Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China.
Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing 100083, China; Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affffairs, China Agricultural University, Beijing 100083, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Oct 5;259:119768. doi: 10.1016/j.saa.2021.119768. Epub 2021 Apr 2.
The tuber development and nutrient transportation of potato crops are closely related to canopy photosynthesis dynamics. Chlorophyll fluorescence parameters of photosystem II, especially the maximum quantum yield of primary photochemistry (Fv/Fm), are intrinsic indicators for plant photosynthesis. Rapid detection of Fv/Fm of leaves by spectroscopy method instead of time-consuming pulse amplitude modulation technique could help to indicate potato development dynamics and guide field management. Accordingly, this study aims to extract fluorescence signals from hyperspectral reflectance to detect Fv/Fm. Hyperspectral imaging system and closed chlorophyll fluorescence imaging system were applied to collect the spectral data and values of Fv/Fm of 176 samples. The spectral data were decomposed by continuous wavelet transform (CWT) to obtain wavelet coefficients (WFs). Three mother wavelet functions including second derivative of Gaussian (gaus2), biorthogonal 3.3 (bior3.3) and reverse biorthogonal 3.3 (rbio3.3) were compared and the bior3.3 showed the best correlation with Fv/Fm. Two variable selection algorithms were used to select sensitive WFs of Fv/Fm including Monte Carlo uninformative variables elimination (MC-UVE) algorithm and random frog (RF) algorithm. Then the partial least squares (PLS) regression was used to establish detection models, which were labeled as bior3.3-MC-UVE-PLS and bior3.3-RF-PLS, respectively. The determination coefficients of prediction set of bior3.3-MC-UVE-PLS and bior3.3-RF-PLS were 0.8071 and 0.8218, respectively, and the root mean square errors of prediction set were 0.0181 and 0.0174, respectively. The bior3.3-RF-PLS had the best detection performance and the corresponding WFs were mainly distributed in the bands affected by fluorescence emission (650-800 nm), chlorophyll absorption and reflection. Overall, this study demonstrated the potential of CWT in fluorescence signals extraction and can serve as a guide in the quick detection of chlorophyll fluorescence parameters.
块茎发育和养分运输与马铃薯作物冠层光合作用动态密切相关。光系统 II 的叶绿素荧光参数，特别是原初光化学量子产量（Fv/Fm），是植物光合作用的固有指标。通过光谱法而非耗时的脉冲振幅调制技术快速检测叶片的 Fv/Fm 有助于指示马铃薯发育动态并指导田间管理。因此，本研究旨在从高光谱反射率中提取荧光信号来检测 Fv/Fm。应用高光谱成像系统和密闭叶绿素荧光成像系统采集 176 个样本的光谱数据和 Fv/Fm 值。采用连续小波变换（CWT）对光谱数据进行分解，得到小波系数（WFs）。对比了包括高斯二阶导数（gaus2）、双正交 3.3（bior3.3）和逆双正交 3.3（rbio3.3）在内的三种母小波函数，结果表明 bior3.3 与 Fv/Fm 相关性最好。采用蒙特卡罗无信息变量消除（MC-UVE）算法和随机蛙（RF）算法两种变量选择算法筛选与 Fv/Fm 相关的敏感 WFs，分别建立偏最小二乘（PLS）回归检测模型，记为 bior3.3-MC-UVE-PLS 和 bior3.3-RF-PLS。bior3.3-MC-UVE-PLS 和 bior3.3-RF-PLS 预测集的决定系数分别为 0.8071 和 0.8218，预测集的均方根误差分别为 0.0181 和 0.0174。bior3.3-RF-PLS 具有最佳的检测性能，对应的 WFs 主要分布在受荧光发射（650-800nm）、叶绿素吸收和反射影响的波段。总体而言，本研究证明了 CWT 在荧光信号提取中的潜力，可为快速检测叶绿素荧光参数提供指导。
