Diagnosis of Invisible Photosynthetic Injury Caused by a Herbicide (Basta) with Chlorophyll Fluorescence Imaging System

Chlorophyll fluorescence imaging is a powerful tool in obtaining physiological information on plant leaf in non-destructive and non-invasive ways. Effects of Basta, one of the most popular commercially available foliar application-type herbicides, on in situ kidney bean leaf was analyzed with a developed chlorophyll fluorescence imaging system. Immediately after the Basta treatment, CO2 assimilation rate and ΦPSΙΙ, which represents the photochemical yield of photosystem ΙΙ, decreased and NPQ, which represents the heat dissipation of absorbed light energy, increased in the treated area. A positive linear correlation was confirmed between assimilation rate and ΦPSΙΙ, while a negative linear correlation was confirmed between assimilation rate and NPQ. These results demonstrated that the early diagnosis of invisible photosynthetic injury caused by Basta was feasible and the chlorophyll fluorescence imaging can be used as a system for early detection of photosynthetic inhibition of growing plants caused by herbicides. [Keywords] chlorophyll fluorescence, CO2 assimilation rate, heat dissipation, photochemical yield of photosystem ΙΙ, photosynthetic injury Introduction In the controlled greenhouse and precision agriculture, the information on plant response and growth environments measured by sensors is used to achieve the optimization of the controlled system, increase in plant production and sustainable agriculture (Hashimoto et al., 1993, Sigrimis, 2001, De Baerdemaeker et al., 2001). Many studies have been done for the application of biotic information, obtained through non-destructive and non-invasive measuring methods, to diagnose invisible plant responses in the research field. Such an approach is called “Speaking Plant Approach (SPA)” (Hashimoto, 1989). In particular, imaging techniques, e.g. multior hyper-spectral image sensing, thermal image sensing, and fluorescence image sensing, have been intensively investigated for use in diagnosis because image information is the most intuitive, easily comprehensible, and provides copious amount of information (Omasa, 1990; Omasa et al., in press). Multior hyper-spectral image sensing measures the reflection spectrum from plants, which contains information on pigments and water status in plants (Myers, 1983; Omasa and Aiga, 1987; Omasa, 1990; Omasa, in press). Thermal image sensing measures surface temperature, which provides information on stomatal response and gas exchange (Omasa et al., 1981ab; Hashimoto et al., 1984; Omasa and Aiga, 1987; Omasa, 1990; Omasa and Croxdale, 1992; Jones, 1999; Omasa, 2002). Fluorescence image sensing is an active sensing technique, for example laser-induced fluorescence (LIF) imaging and chlorophyll fluorescence imaging (Omasa 1990; Lichtenthaler, 1996; Omasa, 1998, Govindjee and Nedbal, 2000; Kim et al., 2002; Omasa and Takayama, 2002). These sensing techniques provide