Document Type
Thesis - Open Access
Award Date
2003
Degree Name
Master of Science (MS)
Department / School
Agricultural and Biosystems Engineering
First Advisor
Daniel S. Humburg
Abstract
Remote sensing was used to model crop quality from measurements of canopy spectra. Three indices of canopy characteristics, derived from satellite image data, were tested for relationship to whole-field sugarbeet quality. Quality was quantified as recoverable sucrose per ton of harvested sugarbeets. Quality data were extracted from the year 2002 Field Database of the Southern Minnesota Beet Sugar Co-operative, (SMBSC), Renville, Minnesota. Linear regression models utilizing canopy indices and changes in canopy indices over time were tested for relationship to sugarbeet quality for four classes of sugarbeets. Classes of sugarbeet tested represented fields planted to a mix of varieties resistant to the disease rhizomania, conventional varieties, and two pure strains. Linear regression models using individual indices for the fields planted to mixed conventional varieties and to a pure strain, B4811, showed statistical significance. Models using temporal changes in individual indices also showed statistical correlation. The trends of regression lines were meaningful in understanding variation of sugarbeet harvest quality with changes in canopy indices on two different single dates. Multiple linear regression models utilizing changes in individual indices over different time intervals also indicated significant correlations for a mixed conventional class and the B4811 variety. The trends in indices over time suggest that fields showing greater decline in indices can be classified as having higher recoverable sucrose content. The study suggests remotely sensed canopy spectral variations using satellite images, and sugarbeet quality variation may be used to develop models to relate quality to canopy indices. However, a larger sample size may be necessary, and additional information regarding fields with pronounced disease or population problems will be necessary to minimize scatter in the data used to develop models.
Library of Congress Subject Headings
Sugar beet -- Quality
Plant canopies -- Remote sensing
Precision farming
Description
Includes bibliographical references (68-73)
Format
application/pdf
Number of Pages
87
Publisher
South Dakota State University
Rights
Copyright © 2003 Subodh Kulkarni. All rights reserved
Recommended Citation
Kulkarni, Subodh, "Modeling Sugarbeet Quality Variables from Satellite Images and Canopy Spectral Indices" (2003). Electronic Theses and Dissertations. 622.
https://openprairie.sdstate.edu/etd/622