水稻锌污染胁迫的光谱奇异性分析

Analysis of hyperspectral singularity of rice under Zn pollution stress

通过研究锌污染胁迫下水稻的光谱奇异性特征来诊断水稻锌污染水平。根据试验区水稻各个生长期的ASD实测高光谱数据和同步获取的作物与农田土壤重金属含量2a田间试验数据,利用Daubechies小波系中的"Db5"小波函数对锌污染胁迫水稻的350～1300nm光谱波段进行5层小波分解,并利用奇异范围、奇异幅度和奇异指数等参数对水稻光谱奇异性进行定量计算与分析。结果表明,"Db5"小波函数分解的第5层小波系数能精准探测水稻光谱的奇异性,其奇异范围集中在480～850nm波段范围;奇异幅度从出苗期到分蘖期迅速增加,并达到最大值,在随后的分蘖期→拔节期→开花期→成熟期逐渐减少;奇异指数从出苗期→分蘖期→拔节期→开花期→成熟期逐渐增加;水稻叶片锌含量与奇异幅度及奇异指数之间存在较强的相关关系,其决定系数(R2)为0.8445,均方根误差(RMSE)为5.60。光谱奇异性能有效地诊断并定量分析水稻锌污染胁迫状况,从而为作物重金属污染胁迫监测提供重要参考。

The aim of this study is to detect the stress levels of rice under Zn pollution by analyzing the characteristics of hyperspectral singularity. Hyperspectral reflectance and heavy metal concentration from different growth stages of rice in two consecutive years were collected in the field experiment. Wavelet transform was performed to hyperspectral reflectance（350-1 300 nm） by using ＂Daubechies 5＂ wavelet function,and three categories of singularity parameters as indicators of hyperspectral singularity of rice under Zn stress were explored,including singularity range（SR） ,singularity amplitude（SA） and singularity exponent（SE） . The results showed that the wavelet coefficient of the fifth decomposition level of ＂Daubechies 5＂ wavelet function proved successful for accurately identifying the hyperspectral singularity of rice under Zn stress. SR of rice was concentrated on the region around 480-850 nm of spectral signal under Zn stress. Maximum value of SA occurred at the tillering stage,and the SA increased sharply from seeding stage to tillering stage and then decreased from jointing stage to anthesis stage and to mature stage,while the SE increased constantly from seeding stage to mature stage when rice was growing. Zn concentration in rice leaves had better linearity with the SA and SE with correlation coefficient（R2） of 0.8445 and root mean square error（RMSE） of 5.60. The hyperspectral singularity applying wavelet transform technique has been shown to indentify and quantitatively analyze the stress levels of rice under Zn pollution effectively and provide important reference for detecting other metal-induced stress on crop.