Modeling Leaf Image, Chlorophyll Fluorescence, Reflectance From SPAD Readings

Many remote sensing technologies were used to evaluate plant physioecology. However, few studies currently existed on the comparisons and the relationships among various remote sensing analyses methods. The objective of our study was to investigate the relationship of leaf image, chlorophyll fluorescence, reflectance with SPAD, and build the models from SPAD using the data obtained from rice and barley crops. Two pot experiments, one in 2009 and the other one in 2010, were conducted to study the relationship between these characteristics at a leaf scale. Three rice varieties (M17, M15, Xiushui 09) and three barley varieties (Hua 30, Zhepi 33, Zhexiu 12) were selected in our greenhouse experiment. The results showed that there was a highly significant relationship between R (red channel of the leaf image), G (green channel of the image), R550 (reflectance at 550 nm), and PRI (photochemical reflectance index), with SPAD (SPAD-502 readings) for rice and barley crops. Close linear correlation was found between leaf chlorophyll maximal fluorescence (F_m) and ratio of variable to maximal chlorophyll fluorescence (F_m) with SPAD reading for rice. However, no significant relationship between F_m and F_v/F_m with SPAD reading was found in barley. Linear and logarithmic equations could be used to describe the relationship between R, G, R550, PRI, F_m, and F_v/F_m with SPAD reading. It suggested that leaf image analysis had stronger relationship with SPAD than reflectance or leaf chlorophyll fluorescence of the two crops of rice and barley.