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Plant functional traits; Reflectance Spectroscopy; Partial Least Square Regression (PLSR); Support Vector Machine (SVM); Foliar Traits; Woody Plants
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Validation And Optimization Of Hyperspectral Reflectance Analysis-Based Predictive Models For The Determination Of Plant Functional Traits In Cornus, Rhododendron, And Salix, Milton I. Valdiviezo
Validation And Optimization Of Hyperspectral Reflectance Analysis-Based Predictive Models For The Determination Of Plant Functional Traits In Cornus, Rhododendron, And Salix, Milton I. Valdiviezo
Honors Undergraduate Theses
Near infrared spectroscopy (NIR) has become increasingly widespread throughout various fields as an alternative method for efficiently phenotyping crops and plants at rates unparalleled by conventional means. With growing reliability, the convergence of NIR spectroscopy and modern machine learning represent a promising methodology offering unprecedented access to rapid, high throughput phenotyping at negligible costs, representing prospects that excite agronomists and plant physiologists alike. However, as is true of all emergent methodologies, progressive refinement towards optimization exposes potential flaws and raises questions, one of which is the cornerstone of this study. Spectroscopic determination of plant functional traits utilizes plants' morphological and …