DataVXJournal of Nanoparticle ResearchPaper
journal article·2022-06

Impacts of graphitic nanofertilizers on nitrogen cycling in a sandy, agricultural soil

Partho Das, Kelsie Davis, C. Ryan Penton, Paul Westerhoff, Yuqiang Bi

Journal of Nanoparticle Research· Volume 24· Issue 6
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Source abstract

Abstract

Graphene nanofertilizers have demonstrated immense potential in improving agricultural productivity and nitrogen management. However, how those nanomaterials interact with soil microbial communities related to N cycle remain unclear. The present study assessed the impact of four different graphitic nanomaterials (i.e., GO, graphene oxide; rGO, reduced graphene oxide; GNP, graphene nanoplatelet; GNA, graphite nanoadditive) and biochar at two different doses (5 and 1000 mg kg−1 soil) on soil respiration, nitrification potential, and microbial N cycling functional genes over 28 days of incubation of sandy agricultural soil. Basal respiration indicated a transient increase of microbial activity with all treatments, while substrate induced respiration (SIR) revealed an enhancement of microbial respiration rate with some treatments that sustained at the end of the incubation. No significant differences in the maximum nitrification potential were observed when treated with GNMs or biochar. However, decreased abundances of amoA genes and increased abundance of denitrifying genes (nirK, nirS, nosZ) in all treated soils suggested a decreased potential for nitrification and boosted denitrification after 28-day exposure. In addition, GNMs showed minimum impact on nifH population in this incubation study. Together, the results suggest that graphitic nanomaterials might suppress nitrification and potentially reduce losses by nitrate leaching in agricultural soils. Graphical abstract
Source: expertdata · Quality: candidate unverified · Source record ↗

Research context

Nanomaterials

OpenAlex topics: Graphene and Nanomaterials Applications · Wastewater Treatment and Nitrogen Removal · Microbial Fuel Cells and Bioremediation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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