Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality

The main goal of this study was to calibrate small unmanned aircraft system (SUAS) based vegetation indices with fertilizer-N application rate and yield for corn and sugar beet. It was hypothesized that canopy reflectance would change with increasing fertilizer-N application rates. The objectives of...

Full description

Bibliographic Details
Main Author: Olson, Daniel O.
Format: Others
Published: North Dakota State University 2019
Online Access:https://hdl.handle.net/10365/29887
id ndltd-ndsu.edu-oai-library.ndsu.edu-10365-29887
record_format oai_dc
spelling ndltd-ndsu.edu-oai-library.ndsu.edu-10365-298872021-09-28T17:10:55Z Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality Olson, Daniel O. The main goal of this study was to calibrate small unmanned aircraft system (SUAS) based vegetation indices with fertilizer-N application rate and yield for corn and sugar beet. It was hypothesized that canopy reflectance would change with increasing fertilizer-N application rates. The objectives of this study were (i) to determine the crop yield and quality in response to fertilizer application rates at two field sites, (ii) map vegetation indices of the experimental plots using drone-based optical sensors, and (iii) calibration of vegetation indices with crop yield. During 2017 and 2018 growing seasons, field trials were conducted to determine corn and sugar beet response to fertilizer-N application rates. In general, the use of optical sensors for quantitative and qualitative relationships were greater after the V6 growth stage in both corn and sugar beet. Early season moisture deficiency, disease, and crop size could impact the quality of the optical sensing data collection. 2019-07-03T19:23:23Z 2019-07-03T19:23:23Z 2019 text/thesis https://hdl.handle.net/10365/29887 NDSU policy 190.6.2 https://www.ndsu.edu/fileadmin/policy/190.pdf application/pdf North Dakota State University
collection NDLTD
format Others
sources NDLTD
description The main goal of this study was to calibrate small unmanned aircraft system (SUAS) based vegetation indices with fertilizer-N application rate and yield for corn and sugar beet. It was hypothesized that canopy reflectance would change with increasing fertilizer-N application rates. The objectives of this study were (i) to determine the crop yield and quality in response to fertilizer application rates at two field sites, (ii) map vegetation indices of the experimental plots using drone-based optical sensors, and (iii) calibration of vegetation indices with crop yield. During 2017 and 2018 growing seasons, field trials were conducted to determine corn and sugar beet response to fertilizer-N application rates. In general, the use of optical sensors for quantitative and qualitative relationships were greater after the V6 growth stage in both corn and sugar beet. Early season moisture deficiency, disease, and crop size could impact the quality of the optical sensing data collection.
author Olson, Daniel O.
spellingShingle Olson, Daniel O.
Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
author_facet Olson, Daniel O.
author_sort Olson, Daniel O.
title Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
title_short Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
title_full Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
title_fullStr Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
title_full_unstemmed Relationship of Vegetation Indices from Drone-Based Passive Optical Sensors with Corn Grain Yield and Sugar Beet Root Yield and Quality
title_sort relationship of vegetation indices from drone-based passive optical sensors with corn grain yield and sugar beet root yield and quality
publisher North Dakota State University
publishDate 2019
url https://hdl.handle.net/10365/29887
work_keys_str_mv AT olsondanielo relationshipofvegetationindicesfromdronebasedpassiveopticalsensorswithcorngrainyieldandsugarbeetrootyieldandquality
_version_ 1719485478619578368