Evidence map›Paper›PMID 39130162›Full record

ArticlePlant phenomics (Washington, D.C.)2024

PREPs: An Open-Source Software for High-Throughput Field Plant Phenotyping.

Atsushi Itoh, Stephen N Njane, Masayuki Hirafuji, Wei Guo

Abstract read
In one paragraph

Article in Plant phenomics (Washington, D.C.), 2024. 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.

Atsushi ItohHokkaido Agricultural Research Center, National Agriculture and Food Research Organization, 9-4 Shinseiminami, Memurocho, Kasaigun, Hokkaido 082-0081, Japan.
Stephen N NjaneHokkaido Agricultural Research Center, National Agriculture and Food Research Organization, 9-4 Shinseiminami, Memurocho, Kasaigun, Hokkaido 082-0081, Japan.ORCID https://orcid.org/0000-0001-5772-5297
Masayuki HirafujiGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1 Chome-1-1 Midoricho, Nishitokyo, Tokyo 188-0002, Japan.
Wei GuoGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1 Chome-1-1 Midoricho, Nishitokyo, Tokyo 188-0002, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An open-source software for field-based plant phenotyping, Precision Plots Analyzer (PREPs), was developed using Window.NET. The software runs on 64-bit Windows computers. This software allows the extraction of phenotypic traits on a per-microplot basis from orthomosaic and digital surface model (DSM) images generated by Structure-from-Motion/Multi-View-Stereo (SfM-MVS) tools. Moreover, there is no need to acquire skills in geographical information system (GIS) or programming languages for image analysis. Three use cases illustrated the software's functionality. The first involved monitoring the growth of sugar beet varieties in an experimental field using an unmanned aerial vehicle (UAV), where differences among varieties were detected through estimates of crop height, coverage, and volume index. Second, mixed varieties of potato crops were estimated using a UAV and varietal differences were observed from the estimated phenotypic traits. A strong correlation was observed between the manually measured crop height and UAV-estimated crop height. Finally, using a multicamera array attached to a tractor, the height, coverage, and volume index of the 3 potato varieties were precisely estimated. PREPs software is poised to be a useful tool that allows anyone without prior knowledge of programming to extract crop traits for phenotyping.

Identifiers

PMID39130162
PMCPMC11310773

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.