5 pp. / In this publication we make a recount of basic terms and acronyms used in describing the functionality and capabilities of precision agriculture technologies. Growers seeking to acquire new systems or upgrade their existing equipment need to be fluent in terminology used in communications, hardware, software, and other areas in order to make good decisions at the time of buying equipment. This information is also useful to educate equipment operators in the in-and-outs of this technology and this way be able to maximize the use of these expensive upgrades.

7 pp. / In this publication, we will make the case of what Precision Agriculture (PA) technologies can do to enhance the productivity of farming systems, with particular attention to the case of irrigated agriculture in the semi-arid Arizona. This guide is intended to aid growers to select the right technology when considering the need to acquire new, or upgrade existing equipment.

No description available.

The objectives of this internship were to demonstrate and apply the knowledge and technical training obtained during Doctor of Engineering coursework and to become familiar with the organizational approach to problems. These objectives were fulfilled in three commercial research and development projects in the field of precision agriculture. The first project involved optimization of a center pivot irrigation system in coordination with the system’s manufacturing company in order to apply irrigation water to maintain uniform soil water content across the field. An optimization-simulation model was developed for this purpose using a dynamic programming approach. The simulations run by the optimization model showed that the existing pivot speed prescription resulted in a more uniform soil water content across the field reducing the crop yield losses. The objective of the second internship project was to analyze the agricultural drainage industry for identification of the potential applications of the spatial soil information into agricultural drainage design and construction. In order to accomplish this task, a comprehensive literature survey was conducted with an emphasis on the drainage approximate equation and numerical methods. Software tools that are currently employed in drainage design and construction were evaluated. A detailed market analysis was conducted with a focus on the industry stakeholders. A strategic strengths, weaknesses, opportunities and threats (SWOT) analysis was conducted for the agricultural drainage industry using Porter’s five forces method. The last internship project involved investigation of the potential for using soil information obtained by SIS in the assessment of soil salinity. A correlation analysis was conducted between the soil paste extract electrical conductivity values measured in the laboratory on collected soil samples and those estimated using the soil resistivity values collected by the SIS, which is a measure of soil salinity. The results showed no clear correlations. While the internship projects provided the intern the opportunity to apply some of the analytical methods learned as part of the Doctor of Engineering coursework, they also provided invaluable experience for the intern to understand research and development projects in a business environment, which was one of the major objectives of the internship.

The academic literature suggests that precision agriculture (PA) is revolutionizing the agricultural sector, with claims that it can enhance sustainability through technological advancements such as tractors with automated guidance, sensor suites, satellites, and drones. The literature on PA widely asserts PA has sustainability benefits claiming that these emerging agricultural technologies will address food system challenges. These challenges include improving the state of food security in the face of a growing global population and the ongoing threats of climate change and environmental degradation caused by agriculture by enhancing agricultural efficiency, productivity, and profits for farmers. Despite this pervasive notion of an inherent link between PA and sustainability, questions persist regarding the substantiation of these "sustainability" benefits, particularly in the promotion of these technologies. To investigate this link between PA and sustainability, this thesis considers the following research questions: What are the key factors and influences that have contributed to the enduring connection between PA and sustainability within the academic literature and how is the concept of sustainability conceptualized and operationalized within the academic discourse on PA? Employing an inductive constructivist perspective, this research examines academic literature collected through systematic literature review and interview transcripts from semi-structured interviews with key informants from academia, to explore the dominant models of sustainability present in the literature and the factors that have contributed to the formation of this inherent link. Drawing on this constructivist perspective, the research demonstrates that sustainability is not an inherent aspect of PA but rather a construct shaped by the various actors responsible for the promotion of PA. This implies that those actively advocating for or endorsing PA, construct the understanding and portrayal of sustainability in relation to PA, leading to a convergence of sustainability conceptualizations reflective of existing productivist paradigms in agriculture. Considering these findings, this thesis contributes to the greater literature which asserts that PA, although full of promise, may reinforce the issues created by contemporary agriculture.

Master of Science / Department of Biological & Agricultural Engineering / Ajay Sharda / In recent years, the technology employed on precision row-crop planters has rapidly advanced. These new technologies include automatic downforce control systems and electronic drive singulation seed meters. These new technologies offer producers higher productivity through high speed planting and increased yield potentials through accurate seed spacing and placement. To begin to understand the benefits and performance of these new technologies, research must be conducted that specifically targets these new systems. With this research, producers would be able to better select equipment for their operation and have a deeper understanding of proper system operation and settings. A test stand, of a scissor-lift type design, was developed to evaluate row crop planter automatic downforce systems. Evaluation of a planter’s automatic downforce system is important for understanding the planter’s capability of maintaining target seeding depth throughout varying field conditions. The test stand consists of a horizontal platform that can raise and lower to simulate terrain changes as well as a mechanism to load the planter row unit’s opening discs to simulate varying soil texture. The vertical height of the test stand and the disc load can be varied in real-time based on utilizing real-world scenarios under simulated conditions to evaluate downforce system response. The stand incorporated several sensors to obtain the overall applied downforce, applied disc load, applied gauge wheel load, and hydraulic pressure. The test stand’s capabilities were evaluated and found to be satisfactory for planter downforce system testing. The test stand was then used to evaluate a commercial automatic downforce system when operating under simulated field conditions. Field data was used to create simulations representing soil type changes, planter operating speed changes, and extreme conditions such as a hard, packed clay or rocky soil type. It was found that the evaluated downforce system was able to maintain target gauge wheel load to within ±223 N for at least 94% of the time during all simulations. This would suggest that the planter would be able to maintain target seeding depth for at least 94% of field operations. Another key aspect for precision agricultural planters is to achieve accurate seed spacing at varying speeds. An electronic drive singulation seed metering system was evaluated to gather the meter’s effectiveness for high speed planting during straight and contour farming mode using simulated field conditions. The simulated conditions were used to gather the meter’s response when encountering high planting speeds, accelerations, decelerations, point-rows, and contours. These meters were found to be highly accurate, with less than 1.5% error in target seed meter speed during all simulated conditions. The meters were also found to have a response time that was always 0.34 seconds or less for all simulated conditions.

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Master of Agribusiness / Department of Agricultural Economics / Arlo Biere / With a large portion of U.S. farm production expenditures related to the cost of fertilizer, seed, and chemicals, producers within the Corn Belt region are looking for new methods and/or planting processes that would deliver higher levels of production efficiencies and lower operating costs. Specifically within the planting operation, Corn Belt producers are faced with the challenge to better manage the higher cost of crop inputs in order to sustain profitability. The primary objective of this thesis is to examine new planting technologies that would better manage planting applications while directly lowering related input costs. Another objective is to understand through regression analysis how various planting variables affect yield potential. Results from the regression analysis illustrate how the various planting variables affect yield and show the importance of “realtime” planter management, advancements possible only with the new planter technology. Customer surveys and several on-site customer visits were conducted throughout the Corn Belt to better understand the actual needs of producers for new planting technologies. Throughout the customer visits, specific questions about the producers’ planting operation were asked to find new ways for precision technology to help increase overall productivity and ultimately profitability. Producer comments and feedback were analyzed through Quality Functional Deployment (QFD) practices and aligned into product development programs. The products developed from the customer research will help producers in the Corn Belt to reduce corn production inefficiencies and, potentially, increase profit margins, assuming profit levels remain steady and/or increase in lieu of reduced input costs.Farm level net present value (NPV) analyses of new planting technologies were performed. Corresponding yield data from efficiencies gained in seed corn placement and control during “real-time” planting applications were integrated into the NPV analyses along with the precision technology costs. The NPV results were positive.

Doctor of Philosophy / Department of Agronomy / V. P. Vara Prasad / Crop assessment and monitoring is important to crop management both at crop production level and research plot level, such as high-throughput phenotyping in breeding programs. Optical sensors based agricultural applications have been around for decades and have soared over the past ten years because of the potential of some new technologies to be low-cost, accessible, and high resolution for crop remote sensing which can help to improve crop management to maintain producers’ income and diminish environmental degradation. The overall objective of this study was to develop methods and compare the different optical sensors in crop assessment and monitoring at different scales and perspectives. At crop production level, we reviewed the current status of different optical sensors used in precision crop production including satellite-based, manned aerial vehicle (MAV)-based, unmanned aircraft system (UAS)-based, and vehicle-based active or passive optical sensors. These types of sensors were compared thoroughly on their specification, data collection efficiency, data availability, applications and limitation, economics, and adoption. At research plot level, four winter wheat experiments were conducted to compare three optical sensors (a Canon T4i® modified color infrared (CIR) camera, a MicaSense RedEdge® multispectral imager and a Holland Scientific® RapidScan CS-45® hand-held active optical sensor (AOS)) based high-throughput phenotyping for in-season biomass estimation, canopy estimation, and grain yield prediction in winter wheat across eleven Feekes stages from 3 through 11.3. The results showed that the vegetation indices (VIs) derived from the Canon T4i CIR camera and the RedEdge multispectral camera were highly correlated and can equally estimate winter wheat in-season biomass between Feekes 3 and 11.1 with the optimum point at booting stage and can predict grain yield as early as Feekes 7. Compared to passive sensors, the RapidScan AOS was less powerful and less temporally stable for biomass estimation and yield prediction. Precise canopy height maps were generated from a CMOS sensor camera and a multispectral imager although the accuracy could still be improved. Besides, an image processing workflow and a radiometric calibration method were developed for UAS based imagery data as bi-products in this project. At temporal dimension, a wheat phenology model based on weather data and field contextual information was developed to predict the starting date of three key growth stages (Feekes 4, 7, and 9), which are critical for N management. The model could be applied to new data within the state of Kansas to optimize the date for optical sensor (such as UAS) data collection and save random or unnecessary field trips. Sensor data collected at these stages could then be plugged into pre-built biomass estimation models (mentioned in the last paragraph) to estimate the productivity variability within 20% relative error.

Current trends in agricultural equipment have led to an increasing degree of autonomy. As the state of the art progresses towards fully autonomous vehicles, it is important to consider assumptions implicit in the design of these vehicles. Current automation in harvesters have led to increased sensing and automation on current combines, but no published research examines the effect of machine size on the viability of the autonomous system. The question this thesis examines is: if a human is no longer required to operate an individual harvester, is it possible to build smaller equipment that is still economically viable? This thesis examines the appropriateness of automating these machines by developing a conceptual model for smaller, fully autonomous harvesters. This model includes the basic mechanical subsystems, a conceptual software design, and an economic model of the total cost of ownership. The result of this conceptual design and analysis is a greater understanding of the role of autonomy in harvest. By comparing machine size, machine function, and the costs to own and operate this equipment, design guidelines for future autonomous systems are better understood. It is possible to build an autonomous harvesting system that can compete with current technologies in both harvest speed and overall cost of ownership. / Master of Science