The response of a sorghum sudangrass cover crop to residual nitrogen and its relationship with spectral sensors

A sorghum sudangrass (SSG) cover crop grown after a cash crop could take up residual nitrogen (N) before it is lost. As in‐field monitoring of SSG properties is laborious, predicting biomass and N concentrations with spectral sensors could be useful. At two sites in Live Oak, Florida, we evaluated t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Agrosystems, Geosciences & Environment Geosciences & Environment, 2024-09, Vol.7 (3), p.n/a
Hauptverfasser: Netto‐Ferreira, Julia Barra, Sá Leitão, Diego Arruda Huggins, Griffin, Winniefred, Sharma, Lakesh K., Maltais‐Landry, Gabriel
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A sorghum sudangrass (SSG) cover crop grown after a cash crop could take up residual nitrogen (N) before it is lost. As in‐field monitoring of SSG properties is laborious, predicting biomass and N concentrations with spectral sensors could be useful. At two sites in Live Oak, Florida, we evaluated the response of SSG to residual N from previous N fertilization and the performance of handheld and satellite sensors in estimating SSG properties. We quantified aboveground biomass, plant N, leaf greenness (NDVI), net potential N mineralization (PNM), and soil permanganate oxidizable carbon (POXC). Residual N did not affect SSG properties, PNM was highest at the highest N input rate in one site, and soil POXC was correlated with SSG properties (biomass and plant N). NDVI measured from a handheld sensor better predicted SSG properties than satellite imagery in these small plots, suggesting a greater potential to be a useful management tool. Core Ideas Sorghum sudangrass growth was not influenced by residual nitrogen (N) from a previous corn crop. In one of two fields, potential N mineralization was highest with the highest N input rate applied to corn. Normalized difference vegetation index derived from a handheld sensor was more predictive of cover crop properties than satellite imagery.
ISSN:2639-6696
2639-6696
DOI:10.1002/agg2.20557