Use of Leaf Spectral Ratio Indices to Estimate Leaf Relative Water Content of Beetroot Under CO_2 Leakage Stress

摘要

To reduce global warming by excessive CO_2 emission, carbon capture and storage (CCS) techniques have been proposed to reduce atmospheric CO_2 and mitigate climate change. However, there is some possible risk of leakage when CO_2 is stored underground. Any large quantities of leaked CO_2 in the soil will induce plant stress such as chlorosis of the leaves and poor development of the plants. The objective of this paper is to estimate the leaf relative water content (RWC) of beetroot under CO_2 leakage stress by using hyperspectral remote sensing. A field experiment was carried out from May to September 2008 at the Sutton Bonington campus of the University of Nottingham (52.8° N, 1.2° W). Individual leaf reflectance spectra and RWC were measured every week in the laboratory to collect a total of 69 spectra and RWC values. Some ratio indices were selected to retrieve the beetroot RWC. The results indicate that the linear model with the reflectance ratio index R_(1100)/R_(1300) as the independent variable had the highest precision of estimation; the absolute estimation error is 1.48, and the relative error is 1.70%; The next best were the indices R_(1070)/R_(1200) and R_(1148)/R_(1088) where the linear model absolute estimation errors were 1.78 and 1.77, respectively, and the relative errors both 2.0%. Ratio indices in the near-infrared range can therefore be used to estimate the plants RWC. This study not only provides a method for estimation of biophysical and biochemical parameters of plants, but also could be used in precision agriculture and CCS leakage safety monitoring utilizing hyperspectral data.