Early frost detection in wheat using machine learning from vertical temperature distributions

Sayma Shammi, Dean Diepeveen, Sebastian Zander, Michael G. K. Jones, Ferdous Sohel

Abstract: Highlights•We demonstrate that vertical temperature gradient is an early indicator of frost.•The gradient is obtained from infrared thermal (IRT) images of in-field wheat crops.•IRT-based Machine learning (ML) model is used for frost detection.•Results show that ML can detect suspected frost night and the severity.•Highly accurate results indicate suitability for early & automatic frost detection.