【摘要】 为探究重金属胁迫下农作物污染响应的敏感叶型及谱段，设计了室外温室环境下的不同铜胁迫梯度玉米花盆试验。以玉米叶片为探究对象，利用仪器测定了出穂期玉米叶片的高光谱反射率数据以及叶片中重金属含量数据，为研究提供了基础数据。从频率域角度，结合时频分析的方法设计了叶片光谱探测法(LSDM),获得了重金属铜胁迫下敏感叶型及谱段，为农作物重金属监测提供技术支撑。根据玉米的生长过程，从老叶(O)、中叶(M)、新叶(N)光谱350～1 300 nm的全谱段和子谱段角度进行探究。(1)对铜胁迫下玉米叶片的高光谱反射率数据进行双微分(SOD)和包络线移除(CR),转换到频率域上，结合时频分析的方法进行Daubechies小波6层分解。(2)根据信号异常点、小波高值点和SODCR曲线高值点，定义玉米叶片的光谱异常参数(SAP)。异常变化反射率ACR(异常反射率与其后一个相邻波段反射率差值的绝对值);异常小波系数AWC(异常小波系数与其后一个相邻波段小波系数差值的绝对值);异常SODCR值ASV(异常点SODCR值与其后一个相邻波段SODCR值差值的绝对值)。通过光谱异常参数与玉米叶片重金属含量的相关关系，探究对铜污染响应敏感的叶型及谱段。结果表明，叶片光谱探测法LSDM能高效地对玉米叶片弱信息进行增强，并准确定位出重金属铜胁迫引起的光谱异常谱段位置，异常变化范围集中在350～800 nm内；光谱异常参数能定量地衡量玉米叶片在重金属铜胁迫下的光谱异常；在不同铜胁迫梯度下，玉米新叶(N)为敏感叶型，敏感谱段为蓝边、绿峰、黄边、红谷。该研究有望为其他谷类农作物及其冠层尺度重金属监测提供技术支撑。更多还原

【Abstract】 A maize pot experiment with different copper stress gradients was designed in an outdoor greenhouse to explore the sensitive leaf types and spectral ranges of crop pollution response under heavy metal stress. Taking maize leaves as the research object, the hyperspectral reflectance data and heavy metal content data of maize leaves during the heading period were measured using instruments, providing basic data for research. This paper designed the Leaf Spectral Detection Method(LSDM) from the frequency domain perspective, combined with time-frequency analysis, to obtain sensitive leaf shapes and spectral bands under heavy metal copper stress, providing technical support for heavy metal monitoring in crops. Based on the growth process of maize, this study explores the full spectrum and sub-spectrum of the old leaf(O), middle leaf(M), and new leaf(N) spectra from 350 to 1 300 nm. Firstly, the hyperspectral reflectance data of maize leaves under copper stress were subjected to double differentiation(SOD) and envelope removal(CR) and transformed into the frequency domain. The Daubechies wavelet 6-layer decomposition was performed using time-frequency analysis methods. Then, based on the signal anomaly points, wavelet high-value points, and SODCR curve high-value points, the spectral anomaly parameters SAP(Spectral Anomaly Parameters) of maize leaves are defined, namely: Abnormal Changes Reflectivity(ACR), which is the absolute value of the difference between the abnormal reflectance and the reflectance of the next adjacent band; Abnormal Wavelet Coefficients(AWC), which is the absolute value of the difference between the abnormal wavelet coefficients and the wavelet coefficients of the next adjacent band; Abnormal SODCR value(ASR), which is the absolute value of the difference between the abnormal point SODCR value and the SODCR value of the next adjacent band. Finally, by examining the correlation between spectral anomaly parameters and heavy metal content in maize leaves, we aim to explore the leaf types and spectral segments sensitive to copper pollution. The results showed that the leaf spectral detection method LSDM can efficiently enhance weak information in maize leaves and accurately locate the spectral anomaly caused by heavy metal copper stress, with the anomaly range concentrated within 350 to 800 nm; Spectral anomaly parameters can quantitatively measure the spectral anomalies of maize leaves under heavy metal copper stress; Under different copper stress gradients, maize new leaves(N) exhibit sensitive leaf types, with sensitive spectral segments including blue edges, green peaks, yellow edges, and red valleys. This paper can provide technical support for monitoring heavy metals in other cereal crops and their canopy scales.更多还原