Novel Remote Sensing Index of Electron Transport Rate Predicts Primary Production and Crop Health in <i>L. sativa </i>and <i>Z. mays</i>

• Main Authors: Oded Liran, Ofer M. Shir, Shai Levy, Ariel Grunfeld, Yuval Shelly
• Format: Article
• Language: English
• Published: MDPI AG 2020-05-01
• Series: Remote Sensing
• Subjects: remote sensing; sun-induced fluorescence; photosynthesis; electron transport rate; vegetation indices; corn
• Online Access: https://www.mdpi.com/2072-4292/12/11/1718

Photosynthesis performance can be assessed quantitatively with light response curves. These curves record the Electron Transport Rate (ETR) as a function of light intensity. Then, statistical fit on these curves parameterize light use efficiency, maximum photosynthetic activity and the reaction of the apparatus to stress. While this technique is performed with portable fluorometers in field conditions, it is difficult to scale it to the canopy level. The Fraunhofer line discrimination technique, which detects fluorescence signals emitted during photosynthesis, is a promising method to assess photosynthetic performance of canopies. In this study, we define a remote sensing ETR index based on a combination of three parameters: sun-induced fluorescence, normalized differential vegetation index and light intensity. Two representatives of C₃ and C₄ photosynthesis, <i>L. sativa</i> and <i>Z. mays</i>, experienced a fertilization concentrations gradient. ETR increased with light intensity in both crops. In <i>L. sativa</i>, ETR assumed a linear relationship between the photosynthetic activity and light intensity, with a correlation of R² = 0.99 to the portable fluorometer. Additional parametrization revealed a resilience of its reaction centers to photoinhibition in maximum light intensities. When <i>Z. mays</i> experienced open field conditions, ETR correlated with the plant’s status. While the results of this study are promising, the index still requires validation in terms of temporal track and spatial variability.