Quantitative inversion of soil trace elements from spectroscopic effects across multiple crop growth periods

Abstract

Human health is directly impacted by trace components found in soil, for which hyperspectral remote sensing technology offers a novel way to rapidly assess dynamic soil environmental quality. In most studies, the premise of quantitative inversion on soil elements is that the known target elements will cause growth stress. However, such stress is unusual in non-polluted areas. Consequently, broad-area soil trace element monitoring in non-contaminated areas remains challenging. Spectral inversion of plant material has a longer time window and is more sensitive to elemental changes than soil spectral inversion (bare soil period). In this work, we conducted a wheat pot experiment with concentration gradients of four trace elements (Fe, B, Mo, and Zn), analyzed leaf (jointing stage) and spike (maturity period) samples using spectral measurements and chemical tests, and filtered the characteristic positions and inverse modeling using the spectra of the element-accumulating preference organs in plant canopies. The canopy aggregation sites differed for each element, and both simple linear regression (SLR) and multiple linear regression (MLR) models based on the spectra of canopy aggregation sites achieved high accuracy. The results of this study enable the construction of an inverse model of plant spectra-plant element content-elements in soil, which can serve as a reference for soil monitoring and assessment in typical crop cover areas.