Improving SPAD spectral estimation accuracy of rice leaves by considering the effect of leaf water content

The spectral range <1,000 nm is commonly used for estimating the chlorophyll content of plants. However, the influence of the response band of leaf water content in the Short-Wave InfraRed on the chlorophyll estimate model is uncertain. We measured the Visible-Near InfraRed-Short Wave InfraRed spectral reflectance and SPAD values of rice (Oryza sativa L.) leaves at different growth stages. The vegetation indices (VIs), red edge positions (REPs), and spectral characteristic parameters (SCPs) were calculated. The correlation between the above parameters and SPAD was analyzed. The effects of chlorophyll and water content on the spectral reflectance absorption characteristics of rice leaves were analyzed by the PROSPECT model. SPAD spectral estimation models were established with different inputs using the Random Forest (RF) regression algorithm. Our results are described as follows: (a) The spectral reflectance after continuum removal of rice leaves was highly correlated with SPAD in 600-690, 720-760, 1,400-1,490, and 1,900-1,980 nm. (b) Compared with VIs and REPs, the SCPs after continuum removal including the Depth (D1) and Area (A1, A2) parameters had the highest correlation with SPAD. (c) By taking into account the influence of leaf water content (LWC), the accuracy of SPAD estimation may be enhanced. The RF SPAD estimate model with SCPs of all absorption valley as inputs performed the best. The findings reveal on the mechanism of the influence of LWC on the accuracy of chlorophyll spectra estimation. It provides technical support for estimating SPAD in rice leaves with high accuracy and for developing chlorophyll tachistoscopes.