Evidence map›Paper›PMID 41487356›Full record

ArticleFrontiers in plant science2025

Assessment of three broadleaf weed species classification in rice field using UAV hyperspectral imaging and machine learning.

Nursyazyla Sulaiman, Nik Norasma Che'Ya, Abdul Shukor Juraimi, Nisfariza Mohd Noor, Rhushalshafira Rosle, Muhammad Huzaifah Mohd Roslim

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Nursyazyla SulaimanDepartment of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Nik Norasma Che'YaDepartment of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Abdul Shukor JuraimiDepartment of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Nisfariza Mohd NoorDepartment of Geography, Faculty of Arts and Social Sciences, University of Malaya, Kuala Lumpur, Malaysia.
Rhushalshafira RosleDepartment of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
Muhammad Huzaifah Mohd RoslimDepartment of Crop Science, Faculty of Agricultural Science and Forestry, Universiti Putra Malaysia, Bintulu, Sarawak, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Broadleaf weed (BLW) infestation is a major challenge in rice cultivation, particularly during the early vegetative stages when competition for resources is most critical. This study aims to enhance early-stage detection and classification of three prevalent BLW species-

Indexed as

hyperspectralmachine learningremote sensingrice cropweed

Identifiers

PMID41487356
PMCPMC12756349

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.