Evidence map›Paper›PMID 32549373›Full record

ArticleSensors (Basel, Switzerland)2020

Evaluation of Soil Management Effect on Crop Productivity and Vegetation Indices Accuracy in Mediterranean Cereal-Based Cropping Systems.

Roberto Orsini, Marco Fiorentini, Stefano Zenobi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Metrology for Agriculture and Forestry 2019.Sensors (Basel, Switzerland) · 2020
    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

3 authors.

Roberto OrsiniDepartment of Agricultural, Food and Environmental Sciences (D3A), Agronomy and Crop Science Section, Marche Polytechnic University, 60131 Ancona, Italy.
Marco FiorentiniDepartment of Agricultural, Food and Environmental Sciences (D3A), Agronomy and Crop Science Section, Marche Polytechnic University, 60131 Ancona, Italy.
Stefano ZenobiDepartment of Agricultural, Food and Environmental Sciences (D3A), Agronomy and Crop Science Section, Marche Polytechnic University, 60131 Ancona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mostly, precision agriculture applications include the acquisition and elaboration of images, and it is fundamental to understand how farmers' practices, such as soil management, affect those images and relate to the vegetation index. We investigated how long-term conservation agriculture practices, in comparison with conventional practices, can affect the yield components and the accuracy of five vegetation indexes. The experimental site is a part of a long-term experiment established in 1994 and is still ongoing that consists of a rainfed 2-year rotation with durum wheat and maize, where two unfertilized soil managements were repeated in the same plots every year. This study shows the superiority of no tillage over conventional tillage for both nutritional and productive aspects on durum wheat. The soil management affects the vegetation indexes' accuracy, which is related to the nitrogen nutrition status. No-tillage management, which is characterized by a higher content of soil organic matter and nitrogen availability into the soil, allows obtaining a higher accuracy than the conventional tillage. So, the users of multispectral cameras for precision agriculture applications must take into account the soil management, organic matter, and nitrogen content.

Indexed as

conventional tillagedurum wheatmultispectral imageryno tillagenutritional statusremote sensingsoil organic matter

Identifiers

PMID32549373
PMCPMC7348749

What OpenQuestion holds

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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.