Evidence map›Paper›PMID 41978004›Full record

ArticleSensors (Basel, Switzerland)2026

UAV-Based Estimation of Tea Leaf Area Index in Mountainous Terrain: Integrating Topographic Correction and Interpretable Machine Learning.

Na Lin, Jian Zhao, Huxiang Shao, Miaomiao Wang, Hong Chen

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

5 authors.

Na LinInstitute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.
Jian ZhaoInstitute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.ORCID 0000-0003-2364-0687
Huxiang ShaoInstitute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.
Miaomiao WangInstitute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.ORCID 0000-0003-2665-6094
Hong ChenInstitute of Digital Agriculture, Fujian Academy of Agricultural Sciences, Fuzhou 350003, China.

Funding

the Basic Scientific Research Special Project of Provincial Public Welfare Research Institutes of Fujian Province, China 2025R1033001the Free Exploration Science and Technology Innovation Project of Fujian Academy of Agricultural Sciences, China ZYTS2023022
6 · The paper itself

Abstract

Leaf Area Index (LAI) is a fundamental parameter for characterizing the growth of tea (

Indexed as

Camellia sinensisMachine LearningPlant LeavesRemote Sensing TechnologyTeaUnmanned Aerial DevicesAlgorithmsBoosting Machine Learning AlgorithmsChinaRandom ForestTeacanopy textureleaf area indexmachine learningSHAPtea plantationtopographic correctionUAV

Identifiers

PMID41978004
PMCPMC13075276

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.