Estimation of the rice aboveground biomass based on the first derivative spectrum and Boruta algorithm - Nian, Ying; Su, Xiangxiang; Yue, Hu; Zhu, Yongji; Li, Jun; Wang, Weiqiang; Sheng, Yali; Ma, Qiang; Liu, Jikai; Li, Xinwei (Frontiers in Plant Science, 2024)
Aboveground biomass (AGB) is regarded as a critical variable in monitoring crop growth and yield.The use of hyperspectral remote sensing has emerged as a viable method for the rapid and precise monitoring of AGB. Due to the extensive dimensionality and volume of hyperspectral data, it is crucial to effectively reduce data dimensionality and select sensitive spectral features to enhance the accuracy of rice AGB estimation models. At present, derivative transform and feature selection algorithms have become important means to solve this problem. However, few studies have systematically evaluated the impact of derivative spectrum combined with feature selection algorithm on rice AGB estimation. To this end, at the Xiaogang Village (Chuzhou City, China) Experimental Base in 2020, this study used an ASD FieldSpec handheld 2 ground spectrometer (Analytical Spectroscopy Devices, Boulder, Colorado, USA) to obtain canopy spectral data at the critical growth stage (tillering, jointing, booting, heading, and maturity stages) of rice, and evaluated the performance of the recursive feature elimination (RFE) and Boruta feature selection algorithm through partial least squares regression (PLSR), principal component regression (PCR), support vector machine (SVM) and ridge regression (RR). Moreover, we analyzed the importance of the optimal derivative spectrum. The findings indicate that (1) as the growth stage progresses, the correlation between rice canopy spectrum and AGB shows a trend from high to low, among which the first derivative spectrum (FD) has the strongest correlation with AGB. (2) The number of feature of rice 删除[NY]: aboveground biomass 删除[NY]: Boruta algorithm 删除[NY]: ation 删除[NY]: the 删除[NY]: s 删除[NY]: spectra 删除[NY]: the first derivative spectrum (FD) has the strongest correlation with rice AGB.