Hyperspectral time series datasets of maize during the grain filling period

Remotely sensed hyperspectral data are increasingly being used to assess crop development and growth throughout the growing season. Large datasets capturing key growth stages can be useful to researchers studying many physiological plant responses. This dataset represents a time series analysis of hyperspectral reflectance measurements taken during the grain filling period across two growing years, two planting dates and 16 maize hybrids. These datasets show how canopy reflectance within the visible and near-infrared portion of the electromagnetic spectrum change as plants approach, reach, and pass physiological maturity.