クロロフィルa蛍光画像を用いた醸造用ブドウのべと病の初期病状の可視化の検討

抄録

Stable food production has become difficult due to global warming and abnormal weather patterns, and in the agricultural sector, damage caused by plant diseases has been increasing. To address the plant diseases, technologies involving unmanned aerial vehicles (UAVs) to monitor the growth status of plants are being investigated. However, when the initial disease symptoms of plants are small and light in color (e.g., downy mildew), it is difficult to detect the disease at sites such as trellis vineyards by simply having the UAV take aerial photographs. It is also necessary to evaluate grapevines from the side views in addition to the aerial view. Another challenge concerns how to obtain high-quality images during the daytime, because of the interference of backlight and excessive brightness from sunlight. To address these challenges, we have investigated a chlorophyll (Chl)a fluorescence imaging technique that allows imaging measurements at night by providing stable lighting. We hypothesized that this new technique could be used to clarify the state of impaired photosynthetic reactions caused by plant diseases. The present study was conducted to calculate and visualize the values of a photosynthetic function index (PFI) in grapevine images. We also evaluated the effectiveness of the proposed technique by comparing its results with those obtained using the conventional pulse amplitude modulation (PAM) fluorescence measurement method, which has been traditionally used for measuring Chla fluorescence. Our findings demonstrated the potential of the new technique using PFI images for visualizing diseased areas on trellis-grown plants.