Evidence map›Paper›PMID 39738218›Full record

ArticleScientific reports2024

Legume content estimation from UAV image in grass-legume meadows: comparison methods based on the UAV coverage vs. field biomass.

Kensuke Kawamura, Tsuneki Tanaka, Taisuke Yasuda, Shoji Okoshi, Masaaki Hanada, Kazuya Doi, Toshiya Saigusa, Takanori Yagi, Kenji Sudo, Kenji Okumura and 1 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 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

11 authors.

Kensuke KawamuraObihiro University of Agriculture and Veterinary Medicine, 2-11 Inada-cho Nishi, Obihiro, Hokkaido, Japan. kamuken@obihiro.ac.jp.
Tsuneki TanakaDairy Research Center, Hokkaido Research Organization (HRO), Nakashibetsu, Hokkaido, Japan.
Taisuke YasudaMount Fuji Research Institute, Yamanashi Prefectural Government, Yamanashi, Japan.
Shoji OkoshiObihiro University of Agriculture and Veterinary Medicine, 2-11 Inada-cho Nishi, Obihiro, Hokkaido, Japan.
Masaaki HanadaObihiro University of Agriculture and Veterinary Medicine, 2-11 Inada-cho Nishi, Obihiro, Hokkaido, Japan.
Kazuya DoiRakuno Gakuen University, 582 Bunkyodai-Midori, Ebetsu, Hokkaido, Japan.
Toshiya SaigusaRakuno Gakuen University, 582 Bunkyodai-Midori, Ebetsu, Hokkaido, Japan.
Takanori YagiHokkaido Agricultural Research Center, National Agriculture and Food Research Organization (NARO), Sapporo, Hokkaido, Japan.
Kenji SudoHokkaido Agricultural Research Center, National Agriculture and Food Research Organization (NARO), Sapporo, Hokkaido, Japan.
Kenji OkumuraHokkaido Agricultural Research Center, National Agriculture and Food Research Organization (NARO), Sapporo, Hokkaido, Japan.
Jihyun LimInstitute for Agro-Environmental Sciences, National Agriculture and Food Research Organization (NARO), Tsukuba, Ibaraki, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Legume content (LC) in grass-legume mixtures is important for assessing forage quality and optimizing fertilizer application in meadow fields. This study focuses on differences in LC measurements obtained from unmanned aerial vehicle (UAV) images and ground surveys based on dry matter assessments in seven meadow fields in Hokkaido, Japan. We propose a UAV-based LC (LC

Indexed as

BiomassFabaceaeGrasslandPoaceaeAlgorithmsJapanRemote Sensing Technology

Identifiers

PMID39738218
PMCPMC11685594

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.