Identification of Disease Stress in Turfgrass Canopies Using Thermal Imagery and Automated Aerial Image Analysis

Remote sensing techniques are important for detecting disease within the turfgrass canopy. Herein, we look at two such techniques to assess their viability in detecting and isolating turfgrass diseases. First, thermal imagery is used to detect differences in canopy temperature associated with the onset of brown patch infection in tall fescue. Sixty-four newly seeded stands of tall fescue were arranged in a randomized block design with two runs with eight blocks each containing four inoculum concentrations within a greenhouse. Daily measurements were taken of the canopy and ambient temperature with a thermal camera. After five consecutive days differences were detected in canopy – ambient temperature in both runs (p=0.0015), which continued for the remainder of the experiment. Moreover, analysis of true colour imagery during this time yielded no significant differences between groups. A field study comparing canopy temperature of adjacent symptomatic and asymptomatic tall fescue and creeping bentgrass canopies showed differences as well (p<0.0492). The second project attempted to isolate spring dead spot from aerial imagery of bermudagrass golf course fairways using a Python script. Aerial images from unmanned aerial vehicle flights were collected from four fairways at Nicklaus Course of Bay Creek Resort in Cape Charles, VA. Accuracy of the code was measured by creating buffer zones around code generated points and measuring how many disease centers measured by hand were eclipsed. Accuracies measured as high as 97% while reducing coverage of the fairway by over 30% compared to broadcast applications. Point density maps of the hand and code points also appeared similar. These data provide evidence for new opportunities in remote turfgrass disease detection.

Name thesis:degree_name

Master of Science in Life Sciences

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Plant Pathology, Physiology and Weed Science

Department dc:contributor.department

Plant Pathology, Physiology and Weed Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2021

Author dc:creator

• Henderson, Caleb Aleksandr

Chair dc:contributor.committeechair

• McCall, David S.

Committee members dc:contributor.committeemember

• Haak, David C.
• Mehl, Hillary L.

• Turfgrass
• Remote Sensing
• Disease
• Thermal Imagery
• Aerial Imagery

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:31481

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/103621