Evaluation of Vegetative Indices to Determine Canopy Ground Cover for Winter Survival and Hybrid Necrosis in Winter Wheat

Authors

Micheal Young, University of Nebraska-LincolnFollow

First Advisor

Stephen Baenziger

Date of this Version

12-2023

Document Type

Thesis

Citation

A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science

Major: Agronomy

Under the supervision of Professor Stephen Baenziger

Lincoln, Nebraska, December 2023

Comments

Copyright 2023, Micheal Young

Abstract

The benefit of unmanned aircraft systems and image processing methods in agronomic research across numerous crops has been well documented as has the importance of wheat, Triticum aestivum L., on the global food supply. Hence there is great interest in digital solutions applied to aspects of wheat breeding. A major trait of importance to winter wheat breeders in higher latitudes is winter survival, which can result in poor yield and performance if lines do not survive extreme cold. Scoring winter survival is most commonly based on visual score of 0% to 100% with the higher percentage conveying higher winter survival rates. With the increased interest in hybrid wheat lines, it has brought an increased need to screen for hybrid necrotic lines in the field. With both hybrid necrosis and winter kill reducing the stand count of a plot, the advantageous situation arose to be able to investigate digital solutions of measuring wheat stand and their relationship with winter survival and hybrid necrosis. We were able to show that the utilization of multiple vegetative indices and segmentation indices derived from multispectral imagery within the same linear model was able to predict stand with a correlation of r = 0.836 (p < 0.01; flight date 5/18/2020) to visually scored plot stand data. Using unnormalized RGB model utilizing segmentation indices (an index that is used to separate vegetative pixels from background pixels) was able to achieve a prediction with a correlation of r = 0.924 (p < 0.01; flight date 5/18/2020) with the visually scored plot stand data, lending to the potential use of segmentation in conjunction with processes where RGB images are not normalized. In lines exhibiting symptoms of hybrid necrosis a clear clustering pattern could be observed as the season progressed for NDVI values of hybrid necrotic lines compared to non-necrotic lines.

Advisor: Stephen Baenziger