Spaceborne imaging spectroscopy enables carbon trait estimation in cover cropand cash crop residues

Authors: Jennewein, Jyoti; HIVELY, DEAN - Us Geological Survey (USGS); LAMB, BRIAN - Us Geological Survey (USGS); Daughtry, Craig; THAPA, RESHAM - Tennessee State University; Thieme, Alison; REBERG-HORTON, CHRIS - North Carolina State University; Mirsky, Steven

Submitted to: Precision Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2024
Publication Date: 6/27/2024
Citation: Jennewein, J.S., Hively, D.W., Lamb, B.T., Daughtry, C.S., Thapa, R., Thieme, A.N., Reberg-Horton, C.S., Mirsky, S.B. 2024. Toward mapping cover crop residue traits with spaceborne imaging spectroscopy. Science of Remote Sensing. 1-33. https://doi.org/10.1007/s11119-024-10159-4.
DOI: https://doi.org/10.1007/s11119-024-10159-4

Interpretive Summary: over crops are biological tools that can provide agroecosystem services including reduced fertilizer needs for the subsequent cash crop. Cover crop residue carbon and nitrogen characteristics largely control how fast nutrients are available to cash crops, but current approaches for measuring these important characteristics across the landscape are limited. Remote sensing with satellites is one method to solve this problem, but there have been limitations in current space-based satellite spectral resolution needed to measure cover crop quality and quantity. One form of remote sensing, “spectroscopy”, divides light into very narrow colors that allow for plant and soil characterization, but only a handful of these sensors have been successfully launched into orbit. Moreover, carbon characteristics in living vegetation have been historically difficult to measure from space due to plant water content. This study measured cover crop nitrogen and carbon characteristics in terminated samples to remove the influence of plant water content. We conducted this work in a laboratory setting and in the field timed with a satellite overpass by a modern imaging spectroscopy satellite. Our results show that carbon characteristics can be successfully measured with spectroscopy with high accuracy and low error. These findings are substantial improvements over previous models that quantified these carbon traits in living vegetation. This work is of value to farmers because it creates a pathway by which maps of cover crop residue characteristics could be integrated into existing decision support tools to estimate residue persistence and nitrogen credits for informing management decisions.

Technical Abstract: Cover crops are biological tools that can provide agroecosystem services including improved soil health, reduced nutrient losses, and reduced fertilizer needs for the subsequent cash crop. When cover crops are terminated, living vegetation is converted into non-photosynthetic vegetation, also termed “residue.” Cover crop residue carbon traits (i.e., lignin, holocellulose, nonstructural carbohydrates) and nitrogen concentrations largely mediate its decomposition rate, nitrogen release kinetics, and the timing and amount of plant-available nitrogen to cash crops. Thus, it is critical to develop non-destructive approaches to quantify cover crop residue biochemical traits. Spectroscopy instruments have a well-established history of accurately estimating crop nitrogen status, but quantifying carbon traits has proven challenging due to confounding relationships with plant water content. Following termination, cover crop residue water content decreases making spectral absorption features of carbon traits more discernible and provides an opportunity to non-destructively estimate residue carbon traits using spectroscopy. The objective of this study was to quantify cover crop residue nitrogen and carbon traits using a combination of 1) the band equivalent reflectance (BER) of the PRecursore IperSpettrale della Missione Applicativa (PRISMA) imaging spectroscopy satellite derived from laboratory collected ASD-spectra (n = 275) of 11 cover crop species and 2) spaceborne PRISMA imagery from two dates that coincided with destructive samplings of cover crop residues in the spring of 2022 (n = 54). For both spectroscopic data sources, we used partial least square regression to predict cover crop residue carbon traits and nitrogen using 100 train-test splits, minimized overfitting risk with the PRESS statistics, and identified important wavelength and spectral indices using VIP scores. Laboratory BER of PRISMA models all demonstrated high accuracies and low errors for estimation of nitrogen and all carbon traits (adj. R2 = 0.90-0.97; RMSE = 0.23-5.44%). Importantly, our results suggest that a single empirical model may be used for a given trait across all 11 cover crop species and three functional groups – cereals, legumes, and brassicas – as we observed no major statistical differences in the slope or intercepts between species functional groups. Spaceborne imaging spectroscopy results demonstrated that cover crop residue carbon traits can be successfully estimated, particularly for concentrations of lignin (adj. R2 = 0.74; RMSE = 2.95%) and holo-cellulose (adj. R2 = 0.77; RMSE = 3.74%). We also observed strong relationships for nonstructural carbohydrates (adj. R2 = 0.60; RMSE = 4.44%). These findings are substantial improvements over previous models that quantified these carbon traits in living vegetation. As spaceborne imaging spectroscopy data become more widely available from NASA’s Surface Biology and Geology (SBG) and ESA’s Copernicus Hyperspectral Imaging Mission for the Environment (CHIME) missions, maps of cover crop residue biochemical traits could be regularly generated and integrated into existing decision support tools to estimate residue persistence and nitrogen credits for informing management decisions.