High-throughput phenotyping (HTP) has the potential to revolutionize plant breeding by providing scientists with exponentially more data than was available through traditional observations. Even though data collection is rapidly increasing, the optimum use of this data and implementation in the breeding program has not been thoroughly explored. In an effort to apply HTP to the earliest stages of a plant breeding program, we extended field-based HTP pipelines to evaluate and extract data from spaced single plants. Using a panel of 340 winter wheat (Triticum aestivum L.) lines planted in full plots and grid-spaced single plants for two growing seasons, we evaluated relationships between single plants and full plot yields. Normalized difference vegetation index (NDVI) was collected multiple times through the growing season using an unoccupied aerial vehicle. NDVI measurements during grain filling stage from both single plants and full plots were typically positively associated with their respective grain yield with correlation ranging from -0.22 to 0.74. The relationship between single plant NDVI and full plot yield, however, was variable between seasons ranging from -0.40 to 0.06. A genome wide association analysis (GWAS) identified the same marker trait associations in both full plots and single plants, but also displayed variability between growing seasons. Strong genotype by environment interactions could impede selection on quantitative traits, yet these methods could provide an effective tool for plant breeding programs to quickly screen early-generation germplasm. Efficient use of early-generation, affordable HTP data could improve overall genetic gain in plant breeding.