Time-Lapse Imaging Identifies Key Indicators of Brown Planthopper Damage Progression in Rice Varieties

Abstract

Improving complex agronomic traits such as yield, plant height, and disease resistance in rice (Oryza sativa L.) is challenging due to their polygenic nature. Conventional breeding methods, often reliant on collective parameters, face limitations in efficiently identifying superior genotypes. Phenomics, however, presents a promising, targeted approach by focusing on individual phenotypic traits. This study employs time-lapse imaging to monitor dynamic phenotypic changes in rice plants infested with the brown planthopper (BPH) (Nilaparvata lugens). Utilizing the Phlizon 6000 W LED Grow Light, which provides far-red wavelengths, and image acquisition with 12 Raspberry Pi 4 Model B units and Raspberry Pi NoIR cameras fitted with blue filters for enhanced NDVI calculations, we captured detailed imagery of plant responses. Our study revealed that NDVI values in the stem region of control plants remained stable, while leaf region values showed an increase. For infested plants, NDVI fluctuations were observed at the lamina joint in the stem region, whereas leaf region values remained consistent. Importantly, damage progression was slower at the lamina joint in resistant rice varieties compared to susceptible ones, underscoring lamina joint discoloration as a valuable parameter for evaluating BPH resistance. This phenome-based precision breeding approach holds significant potential for accelerating the development of rice varieties with enhanced resistance to this pervasive pest, offering new avenues for improving crop resilience and yield.