Evidence map›Paper›PMID 32484823›Full record

ArticlePloS one2020

The distribution of functional N-cycle related genes and ammonia and nitrate nitrogen in soil profiles fertilized with mineral and organic N fertilizer.

Massimo Zilio, Silvia Motta, Fulvia Tambone, Barbara Scaglia, Gabriele Boccasile, Andrea Squartini, Fabrizio Adani

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Forecasting Root Rot Disease through Predictive Microbial Functional Profiling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Massimo ZilioGruppo Ricicla labs., DiSAA, Università degli Studi di Milano, Milan, Italy.ORCID 0000-0001-5007-4540
Silvia MottaEnte Regionale per i Servizi alla Agricoltura e alle Foreste, Regione Lombardia, Milan, Italy.
Fulvia TamboneGruppo Ricicla labs., DiSAA, Università degli Studi di Milano, Milan, Italy.
Barbara ScagliaGruppo Ricicla labs., DiSAA, Università degli Studi di Milano, Milan, Italy.
Gabriele BoccasileDG Agricoltura, Regione Lombardia, Milan, Italy.
Andrea SquartiniDAFNAE, Università degli Studi di Padova, Agripolis, Padua, Italy.ORCID 0000-0002-1961-1165
Fabrizio AdaniGruppo Ricicla labs., DiSAA, Università degli Studi di Milano, Milan, Italy.ORCID 0000-0003-0250-730X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nitrogen transformation in soil is a complex process and the soil microbial population can regulate the potential for N mineralization, nitrification and denitrification. Here we show that agricultural soils under standard agricultural N-management are consistently characterized by a high presence of gene copies for some of the key biological activities related to the N-cycle. This led to a strong NO3- reduction (75%) passing from the soil surface (15.38 ± 11.36 g N-NO3 kg-1 on average) to the 1 m deep layer (3.92 ± 4.42 g N-NO3 kg-1 on average), and ensured low nitrate presence in the deepest layer. Under these circumstances the other soil properties play a minor role in reducing soil nitrate presence in soil. However, with excessive N fertilization, the abundance of bacterial gene copies is not sufficient to explain N leaching in soil and other factors, i.e. soil texture and rainfall, become more important in controlling these aspects.

Indexed as

FertilizersAmmoniaGene DosageGene Expression RegulationMineralsNitratesNitrogen CycleSoilAmmoniaFertilizersMineralsNitratesSoil

Identifiers

PMID32484823
PMCPMC7266355

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.