Document Type
Thesis - Open Access
Award Date
2020
Degree Name
Master of Science (MS)
Department / School
Agronomy, Horticulture, and Plant Science
First Advisor
Melanie Caffee
Abstract
Current strategies for phenotyping (for traits like biomass) numerous breeding lines under field conditions demand significant investment in both time and labor. Unmanned aerial systems (UAS) can be used to collect vegetation indexes (VI) with high throughput and could provide an efficient way to predict forage yield in breeding nurseries with accuracy. The main objective of the study was to evaluate the use of VIs derived from UAV collected images for estimating crop biomass. For this study, forage trials consisting of 35 oat genotypes were carried out at three locations in 2018 and four locations in 2019. Unmanned aerial vehicles (UAV) equipped with multispectral and visible sensors were flown over experimental plots in Volga, South Shore, and Beresford, several times throughout the 2018 and 2019 growing seasons. Images were also collected in Pierre in 2019 just prior forage harvest. Fresh and dry biomass were collected on each plot at each location. Several VIs derived from the UAV collected pictures were significantly positively correlated with fresh and dry biomass for the locations Volga and Beresford (r=0.2-0.65). However, none of the VIs were significantly correlated with crop biomass in South Shore. Multiple linear regression models (MLR) were developed for each location to predict fresh and dry biomass using VIs, plant height, crown rust severity and chlorophyll content as explanatory variables. The best predictive models for dry biomass prediction had a R-square value of 0.52 for Volga, 0.67 for Beresford and 0.25 for South Shore. For fresh biomass prediction, selected models had a R-square values of 0.83 for Volga, 0.9 for Beresford, and 0.44 for South Shore. Results from Beresford and Volga suggests that VIs derived from UAV collected could be useful for biomass prediction. Yet, multiple years of trial data would be necessary to further validate the potential use of UAV for estimating oat biomass.
Library of Congress Subject Headings
Drone aircraft.
Oats -- Breeding.
Forage plants -- Yields.
Plant biomass.
Format
application/pdf
Number of Pages
78
Publisher
South Dakota State University
Recommended Citation
Sharma, Prakriti, "Use of Unmanned Aerial System (UAS) for High Throughput Evaluation of Forage Yield in Oat Breeding Nurseries" (2020). Electronic Theses and Dissertations. 3941.
https://openprairie.sdstate.edu/etd/3941
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Rights Statement
