Abstract

Induced defense responses in plants vary greatly among species, with many species exhibiting strong upregulation of secondary metabolites under attack by herbivores or pathogens. Secondary metabolite responses are most commonly analyzed using nuclear magnetic resonance or mass spectroscopy, though such approaches are costly and time-intensive. This study explores the use of hyperspectral reflectance as a more time- and cost-efficient method of detecting herbivore-induced secondary metabolite responses in plants. A diverse cross-section of wild sunflowers (genus Helianthus) were grown under controlled conditions and challenged with insect herbivory. Hyperspectral reflectance data was collected and analyzed using a principal component analysis in conjuncture with a support vector classification model to detect herbivore-induced versus control plants. The best model had a 93% accuracy rate at predicting whether a sample came from an induced or control plants when using data from all species tested. However, the changes in hyperspectral reflectance under herbivore induction varied greatly across species.

Thesis Completion

2018

Semester

Fall

Thesis Chair/Advisor

Bohlen, Patrick

Degree

Bachelor of Science (B.S.)

College

College of Sciences

Department

Biology

Location

Orlando (Main) Campus

Language

English

Access Status

Open Access

Release Date

12-1-2018

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