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. Spaceborne imaging spectroscopy enables carbon trait estimation in cover cropand cash crop residues. Precision Agriculture. 25:2165-2197. 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: Purpose Cover crops and reduced tillage are two key climate smart agricultural practices that can provide agroecosystem services including improved soil health, increased soil carbon sequestration, and reduced fertilizer needs. Crop residue carbon traits (i.e., lignin, holocellulose, non-structural carbohydrates) and nitrogen concentrations largely mediate decomposition rates and amount of plant-available nitrogen accessible to cash crops and determine soil carbon residence time. Non-destructive approaches to quantify these important traits are possible using spectroscopy. Methods The objective of this study was to evaluate the efficacy of spectroscopy instruments to quantify crop residue biochemical traits in cover crop agriculture systems using partial least squares regression models and a combination of (1) the band equivalent reflectance (BER) of the PRecursore IperSpettrale della Missione Applicativa (PRISMA) imaging spectroscopy sensor derived from laboratory collected Analytical Spectral Devices (ASD) spectra (n'='296) of 11 cover crop species and three cash crop species, and (2) spaceborne PRISMA imagery that coincided with destructive crop residue collections in the spring of 2022 (n'='65). Spectral range was constrained to 1200 to 2400 nm to reduce the likelihood of confounding relationships in wavelengths sensitive to plant pigments or those related to canopy structure for both analytical approaches. Results Models using laboratory BER of PRISMA all demonstrated high accuracies and low errors for estimation of nitrogen and carbon traits (adj. R2'='0.86 - 0.98; RMSE'='0.24 - 4.25%) and results indicate that a single model may be used for a given trait across all species. Models using spaceborne imaging spectroscopy demonstrated that crop residue carbon traits can be successfully estimated using PRISMA imagery (adj. R2'='0.65 - 0.75; RMSE'='2.71 - 4.16%). We found moderate relationships between nitrogen concentration and PRISMA imagery (adj. R2'='0.52; RMSE'='0.25%), which is partly related to the range of nitrogen in these senesced crop residues (0.38–1.85%). PRISMA imagery models were also influenced by atmospheric absorption, variability in surface moisture content, and some presence of green vegetation. Conclusion As spaceborne imaging spectroscopy data become more widely available from upcoming missions, crop residue trait estimates could be regularly generated and integrated into decision support tools to calculate decomposition rates and associated nitrogen credits to inform precision field management, as well as to enable measurement, monitoring, reporting, and verification of net carbon benefits from climate smart agricultural practice adoption in an emerging carbon marketplace.