Relationship between photochemical efficiency of photosystem II and the photochemical reflectance index of mango tree: merging data from different illuminations, seasons and leaf colors

Abstract

In order to elucidate the effects of chlorophyll concentration and seasonal temperature on the relationship between photosystem II (PSII) efficiency and the photochemical reflectance index (PRI) of leaves under different light intensity, mango (Mangifera indica), a low-temperature-sensitive species, was used for the study. From early winter to summer, we selected several days to measure chlorophyll fluorescence and leaf spectral reflectance of mango leaves with dark green to yellow green colors, under natural sunlight from predawn to sunset and under six levels (0, 200, 400, 800, 1200 and 2000 mumol m(-2) s(-1)) of artificial illumination. When leaves were exposed to light, both PRI and PSII efficiency decreased with the increase in illumination, yet the PSII efficiency-PRI relationship varied with temperature and leaf color. Both predawn PRI and the X-intercept of the PSII efficiency-PRI regression equations were higher in dark green leaves and on the day with higher minimum air temperature, and lower on opposite conditions. These were due to the influence of chlorophyll on the reflection of wavebands for detecting PRI, and leaves retained a higher degree of epoxidation state of xanthophyll cycle pigments in cold predawn. Therefore, when data obtained at different seasons and with different leaf colors were pooled for analysis, PRI was not closely related to PSII efficiency. Yet, either in the darkness of predawn or under a given level of illumination, PSII efficiency always showed a significant positive correlation with PRI, with data from different leaf colors and seasons merged for statistics analysis. Because both the intercept and slope of the PSII efficiency-PRI equation showed a negative regression with photosynthetic photon flux (PPF), an empirical regression model, i.e., PSII efficiency = c + d . PPF + e . (PPF)(2) + f . PRI + g . PPF . PRI, could be fitted for multiple regression analysis. Based on the close correlation between the estimated and measured PSII efficiency (r(2) = 0.844-0.907, P < 0.001), using dynamic data obtained from leaves with yellow green to dark green colors, measurement was taken at predawn (F(v)/F(m)) and under any given strength of sunlight and artificial illumination (DeltaF/F(m)') through different seasons. We, thus, concluded that this empirical regression model could simulate both the seasonal and diurnal variations of PSII efficiency.