光谱学与光谱分析, 2018, 38 (1): 212, 网络出版: 2018-01-30   

铜铅离子胁迫下玉米污染程度的光谱识别

Spectra Recognition of Corn Pollution Degree under Copper and Lead Ion Stress
作者单位
1 中国矿业大学(北京)地球科学与测绘工程学院, 北京 100083
2 安徽理工大学测绘学院, 安徽 淮南 232001
摘要
重金属铜离子(Cu2+)与铅离子(Pb2+)污染对玉米叶片光谱的影响微弱、 隐蔽而难于探测。 研究中设置不同浓度Cu2+, Pb2+胁迫的玉米盆栽实验, 测定了玉米叶片光谱、 叶片中Cu2+, Pb2+含量与叶绿素相对含量, 分析了Cu2+, Pb2+污染胁迫下玉米叶片光谱响应特征, 并选取480~670与670~750 nm范围来进行分析, 在光谱维中定义了光谱微分差信息熵指数与在频率域中通过谐波分析提取了前三次谐波振幅(c1, c2与c3)指数, 并用所定义的指数探测分别受Cu2+, Pb2+胁迫玉米叶片光谱微弱差异。 实验结果表明, 在480~670与670~750 nm范围内, 玉米叶片中重金属离子浓度越大, 其光谱微分差信息熵就越大; 在480~670 nm波段, 谐波分解后第一谐波振幅c1与第二谐波振幅c2可用于识别Cu2+, Pb2+污染程度; 在670~750 nm波段, 第一谐波振幅c1、 第二谐波振幅c2与第三谐波振幅c3可用于识别Cu2+污染程度, 而c2则可以识别Pb2+污染程度, 污染胁迫越大振幅越大。 在480~670与670~750 nm波段内, 光谱微分差信息熵与前三次谐波振幅可作为识别玉米受Cu2+, Pb2+污染胁迫程度的指数, 从光谱维与频率域两种维度来识别玉米受Cu2+, Pb2+胁迫程度的方法可行, 文中定义的两类指数可稳健、 可靠地探测与识别玉米受Cu2+, Pb2+影响所产生的光谱微弱差异, 研究结果对利用高光谱来探测植被受重金属污染胁迫程度具有一定的参考价值。
Abstract
The effect of heavy metals copper ion (Cu2+) and lead ion (Pb2+) on corn leaf spectra is weak, hidden and difficult to be detected. The corn pot experiment of different concentrations of Cu2+, Pb2+ stress is set. Corn leaf spectra, leaf Cu2+, Pb2+ content, and chlorophyll relative content were measured. The corn leaf spectra characteristic due to Cu2+, Pb2+ pollution stress was also analyzed, and then 480~670 and 670~750 nm bands were selected to be studied. The index of spectra derivative difference entropy and the first three times harmonic amplitudes (c1, c2 and c3) was defined, and then leaf spectra faint change was detected by use of the index. In the end, it was concluded that in 480~670 and 670~750 nm bands, corn leaf had the greater concentration of heavy metal ions and the greater of its corresponding spectra derivative difference entropy. In 480~670 nm bands, the harmonic amplitudes c1 and c2 can be used to identify the Cu2+, Pb2+ pollution degree; In the 670~750 nm bands, the harmonic amplitudes c1, c2 and c3 can be used to identify Cu2+ pollution level, and c2 can identify the Pb2+ pollution degree. The larger amplitude value meaned more serious pollution stress in 480~670 and 670~750 nm bands. The index of spectra differential difference entropy and harmonic amplitudes (c1, c2 and c3) can be used as identification corn pollution degree under Cu2+, Pb2+ stress. The method based on spectra and frequencey domain to identify corn pollution degree under Cu2+, Pb2+ stress was feasible. The index of spectra differential difference entropy and harmonic amplitudes (c1, c2 and c3) can be more robust and reliable in the detection and identification spectra weak differences of corn leaf affected by Cu2+, Pb2+, and the result has certain practical application value in identifying vegetation pollution degree under heavy metal on base of hyperspectral data.

郭辉, 杨可明, 张文文, 刘聪, 夏天. 铜铅离子胁迫下玉米污染程度的光谱识别[J]. 光谱学与光谱分析, 2018, 38(1): 212. GUO Hui, YANG Ke-ming, ZHANG Wen-wen, LIU Cong, XIA Tian. Spectra Recognition of Corn Pollution Degree under Copper and Lead Ion Stress[J]. Spectroscopy and Spectral Analysis, 2018, 38(1): 212.

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