The primary objective of this master's thesis is to examine a new version of a power unit currently utilized in an unmanned aerial vehicle and develop a simulation model of the power unit. The theoretical groundwork needed for developing a model has been presented, describing components used and the function of the different subsystems. The development of a model is done in the simulation environment of Simscape. Measurements were preformed on the physical prototype of the power unit. These measurements were used to verify the simulation. The results of the simulations and the measurements are presented at the end of the thesis, confirming the simulation model's validity.

This research involved testing several aspects of industrial hemp (Cannabis sativa L.) production, including the impact of tillage on seed and fiber production, optimal harvest time for seed yield and quality, the response of seed yield to nitrogen fertility rates, and the potential of hemp as a forage crop. A three-year study was conducted in Blacksburg and Orange of Virginia State to assess the effects of tillage management and production systems (e.g., seed, dual, and fiber) on hemp establishment and productivity. Two cultivars, Joey (a dual-purpose variety) and EcoFibre (bred specifically for fiber), were planted into seedbeds prepared with conventional tillage and no-till management. The cultivar Joey, lower plant populations under seed production systems resulted in taller plants (P = 0.0002) compared to the dual-purpose production systems in 2020. Greater plant heights (P < 0.0001) with fiber production systems in 2021 and 2022 were due to differences between cultivars and their time of flowering. Conventional tillage resulted in greater (P ≤ 0.0161) plant populations than no-tillage for all production systems in each year, and this response was more pronounced with fiber management in 2020 (tillage × production systems interaction; P = 0.0007). Greater (P < 0.001) yields with fiber systems observed in 2021 and 2022 were largely driven by the more productive EcoFibre cultivar. Despite treatment differences in population density, biomass and seed yields varied less by tillage management and production systems. Lower plant population density was associated with greater biomass and seed yields per plant. However, for desired fiber quality and mechanical harvest feasibility, a higher plant population density is recommended. A second study aimed to determine the optimum harvest time for seed yield of two hemp cultivars. 'Joey', and 'Grandi,', were established in Blacksburg and Orange, Virginia in mid-May/early June of 2021 and 2022. The experiment was conducted as a randomized complete block design with a repeated measurement arrangement and four replicates. Plants were harvested four times at one-week intervals starting in mid-summer. Harvest date significantly affected seed yield, with the response differing by cultivar (cultivar × date interaction; P = 0.001) in 2022 at the Orange site. In Blacksburg, seed yields were similar for the two cultivars and greatest at the second harvest each season (July 22, 2021, and July 25, 2022), although they were substantially lower in 2022 due to drought (1750 vs. 480 kg ha-1; P < 0.0001). In Orange, in 2021, as planting occurred late, harvests were also deferred until August 17, and seed yields were greatest at this first harvest (1180 kg ha-1; P<0.0001). In 2022, yields at the Orange location were highest for Grandi at the first harvest (July 21; 1510 kg ha-1) and for Joey at the second harvest (July 28; 1280 kg ha-1) (Harvest Time by Cultivar interaction, P = 0.0010). Over the subsequent weeks of harvest, yields drastically declined (16 to 41% in 2021 and 27 to 47% in 2022 in Blacksburg; 52% to 91% in 2021 and 28% to 65% in 2022 in Orange, compared to the highest yield). Harvest timing is critical to achieving optimum seed yield, and it varies with cultivar, eco-physiographic location, and weather (e.g., rainfall). Fatty acids (FA) varied by cultivar, location, and harvest timing, but patterns of response were not consistent across FA. Gamma-linolenic (P ≤ 0.002) and oleic acids (P ≤ 0.023) were generally greater in Joey, with greater arachidic acid (P ≤ 0.013) concentrations in Grandi. Stearidonic acid concentrations declined with later harvest date in Orange location (P ≤ 0.0034). A third study aimed to measure hemp's response to different N rates and to determine the ability to predict plant N content and seed yield based on UAV-based multispectral imagery. Two hemp cultivars, 'Joey' and 'Grandi', were planted and five N rates (0, 60, 120, 180, 240 kg N ha-1) were tested in Blacksburg, Virginia in 2020, 2021, 2022. Aerial image acquisition occurred at three different growth stages in 2021 using dji M 300 drones mounted with multispectral sensors. Red/Blue index (R2=0.89), near-infrared (NIR) band (R2=0.84) and Enhanced vegetation index (EVI) (R2=0.81) were better predictors of N content in leaf samples than other vegetation indices that were evaluated. Green normalized difference vegetation index (GNDVI) was the better predictor of hemp seed yield (R2=0.58) than other evaluated vegetation indices. The seed yield of hemp was influenced (P ≤ 0.0177) by the N input in all three experimental years. In 2020, seed yield did not increase steadily with the increase of N rate; the highest seed yield, 1640 kg ha-1, was observed at 120 kg N ha-1. In 2021, maximum seed yield of 2500 kg ha-1 occurred at the maximum N rate (240 kg N ha-1). In 2022, a weak response to N rate was observed; maximum seed yield was 380 kg ha-1, again at 240 kg N ha-1. The overall growth of the hemp plants was affected by limited rainfall and weed pressures in 2022, leading to a significant reduction in seed yield. Response to N rate will vary depending on other factors such as available soil moisture during the growing season, weed pressure, and growing period. A fourth study examined the yield and nutritive value of three hemp cultivars, 'Grandi', 'Joey', and 'EcoFibre' as potential forage crops when harvested at weekly intervals in Blacksburg, VA. The greatest biomass and TDN yields across cultivars were 3.17 Mg ha-1 and 2.08 Mg ha-1 respectively, at two months after establishment in 2021. In the dry 2022 season, biomass and TDN yield were 1.9 Mg ha-1 and 1.03 Mg ha 1, respectively, two months after establishment. Hemp nutritive value measures varied by cultivar and harvest time (P < 0.05). Depending on the cultivar and harvest time, hemp plant biomass contained 13 to 32% CP, 22 to 45% NDF, 20 to 38% ADF, 4 to 9% lignin, and 52 to 80% TDN (cultivar × time interaction; P < 0.05). Hemp CP and TDN decreased gradually with maturation while ADF, NDF, and lignin increased (P<0.0001); however, this decline with maturity did not appear as severe as occurs with many other forages. These preliminary results suggest that hemp has the potential to be used as a forage crop. More research is needed to address hemp management and utilization, including field establishment and production, harvest timing for optimum tonnage and forage quality, and animal intake and performance studies. These findings provide new insights into industrial hemp production in the mid-Atlantic region of the United States. Optimal tillage practices, precise harvest timing, appropriate N fertility rates, and proper management techniques all are crucial for maximizing hemp seed and fiber production and quality. Furthermore, hemp shows promise as a forage crop with its adaptability and favorable nutritional properties. Further research is warranted to refine cultivation techniques, improve crop quality, and explore the full potential of hemp in various industries. / Doctor of Philosophy / Industrial hemp (Cannabis sativa L.) is a versatile crop with numerous applications in various industries, but much work must be done to understand crop responses to management practices and improve its potential as a crop for greater sustainability. In this study, we explored different aspects of hemp agronomic management. Hemp traditionally has been planted into tilled fields, which increases the chance for soil erosion. We examined whether hemp could be established without tillage and found that although tilled fields generally had great populations of taller plants; total biomass and seed yields were not as influenced by tillage. Our research suggests that with some tweaking, hemp can be successfully established without soil tillage. Next, we investigated the optimal time to harvest hemp for maximum seed yield. Harvesting at the right moment is crucial, as seeds ripen unevenly, resulting in varying quality and yield. By carefully timing the harvest, we can maximize seed yield and ensure high-quality seeds. Our cultivars were best harvested in a late July to early August time frame. Under favorable weather conditions, we observed seed yields ranging from 1,180 to 2,510 kilograms per hectare, depending on the hemp cultivar and location. Additionally, we studied the response of hemp seed yield to nitrogen fertilization rates. Nitrogen is an essential nutrient for plant growth, and we found that nitrogen significantly influenced seed yield, although the pattern of response varied by growing conditions. Over three years, seed yields ranged from 380 to 2,510 kilograms per hectare. Yields generally increased with nitrogen inputs but were highly affected by available moisture. Fertility studies help farmers determine the ideal nitrogen levels for their hemp crops, promoting healthy growth, maximizing yield, and minimizing environmental contamination. Within this study, we also evaluated aerial imagery technologies to monitor plant nitrogen status and we observed that remote sensing technologies are promising for building predictive nutrient management tools. Lastly, we explored the potential of hemp as a forage crop. Hemp plants have unique nutritional properties (e.g., protein, fatty acids) and can be used as feed for livestock. We investigated the best time to harvest hemp for maximum biomass and nutrient content, important factors for animal nutrition. Hemp plants grow rapidly and within two months after establishment they yielded up to 3.17 metric tons of biomass per hectare, with relatively high nutritional value. Overall, these studies provide valuable insights into hemp production, including the importance of tillage practices, optimal harvest timing, and appropriate nutrient management. By applying these findings, farmers can enhance their hemp cultivation techniques, resulting in higher yields, improved crop quality, and better environmental outcomes.

Soil erosion by water is a main form of land degradation worldwide. The problem has been addressed, among others, in the United Nations Sustainability Goals. However, for mitigation of erosion consequences and adequate management of affected areas, reliable information on the magnitude and spatial patterns of erosion is needed. Although such need is often addressed by erosion modelling, precise erosion monitoring is necessary for the calibration and validation of erosion models and to study erosion patterns in landscapes. Conventional methods for quantification of rill erosion are based on labour-intensive field measurements. In contrast, remote sensing techniques promise fast, non-invasive, systematic and larger-scale surveying. Thus, the main objective of this study was to develop and evaluate automated and transferable methodologies for mapping the spatial extent of erosion rills from a single acquisition of remote sensing data. Data collected by an uncrewed aerial vehicle was used to deliver a highly detailed digital elevation model (DEM) of the analysed area. Rills were classified by two methods with different settings. One approach was based on a series of decision rules applied on DEM-derived geomorphological terrain attributes. The second approach utilized the random forest machine learning algorithm. The methods were tested on three agricultural fields representing different erosion patterns and vegetation covers. Our study showed that the proposed methods can ensure recognition of rills with accuracies between 80 and 90% depending on rill characteristics. In some cases, however, the methods were sensitive to very small rill incisions and to similar geometry of rills to other features. Additionally, their performance was influenced by the vegetation structure and cover. Besides these challenges, the introduced approach was capable of mapping rills fully automatically at the field scale and can, therefore, support a fast and flexible assessment of erosion magnitudes.

As drones become more widespread throughout modern industry, the demand for drone automation increases. Drones are used for many applications, but their effectiveness relies heavily on their battery life. By designing, implementing, and evaluating an automatic drone landing and battery exchange system, drone missions can be more streamlined and efficient by eliminating the need for manual battery exchange. Previous projects within this topic rely on high-precision landing combined with a manipulator with low degrees of freedom for battery removal. This project offers a solution that allows less strict landing requirements to better fit drones of different sizes and shapes for a wide variety of applications. This autonomous drone landing and battery exchange system uses a robotic arm with 6 degrees of freedom for battery removal and on-board image processing to locate and land on a large, rotatable landing pad.

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