School of Life Sciences, Nanjing University, Xianlin Road 163, Nanjing, 210000, People's Republic of China.
Suzhou Institute of Technology, Jiangsu University of Science and Technology, Zhangjiagang, 215600, China.
Environ Sci Pollut Res Int. 2019 Jan;26(2):1848-1856. doi: 10.1007/s11356-018-3745-9. Epub 2018 Nov 20.
Cadmium (Cd) contaminated rice has become a global food security issue. Hyperspectral remote sensing can do rapid and nondestructive monitoring of environmental stress in plant. To realize the nondestructive detection of Cd in brown rice before harvest, the leaf spectral reflectance of rice exposed to six different levels of Cd stress was measured during the whole life stages. In addition, the dry weight of rice grain and Cd concentrations in brown rice were measured after harvest. The impact of Cd stress on the quantity and the quality of rice grain and on the leaf reflectance of rice was analyzed, and hyperspectral estimation models for predicting the Cd content in brown rice during three growth stages were established. The results showed that rice plants can impact the quality of the brown rice seriously, even if the impact on the quantity was not significant. All the established models had the capability to estimate Cd concentrations in brown rice (R > 0.598), and the best performance model, with the R value of 0.873, was use first derivative spectrum of booting stage as variable. It was concluded that the hyperspectral of rice leaves provides a new insight to predict Cd concentration in brown rice before harvest.
镉（Cd）污染大米已成为全球食品安全问题。高光谱遥感可以快速、无损地监测植物的环境胁迫。为了实现在收获前对糙米中 Cd 的无损检测，在整个生长阶段测量了暴露于六种不同 Cd 胁迫水平下的水稻叶片光谱反射率。此外，还测量了收获后水稻籽粒的干重和糙米中的 Cd 浓度。分析了 Cd 胁迫对水稻籽粒数量和质量以及水稻叶片反射率的影响，并建立了三个生长阶段预测糙米中 Cd 含量的高光谱估算模型。结果表明，水稻植株即使对产量的影响不显著，也会严重影响糙米的质量。所有建立的模型都能够估计糙米中的 Cd 浓度（R>0.598），表现最好的模型，其 R 值为 0.873，使用抽穗期一阶导数光谱作为变量。结论认为，水稻叶片的高光谱为预测收获前糙米中的 Cd 浓度提供了新的见解。
