Earlier Detection of Rice Blast Through a Physiological Signal Derived from Sun-induced Chlorophyll Fluorescence.

Rice blast is one of the major diseases in rice causing significant rice yield reduction. To prevent its widespread dispersal and mitigate impacts on rice yield, earlier detection is key. Sun-induced chlorophyll fluorescence (SIF) has shown the potential for quantifying plant stress earlier than conventional remote sensing approaches and might contribute to disease detection and control. Particularly, recent investigations showed that a physiological signal obtained from SIF (i.e., physiological SIF yield, ΦF) can be even more highly indicative of plant physiological status than SIF. Unlike other environmental stressors, however, rice blast causes a fatal impact in a much shorter period, and whether the rice blast detection by SIF can be sufficiently earlier than visual confirmation or conventional vegetation indices for improved disease control is yet to be investigated. This study aims to assess the detection of rice blast using SIF compared to visual assessment and conventional vegetation indices in a non-flooded rice field. Specifically, we built a portable field spectroscopic system to effectively collect spectral reflectance (400 - 900 nm) and spectral radiance data (630 - 800 nm) for vegetation indices and SIF retrieval, respectively. To better detect the physiological impacts of rice blast, we calculate and analyze ΦF, which is obtained as the ratio of SIF to a product of photosynthetically active radiation and near-infrared reflectance of vegetation. This study will contribute to the earlier detection of rice blast infection and more effective disease control in crops and improve our understanding of rice blast progression and its impact on crop physiology.