This study evaluated the potential of using simple, semi-empirical resistance models for the direct estimation of crop evapotranspiration as an alternative to the traditional approach involving a reference equation and a crop coefficient. It consisted of three major parts. The first part originally aimed at the development of simple expressions for the aerodynamic and surface resistance terms in the Penman-Monteith equation. This goal could not be achieved because of two reasons: First, the determination of aerodynamic resistance was rendered impossible because of problems with the measurements, and, secondly, the values of surface resistance, back-calculated from the Penman-Monteith equation, turned out to be very sensitive to the estimates of aerodynamic resistance. In the second part, two forms of the Penman-Monteith equation and one form of the Shuttleworth-Wallace model were compared to each other and to the traditional KimberlyPenman approach. The analysis showed that (1) it was possible to fit a simple form of the Penman-Monteith equation to measured data, (2) one form of the Penman-Monteith equation allowed a better fit than the KimberlyPenman approach and ( 3) the Shuttleworth-Wallace model provided a slightly better fit to the data than the Penman-Monteith equation. In the third part, the possibility of estimating net radiation and soil heat flux was investigated and a comparison was made between meteorological observations obtained at a grassed weather station and those obtained above an agricultural crop. The results indicated that (1) it was difficult to obtain an accurate estimate of net radiation or soil heat flux for a partial canopy and (2) major differences existed between measurements of vapor pressure deficit and wind speed obtained above an agricultural crop and at a grassed weather station. From the analysis, it is concluded that the benefit of using a semi-empirical form of the Penman-Monteith equation instead of the traditional approach is limited, in particular for the prediction of crop evapotranspiration from limited historical measurements executed at a grassed weather station. As an alternative, the use of an elaborate multi-layer model for the determination of more versatile crop coefficients is suggested.

Much interest has been focused on site-specific crop production since the introduction of grain yield monitoring systems. Considerable research has been conducted in the area of site-specific grain production. Lack of a cotton yield monitor has slowed implementation of site-specific practices in cotton production. However, due to the intense level of management corrunonly associated with in cotton production. it may prove to be an ideal crop for site-specific practices. Preliminary testing was conducted in the fall of 1995 to verify that a batch weighing system used in conjunction with Global Positioning System (GPS) equipment was a satisfactory method of monitoring cotton yield variability for field-scale research. The objective of the yield monitoring system was to enable field-scale research, rather than being restricted by small plots. The weighing system was improved in 1996 by increasing the weighing capacity, ease of operation, and reduction of the basket weight to cotton capacity ratio. In 1996 a five-acre portion of a production cotton field in Milan, Tennessee was selected to monitor spatial variation throughout the growing season. The field was divided into 182 plots. An extensive soil survey was performed on the field in the spring revealing six soil series within the test area. Soil samples were extracted and analyzed from each plot in the spring and the fall. Soil moisture was monitored throughout the growing season from 26 observation sites within the test area. The overall objective of the research was to relate soil chemical and physical variability within a production field to crop yield. 1996 field data was the first of collected a three-year study. Therefore, information obtained from 1996 field data collected cannot be considered conclusive without statistical replication. It should be noted that weather patterns tend to have an effect on spatial performance of crops. Although some of the variables measured during the first year had a greater affect on yields than others.

Automation in agriculture, driven by labor shortages and steep production costs, is integral to the future cultivation of specialty crops such as strawberries. To efficiently harvest a strawberry field, a tri-layered algorithm is developed to address the assignment problem that arises when cooperative robots seek a new row to harvest. The proposed algorithm incentivizes robots to cooperate to maximize yield in minimal time, analogous to human harvesters, making it relatively simple to understand and implement. A primary local auction phase is implemented with a centralized fallback algorithm. The local auction is of constant time complexity and aims to reduce communication time among robots, allowing the algorithm to scale to the large farm and fleet sizes required for commercial production. The decentralized process enables real-time decision making and improves robustness. A Monte-Carlo simulation of the proposed algorithm is developed, and the results are compared to a centralized benchmark process with the algorithm displaying superior scalability

To entice a small-scale hay producer to purchase equipment that will improve their hay hauling operation, a more cost effective and more universal solution must be developed. The objectives of this project are to develop and test a prototype large round bale handler. The prototype was built to industry standards, using modern electronic controls and the latest design and fabrication methods. The prototype makes use of an existing trailer and by doing so can be a less expensive method of hauling hay when compared to other equipment currently on the market. While the combination of the prototype bale handler and new equipment trailer is similar in price to a stand alone round bale handler, a small-scale hay producer might be more likely to purchase the combination of the bale handler and trailer because the trailer can be used for many tasks throughout the year.

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In modern agriculture, nanotechnology has been at the forefront of agrochemical product innovation. For crop protection, researchers have turned to nano-zinc oxide (nano-ZnO) products that could potentially serve as an alternative to copper-based pesticides while mitigating micronutrient Zn deficiency. In this thesis, Zinkicide®, a nano-ZnO (4.5% Zn) based agriculture-grade product formulation has been investigated for their potential use as a broad-spectrum bactericide with systemic activity. Initial studies showed that Zinkicide® exhibits phytotoxicity to susceptible plants and experiences limited rainfastness. It is hypothesized that a suitable spray adjuvant will improve rainfastness and zinc absorption without compromising the antimicrobial efficacy. To test these hypotheses, the effect of three commercially available spray adjuvants – FitoFix®, Photon®, and AgriOil® – on Zinkicide®'s physico-chemical properties including wettability, zinc mobility and rainfastness were evaluated using citrus plants. Effects of adjuvant on Zinkicide® antimicrobial properties were also examined. Characterization results indicated that the composition of spray adjuvants has minimal effect on the deposition pattern (coffee ring effect) of Zinkicide® on glass and almost no effect on citrus leaf substrates. The wettability of Zinkicide® was slightly altered by the addition of adjuvants when tested on both substrates. FTIR data indicates that the adjuvants do not chemically interact with Zinkicide®. The effect of spray adjuvants on Zinkicide® antimicrobial properties were investigated using two model pathogens, Xanthamonas alfalfae and Pseudomonas syringae. The results suggest that the addition of adjuvants had no noticeable effect on the antimicrobial properties of Zinkicide®. The zinc in-planta mobility and rainfastness studies showed that the spray adjuvants have no observable effect on these properties. The above research findings could help advance Zinkicide® research in finding other potential adjuvant candidates in tank-mix settings.

The Appalachian Region is a rich and diverse forest ecosystem impacted by present and past mining activities. The Surface Mining Control and Reclamation Act (SMCRA) of 1977 was enacted to resolve many of the environmental problems caused by surfacing mining, such as landslides, erosion, flooding, and poor water quality. As with many solutions, this one came with its own set of environmental problems due to compaction and the introduction of aggressive non-native grasses and shrubs altering hydrologic processes and ecosystem function. The Forestry Reclamation Approach (FRA) is a method for re-establishing forested ecosystems on mined lands. This project evaluated the effect of FRA on throughfall by comparing 10-, 20-, and 100-year old tree plots consisting of coniferous or deciduous trees. Throughfall rates were significantly impacted by tree type and age. Coniferous trees intercepted more rainfall than deciduous ones and the older trees tended to intercept the least. Presence/absence of leaves impacted throughfall depths for deciduous trees. Throughfall was significantly impacted by storm event characteristics. Results may help guide management of forested watersheds regarding strategies to reduce water yields on mined lands.

Ground truthing actual crop types in an area can be expensive and time-consuming. The California Department of Water Resources attempts to ground truth land use in each county in California every five years. However, this is limited by budgetary constraints and often results in infrequent (more than every ten years) surveying of many counties. An accurate accounting of crops growing in a region is important for a variety of purposes including farm production estimates, groundwater and surface water modeling, evapotranspiration estimation, water planning, research applications, etc. Agricultural land use is continually changing due to development and environmental factors. Currently, USDA NASS provides georeferenced land use maps of regions throughout the U.S. While these are beneficial, the accuracy is not very high for California due to the wide variety of crops grown throughout the state. California has an increasingly complex agricultural system which includes multi-crops changing on an annual and even semiannual basis, long growing seasons, and complex and flexible irrigation schedules. Remotely sensed data from available satellites are used to more accurately classify crop types within the Madera and Merced Counties of California’s Central Valley. An initial classification approach utilizing a simplified decision tree for a data subset of the area considered is presented. In order to accommodate the larger dataset at hand, a computer based approach is applied using the Nearest Neighbor classification algorithm in the computer program eCognition. Iterative analyses were performed to consider a range of scenarios with varying spectral inputs. The results show the methods presented can be beneficial in discriminating 24 of the major crop types from multi-temporal spectral data.

Land application and storage of horse manure and municipal sludge can increase nutrient and bacteria concentrations in runoff. Biochar increases soil nutrient retention when used as a soil amendment. The objectives of this study were to determine if biochar, when mixed with horse manure or sludge, affects runoff concentrations of total Kjehldahl nitrogen (TKN), ammonia-nitrogen (NH3-N), nitrate (NO3-N), total phosphorus (TP), dissolved phosphorus (DP), total suspended solids (TSS), chemical oxygen demand (COD), and fecal coliforms (FC). Horse manure and sludge were applied to 2.4 x 6.1 m fescue plots (six each), with three plots of each material amended with 5-8% biochar w/w. Simulated rainfall (101.6 mm/h) was applied to the 12 treatment plots and three control plots. The first 0.5 h of runoff was collected and analyzed for the above-listed parameters. The data were analyzed using an ANCOVA, with SCS runoff curve number (CN) used as the covariate. In general, CN was directly correlated to runoff concentrations of parameters. Plots with low CN values displayed no treatment differences for any measured parameter. Biochar reduced runoff concentrations of TKN and NH3-N for municipal sludge treatments, and TKN, NH3-N, TP, TSS, and FC for horse manure treatments.

ASABE/ISO Standard 12188-2 provides test procedures for positioning and guidance systems in agricultural vehicles during straight and level travel. The standard provides excellent descriptions of test procedures, however it does not provide detail on methods to carry out the calculations necessary to calculate relative cross-track error (XTE), which is the primary measurement used to judge accuracy of the system. The standard was used to estimate the guidance accuracy of a relatively low-accuracy vehicle at 1.25 and 0.5 m s-1. At 1.25 m s-1, a nearest point calculation overestimated mean XTE by 0.8 cm, or 8.2%. The location sampling density was much higher with a 0.5 m s-1 travel speed, and mean XTE was only overestimated by 0.1 cm with the nearest point method. Power and energy data were recorded using a sled with a known weight to vary the drawbar force on asphalt. This will allow a comparison between the electric and conventional tractor over a range of forces applicable to a 20 HP tractor. The electric tractor was found to consume less than half the energy compared to a Kubota L5030 in a common configuration and a custom configuration to match the weight distribution of the electric tractor. Finger weeding tasks were recorded throughout the year capturing the duration and frequency of these tasks at the University of Kentucky (UK) consumer supported agriculture (CSA) farm. Power and energy data were recorded from the electric tractor while finger weeding. Diesel consumption was also recorded from a conventional tractor while finger weeding. Field data shows that the electric tractor needs approximately 0.532 kWh of energy while a conventional tractor requires approximately 1.258 kWh or energy to finger weed each row of vegetables. Conventional electric bills were compiled for the University of Kentucky CSA establishing an average monthly electric need. Historic NREL data was compiled establishing an average potential solar resource for central Kentucky. It was determined that a 15 kW photovoltaic array could meet the conventional electric needs of the UK CSA and supply the net energy allowing the electric tractor to meet the finger weeding need.