51. Feasibility of Using Rice Leaves Hyperspectral Data to Estimate CaCl2-extractable Concentrations of Heavy Metals in Agricultural Soil
- Author
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Weihong Zhou, Ying Liu, Xiaolong Du, Yangyang Liu, Mengmeng Zou, Qian Wang, Jingjing Zhang, Xiaoqing Liu, and Jianlong Li
- Subjects
021110 strategic, defence & security studies ,Cadmium ,Multidisciplinary ,Oryza sativa ,Soil test ,lcsh:R ,0211 other engineering and technologies ,chemistry.chemical_element ,food and beverages ,lcsh:Medicine ,02 engineering and technology ,010501 environmental sciences ,Photochemical Reflectance Index ,01 natural sciences ,Normalized Difference Vegetation Index ,Bioavailability ,Crop ,chemistry.chemical_compound ,chemistry ,Environmental chemistry ,Chlorophyll ,Environmental science ,lcsh:Q ,lcsh:Science ,0105 earth and related environmental sciences - Abstract
Heavy metals contamination is a serious problem of China. It is necessary to estimate bioavailability concentrations of heavy metals in agricultural soil for keeping the food security and human health. This study aimed to use hyperspectral data of rice (Oryza sativa) leaves as an indicator to retrieve the CaCl2-extractable concentrations of heavy metals in agricultural soil. Twenty-one rice samples, soil samples and reflectance spectra of rice leaves were collected, respectively. The potential relations between hyperspectral data and CaCl2-extractable heavy metals (E-HM) were explored. The partial least-squares regression (PLSR) method with leave-one-out cross-validation has been used to predict concentrations of CaCl2-extractable cadmium (E-Cd) and concentrations of CaCl2-extractable lead (E-Pb) in farmland soil. The results showed that the concentrations of E-Cd in soil had significant correlation with concentrations of Cd in rice leaves; the number of bands associated with E-Cd was more than that of E-Pb. Four indices (normalized difference vegetation index (NDVI), carotenoid reflectance index (CRI), photochemical reflectance index 2 (PRI2), normalized pigments chlorophyll ratio index (NPCI)) were significant (P R2 = 0.592 and RMSE = 0.046. We conclude that if the rice was sensitive to E-HM and/or the crop was stressed by the E-HM, the hyperspectral data of field rice leaves hold potentials in estimating concentration of E-HM in farmland soil. Therefore, this method provides a new insight to monitoring the E-HM content in agricultural soil.
- Published
- 2019