基于高光谱图像的水稻叶片重金属交叉污染诊断:温室试验

Shuangyin Zhang, Teng Fei, Yanhong Ran
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引用次数: 4

摘要

本研究旨在探讨利用水稻植物高光谱图像快速诊断农业土壤中重金属铅、镉交叉污染的可行性。为了提高诊断准确率,采用了多种数据预处理方法。基于二阶导数谱带的SVM模型对无、低、中、高浓度应力的最佳诊断准确率均在75%以上。据我们所知,这是第一个利用高光谱图像识别铅和镉交叉污染的研究。结果表明,利用高光谱图像从水稻植株观测中诊断农业土壤中铅镉交叉污染是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosis of heavy metal cross contamination in leaf of rice based on hyperspectral image: a greenhouse experiment
The objective of this study was to explore the feasibility for rapid diagnosis of heavy metal Pb and Cd cross contamination in agricultural soil with hyperspectral image of rice plants. Several data pretreatment methods were applied to improve the diagnosis accuracy. The best diagnosis accuracy of SVM model were all above 75% for any none, low, medium and high concentration stress based on the spectral band of second derivative. To the best of our knowledge, this is the first study identifying Pb and Cd cross contamination by using hyperspectral images. The results indicates that it is feasible to diagnose the Pb and Cd cross contamination in agricultural soils from observation of rice plants using hyperspectral image.
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