Investigating novel sensing solutions is important for improving the existing phenotyping pipeline. Polarization is strongly correlated with the geometric properties of an object, such as surface roughness and its orientation relative to the sensor or light source. It has the potential to detect leaf wilting and quantify leaf angles in turfgrass, which are both crucial in precision turfgrass irrigation and crop coefficient determination. This study explores the integration of polarization imaging into RGB imaging pipelines for evaluating turfgrass responses to drought. A controlled dry-down was conducted on two zoysiagrass cultivars and two bermudagrass cultivars grown in pots. Polarization images, RGB images, and visual wilting ratings were collected daily during the four-day dry-down period. Leaf angles, both azimuth and zenith, were derived from top- and side-view RGB images, respectively. We analyzed polarization metrics, including the degree of linear polarization (DoLP) and the angle of polarization (AoP), to assess their relationship with drought stress indicators, such as wilting scores, low Excess Green Index (EGI) values, and changes in leaf angles. EGI and the standard deviation of AoP strongly correlated with wilting scores. Furthermore, DoLP values correlated with leaf zenith angle when the incident light angle was known.
