Interested Members of the University Community are invited to attend the Final Oral Examination for the Degree of Master of Science of  Valerie Craig of the Department of Plant Agriculture 

Date: Wednesday, December 7th, 2022
Time: 3:00 pm
Location: CRSC 307 
Zoom link: https://zoom.us/j/95737115540?pwd=UmEwemtYRzJta01FcGVQWUQ4UU50UT09
Meeting ID: 957 3711 5540
Passcode: 310922 

Thesis Title: “Vegetation Index Development for High Throughput Detection of Maize (Zea mays L.) Black Layer “ 

Advisory Committee 
Dr. Elizabeth Lee (Advisor)
Dr. Hugh Earl
Dr. Aaron Berg
Dr. John Sulik

Examination Committee
Dr. Gale Bozzo, Chair
Dr. Joshua Nasielski
Dr. John Sulik
Dr. Elizabeth Lee                                    

ABSTRACT 

Maize black layer (BL) is the developmental stage where plants reach physiological maturity, which is a desirable trait, but phenotyping this trait is time consuming and costly. Any tool enabling high-throughput phenotyping of BL would be an invaluable asset for developing or maintaining short-season maize hybrids. This thesis investigated the potential of using remote sensing (RS) technologies to detect BL. The spectral signatures of 16 short-season maize hybrids were captured using a ground-based hyperspectral sensor through the late grain filling period (GFP) which were then used to develop and test vegetation indices (VIs) that correlated with BL formation. Two of these VIs, the normalized green red difference index (NGRDI) and the novel VI.5 were highly accurate, specific, and had spectral curves that match the physiology of maize in the late GFP. These findings suggest that high-throughput phenotyping of maize BL is possible using RS technologies. 

Publications: 

Craig, V., Earl, H., Sulik, J., & Lee, E.A. (2021). Hyperspectral time series datasets of maize during the grain filling period. Scholars Portal Dataverse. https://doi.org/10.5683/SP2/1ZVWFV

Hyperspectral time series datasets of maize during the grain filling period 

Craig, V., Earl, H., Sulik, J., & Lee, E.A. (2023).Vegetation Index Development for High Throughput Detection of Maize Black Layer. The Plant Phenome Journal. (To be published).