Quantifying Greenhouse Gas (CO2, CH4, and N2O) Fluxes from Soil in a Pasture

doi:10.1201/b10600-22

GIS Applications in Agriculture, Volume Two 2011

DOI: 10.1201/b10600-22

|View full text |Cite

Quantifying Greenhouse Gas (CO2, CH4, and N2O) Fluxes from Soil in a Pasture

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Butchee et al (2011) found that the farmers’ N rate could be reduced by 23 kg N ha −1 without reducing wheat yield and grain protein based on the Oklahoma sensor‐based N calculator. Bronson et al (2011b) obtained similar results in Missouri where VNMS reduced N consumption by 30 kg N ha −1 without any loss of corn yield. Raun et al (2002) showed that in Oklahoma an algorithm driven by crop sensors reduced N use by 47 kg ha −1 and improved NUE by more than 15%.…”

mentioning

confidence: 69%

Nitrogen Consumption and Productivity of Cotton under Sensor‐based Variable‐rate Nitrogen Fertilization

Yin

Raper

et al. 2019

Agronomy Journal

View full text Add to dashboard Cite

Precision N management based on crop reflectance can be used to reduce over‐ and under‐application of N fertilizer to cotton (Gossypium hirsutum L.). The objective of this study was to evaluate the effects of variable‐rate nitrogen management systems (VNMS) based on optical sensing of crop canopy relative to a farmer's uniform‐rate nitrogen application system (FUNS) on N fertilizer consumption, post‐harvest soil N level, and cotton productivity. Eight field strip‐plot trials were conducted on cotton across West Tennessee during 2012 to 2014. Four sensor‐based VNMS were compared with FUNS in a randomized complete block design with three replicates. Two VNMS were based on optical sensing of canopy alone with different algorithms, while the other two were developed from optical sensing and crop yield maps of previous years but differed in algorithms. The variable and uniform fertilizer application systems had similar leaf N concentrations between early bloom and mid‐bloom and similar canopy normalized difference vegetation index (NDVI) values at mid‐bloom. The VNMS produced similar lint yield as FUNS. The VNMS reduced N consumption by 10.3 to 16.9% and improved nitrogen use efficiency (NUE) by 8.3 to 11.0% compared with FUNS. Both VNMS and FUNS had similar post‐harvest N levels in soil profile. Benefits from incorporating yield maps into sensor‐based VNMS were not noticeable. Thus, the in‐season sensor‐based VNMS are reliable in precision N management for cotton resulting in comparable lint yield, less N consumption, and higher NUE, which could lead to environmental and economic benefits. Core Ideas Leaf N concentration and canopy normalized difference vegetation index were comparable under variable‐rate N management systems relative to a farmer's uniform‐rate N application system. Variable‐rate N management systems produced similar lint yield but better fiber quality compared with a farmer's uniform‐rate N application system. Variable‐rate N management systems reduced N use by 10.3 to 16.9% but increased nitrogen use efficiency by 8.3 to 11.0% over a farmer's uniform‐rate N application system. No effect of variable‐rate N management systems was observed on post‐harvest soil N level relative to a farmer's uniform‐rate N application system. Benefits with incorporating yield maps into sensor‐based variable‐rate N management systems were not noticeable.

show abstract

mentioning

confidence: 69%

Nitrogen Consumption and Productivity of Cotton under Sensor‐based Variable‐rate Nitrogen Fertilization

Yin

Raper

et al. 2019

Agronomy Journal

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Quantifying Greenhouse Gas (CO2, CH4, and N2O) Fluxes from Soil in a Pasture

Cited by 1 publication

References 10 publications

Nitrogen Consumption and Productivity of Cotton under Sensor‐based Variable‐rate Nitrogen Fertilization

Nitrogen Consumption and Productivity of Cotton under Sensor‐based Variable‐rate Nitrogen Fertilization

Contact Info

Product

Resources

About