Date of Award
8-1-2023
Language
English
Document Type
Master's Thesis
Degree Name
Master of Science (MS)
College/School/Department
Department of Chemistry
Dissertation/Thesis Chair
Igor K Lednev
Committee Members
Alan A Chen, Ting Wang
Keywords
ATR FT-IR Spectroscopy, Genetic Algorithm, PLS DA
Subject Categories
Chemistry
Abstract
Spectroscopic methods have recently been used to analyze plant species and maturation. However, there is a lack of research into employing spectroscopy for distinguishing living plant material and dead plant material, which is important for the agriculture and environmental health fields. Here in this study, we have shown the potential of ATR-FT IR (Attenuated total reflectance Fourier transformed infrared spectroscopy) to classify plant materials as living or dead through the help of multivariate statistical analysis methods. Plant samples were from the roots and needles of picea rubens, more commonly known as the red spruce tree. The samples were classified by creating a Partial Least Squares Discriminant Analysis model with the spectral features that were identified using a genetic algorithm. Classification of the roots of the red spruce tree into living and dead classes was done with 98% accuracy for the cross-validation of the calibration dataset and we achieved 100% accuracy for the classification of the root samples for the external validation dataset. The classification model achieved 100% accuracy in differentiating dead needles from living needles even after removing the water contribution of the IR spectrum.
Recommended Citation
Hoplight, Bailey Ann, "Distinguishing Between Living And Dead Plant Material From The Red Spruce Using Atr Ft-Ir Spectroscopy" (2023). Legacy Theses & Dissertations (2009 - 2024). 3151.
https://scholarsarchive.library.albany.edu/legacy-etd/3151
