitations of the tractor driving simulator, its use for event perception response time research is questionable. The tractor driving simulator used in this study may be better suited for distracted driving studies and studies comparing the ways in which FEOs drive passenger vehicles compared to tractors. Keywords: Driving simulation, Perception response time, Senior drivers, Tractor.

Technology’s Tools

The evolution from farmer-miller craft distilling to large-scale commercial industrial distilling was abetted by inventions and innovations that were related either directly or indirectly to the distilling process. Some inventions that were directly applicable to the distilling process included the high-capacity column still, developed through several iterations in the 1820s. In 1828 European inventor Aeneas Coffey patented an improved design, and it was later refined by American inventors. Other inventions beneficial to industrial distilling included grain elevators, slop dryers, hoists, and the barrel storage rack developed by Frederick Stitzel. Steam-powered railroads and boats, farm equipment, glass bottle production, and improved grain varieties also influenced distilling. Many inventions required changes in structures or transport and thereby modified the distilling landscape with new forms and placements.

Examination of Realism in a High-Fidelity Tractor Driving Simulator

HighlightsDescribes the creation of a new high-fidelity tractor driving simulator.Describes the perceived realism of a tractor driving simulator among 99 Midwestern farm equipment operators.Examines how farm equipment operator characteristics affect perceived realism of a tractor driving simulator.Discusses potential improvements for future generations of tractor driving simulators.Abstract. Transportation-related incidents are the leading cause of occupational fatalities for all industries in the U.S., including the agricultural industry, which suffers thousands of crashes involving farm equipment each year. Simulated driving studies offer a safe and cost-effective way to conduct driving research that would not be feasible in the real world. A tractor driving miniSim was developed and then evaluated for realism at the University of Iowa among 99 Midwestern farm equipment operators. It is important for driving simulators to have a high degree of realism for their results to be applicable to non-simulated driving operations. High-fidelity driving simulators facilitate extrapolations made by driving research but should be re-tested for realism when changes are made to the design of the simulator. The simulator used in this study emulated a tractor cab with realistic controls, three high-resolution screens, and high-fidelity sound. After completing a 10-minute drive, farm equipment operators completed a survey and scored four specific domains assessing specific characteristics (i.e., appearance, user interface, control, and sound) of the tractor simulator’s realism using a seven-point Likert scale (from 0 = not at all realistic to 6 = completely realistic). An overall realism score and domain scores were calculated. Farm equipment operators were also asked to provide recommendations for improving the tractor miniSim. Overall, farm equipment operators rated the simulator’s realism favorably (i.e., >3 on a scale from 0 to 6) for all individual items and domains. The appearance domain received the highest average realism score (mean = 4.58, SD = 1.03), and the sound domain received the lowest average realism score (mean = 3.86, SD = 1.57). We found no significant differences in realism scores across farm equipment operator characteristics. The most frequently suggested improvements were to tighten the steering wheel (27%), make the front tires visible (19%), and that no improvements were needed to improve the simulator realism (18%). This study demonstrates that the new tractor miniSim is a viable approach to studying farm equipment operations and events that can lead to tractor-related crashes. Future studies should incorporate the suggested improvements and seek to validate the simulator as a research and outreach instrument. Keywords: Driving simulator, Farm equipment operators, Realism, Tractors.