Back to results

University of Illinois at Urbana-Champaign

Evaluation of Sensing and Machine Vision Techniques in Stress Detection and Quality Evaluation of Turfgrass Species

Abstract

dc:description

The utility of different image sensing and non-image sensing techniques was also studied in objectively evaluating turfgrass quality parameters like, color, density and texture from National Turfgrass Evaluation Program trials. Image sensing took the greatest amount of time, while non-image sensing techniques were the fastest among the evaluated methods. All methods showed significant differences in cultivars for color in different trials. The quantified hue values from the multispectral camera were the least correlated with other evaluation techniques. Both chlorophyll meter and turf color meter showed potential in quantifying turfgrass color with greater consistency. However, the narrow separation obtained using turf color meter may not allow cultivar differentiation from species with less genetic color variation. Texture evaluation of turfgrasses was done after developing and implementing the run length encoding algorithm (RLE) on simulated turf built using twist ties in both planar and turf-type arrangements. Significant relationship was observed between manual measurements of twist ties and RLE-derived values. The algorithm implementation on true turfgrass images collected under greenhouse and field conditions from Kentucky bluegrass showed significantly positive relationship between RLE values and visual evaluation ratings. The possibility of collecting and analyzing images from multiple plots for color quantification was also evaluated successfully using an elevated platform from both Kentucky bluegrass and fairway bentgrass trials.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Natural Resrouces and Environmental Sciences
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Narra, Siddhartha
Contributors dc:contributor
  • Fermanian, Thomas W.

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI3290329
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/83121

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Narra, Siddhartha. Evaluation of Sensing and Machine Vision Techniques in Stress Detection and Quality Evaluation of Turfgrass Species. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/83121