Evidence map›Paper›PMID 37644055›Full record

ArticleScientific reports2023

A soil productivity system reveals most Brazilian agricultural lands are below their maximum potential.

Lucas T Greschuk, José A M Demattê, Nélida E Q Silvero, Nícolas Augusto Rosin

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Lucas T GreschukDepartment of Soil Science, University of São Paulo (ESALQ/USP), Av. Pádua Dias, 11, Piracicaba, SP, 13418-900, Brazil.
José A M DemattêDepartment of Soil Science, University of São Paulo (ESALQ/USP), Av. Pádua Dias, 11, Piracicaba, SP, 13418-900, Brazil. jamdemat@usp.br.
Nélida E Q SilveroDepartment of Soil Science, University of São Paulo (ESALQ/USP), Av. Pádua Dias, 11, Piracicaba, SP, 13418-900, Brazil.
Nícolas Augusto RosinDepartment of Soil Science, University of São Paulo (ESALQ/USP), Av. Pádua Dias, 11, Piracicaba, SP, 13418-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food production is extremely dependent on the soil. Brazil plays an important role in the global food production chain. Although only 30% of the total Brazilian agricultural areas are used for crop and livestock, the full soil production potential needs to be evaluated due to the environmental and legal impossibility to expand agriculture to new areas. A novel approach to assess the productive potential of soils, called "SoilPP" and based on soil analysis (0-100 cm) - which express its pedological information - and machine learning is presented. Historical yields of sugarcane and soybeans were analyzed, allowing to identify where it is still possible to improve crop yields. The soybean yields were below the estimated SoilPP in 46% of Brazilian counties and could be improved by proper management practices. For sugarcane, 38% of areas can be improved. This technique allowed us to understand and map the food yield situation over large areas, which can support farmers, consultants, industries, policymakers, and world food security planning.

Identifiers

PMID37644055
PMCPMC10465562

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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.