Steve is a doctoral candidate in Plant breeding at Texas A&M University in College Station, Texas. He has worked in the Maize Breeding and Quantitative Genetics program under Dr. Seth Murray since 2014. Steven received his B.S. in Biology from the University of Central Florida in 2013 with a minor focus in Chemistry. He received his M.S. in Plant Breeding at Texas A&M University in 2016. Steve's MS research focused on understanding the effect of advance mating designs on linkage disequilibrium and mapping quantitative traits (doi: 10.3835/plantgenome2017.11.0102). Additionally he worked on developing proof of concept protocols for the proposed cycling of gametes in vitro (doi:10.1038/nbt.2710).
As a Plant Breeding doctoral candidate, Steve focuses on the implementation of unmanned aerial systems within a field based breeding program. He is currently a Tom Slick Senior Graduate Fellow within the College of Agriculture and Life Sciences at Texas A&M University. His research focuses on the use unmanned aerial systems in gathering temporal data sets on maize height growth. He is using temporal maize height as a proof of concept phenotype to identify the strengths of weakness that accompany the evaluation of field based agriculture setting at a research plot level. Steve is interested in leveraging such temporal data sets to understand differential marker trait association through out maizes life cycle to better understand the underlying genetic regulation of maize growth.
Research Areas: Genomics, Phenomics, Applied Plant Biology, Computational Biology, Environmental Plant Biology, Genetics
- Anderson, S.L., Murray, S.C., Malambo, L., Ratcliff, C., Popescu, S., Cope, D., Jung, J., Chang, A., and Thomasson, A. (In prep). Prediction of Maize Grain Yield Before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems. The Plant Phenome (Target Journal).
- Anderson, S. L., Mahan, A. L., Murray, S. C., & Klein, P. E. (2018). Four Parent Maize (FPM) Population: Effects of Mating Designs on Linkage Disequilibrium and Mapping Quantitative Traits. The Plant Genome. doi: 10.3835/plantgenome2017.11.0102.