| 李燕,杨可明,王敏,程凤,高鹏,张超.铜胁迫下玉米光谱变化的奇异性诊断指数与污染甄别[J].农业环境科学学报,2019,38(1):14-21. |
| 铜胁迫下玉米光谱变化的奇异性诊断指数与污染甄别 |
| Singularity diagnostic index pollution identification of corn spectral variations under copper stress |
| 投稿时间：2018-04-16 |
| DOI：10.11654/jaes.2018-0501 |
| 中文关键词: 玉米铜污染 光谱时频特征分析 奇异性诊断指数 奇异性 |
| 英文关键词: copper contamination spectral time-frequency feature analysis singular diagnostic index singularity |
| 基金项目:国家自然科学基金项目（41271436）；中央高校基本科研业务费专项资金项目（2009QD02） |
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| 摘要点击次数: 2099 |
| 全文下载次数: 1822 |
| 中文摘要: |
| 通过研究不同程度铜污染胁迫下玉米光谱奇异性变化特征来诊断玉米受Cu2+污染程度。通过设置不同铜胁迫浓度下的玉米盆栽实验，根据实测的SVC高光谱数据和Cu2+含量数据，采用经验模态分解（EMD）与小波变换相结合的方法提取玉米光谱奇异信息，并构建奇异性诊断指数对玉米光谱奇异性进行定性分析，从而实现玉米铜污染程度的甄别。同时与常规的绿峰高度、红边最大值、红边一阶微分包围面积等植被重金属污染信息监测方法进行比较来验证该方法的有效性。结果显示：奇异性诊断指数（SI）与玉米叶片中Cu2+含量存在较强的相关关系，SI随叶片中Cu2+含量的增加而增大，其相关系数达到0.972 4，从而证明光谱奇异性诊断指数能有效地诊断叶片光谱的奇异性变化及其污染程度，为作物重金属污染监测提供参考依据。 |
| 英文摘要: |
| The aim of this study is to detect the stress levels of corn under different levels of Cu2+ pollution by analyzing the characteristics of hyperspectral singularity variations. By setting the potted corn experiment for stress via different concentration gradients of Cu2+ and based on the measured SVC hyperspectral data and Cu2+ concentration, corn spectral singular information was extracted with a method that combined empirical mode decomposition(EMD) and wavelet transform. The singular diagnostic index(SI) was used to indicate the corn hyperspectral singularity variations in order to screen the corn pollution level. Meanwhile, the proposed method was verified as valid compared to the conventional monitoring methods of vegetation heavy metal pollution information such as green-peak height, red edge maximum, and first derivative area of the red edge. The results showed a strong correlation between the singular diagnostic index and copper content of corn leaves. The singular diagnostic index increased with the content of Cu2+ in corn leaves. Furthermore, the correlation coefficient reached 0.972 4, which proves that the singular diagnostic index could be used to diagnose the stress levels of maize under Cu2+ pollution conditions effectively. This study provides a reference for monitoring the heavy metal pollution of crops. |
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