Agronomy and Horticulture, Department of
First Advisor
Donald Lee
Second Advisor
Leah Sandall
Date of this Version
12-2023
Citation
A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science
Major: Agronomy
Under the supervision of Professors Donald Lee and Leah Sandall
Lincoln, Nebraska, December 2023
Abstract
Triticale (Triticosecale) is a multifunctional hybrid cereal crop that adopted the hardiness of rye and wheat's high-yielding and nutritional qualities. Plant breeding programs work to improve the quality and number of varieties available to producers through multiple rounds of evaluation and selection. However, traditional phenotyping methods are labor-intensive, time-consuming, and destructive, creating a phenotyping bottleneck. Remote sensing using unmanned aerial systems has the potential to alleviate this issue and change the evaluation of phenotypes in a breeding. Demand for educational resources to advance public awareness and prepare the workforce has increased with the utilization of more technology in agriculture. Limited research focuses on using UAV-derived vegetation indices to measure biomass in triticale. In addition, agriculture professionals need more education and understanding about the potential benefits and practical implementation of remote sensing technologies in plant breeding contexts. This research aims to (1) Evaluate the potential of UAV-derived vegetation indices to estimate above-ground biomass in triticale and (2) Assess the impact of open educational resources on the change in self-reported and objectively assessed knowledge of phenotype evaluation using high throughput phenotyping. The results of study one show high correlations between biomass and several vegetation indices, indicating that UAV-derived vegetation indices have the potential to be used as an alternative to destructive biomass sampling for phenotyping biomass in triticale. The results of study two show the open educational resource High Throughput Phenotyping in Plant Breeding increases learner overall self-reported knowledge, UAV self-reported knowledge and cross-listed self-reported knowledge. In addition, the lesson increases overall objectively assessed knowledge and cross-listed objectively assessed knowledge.
Advisors: Donald Lee and Leah Sandall
Included in
Agricultural Science Commons, Agriculture Commons, Agronomy and Crop Sciences Commons, Other Plant Sciences Commons, Plant Biology Commons
Comments
Copyright 2023, Catherine Kay Mick