Evidence map›Paper›PMID 42038806›Full record

ArticlePlant phenomics (Washington, D.C.)2026

UAV-based spatial sampling bridges ground measurements and satellite data for multi-scale estimation of sugar beet aboveground biomass.

Qing Wang, Chunyu Jiang, Qing Li, Yingpu Che, Jianyi Huang, Shunfu Xiao, Ke Shao, Chen Chen, Lisuo Ren, Yan Guo and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

12 authors.

Qing WangCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Chunyu JiangCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Qing LiCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Yingpu CheCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Jianyi HuangCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Shunfu XiaoCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Ke ShaoInner Mongolia Academy of Science and Technology, Hohhot, 010010, China.
Chen ChenBayannur Modern Agriculture and Animal Husbandry Development Center, Bayannur, 015000, China.
Lisuo RenBayannur Modern Agriculture and Animal Husbandry Development Center, Bayannur, 015000, China.
Yan GuoCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Baoguo LiCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.
Yuntao MaCollege of Land Science and Technology, China Agricultural University, Beijing, 100193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aboveground biomass (AGB) is a critical indicator for assessing crop growth status and productivity, yet accurately linking fine-scale ground measurements with coarse-resolution satellite imagery remains challenging. Here, we propose an integrated ground-UAV-satellite framework that combines high-resolution UAV observations with an optimized systematic sampling-Global Moran's I (SS-GMI) procedure and a simple allometric growth model. Multi-variety sugar beet cultivated across heterogeneous habitats was used as a case study. Results indicate that a power-law model effectively captures the allometric relationships between AGB, plant height, and the Dreg vegetation index in sugar beet, achieving high accuracy and strong transferability. Incorporating phenological information from Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) codes and a thermal index further enhanced model robustness across independent habitat trials, yielding coefficients of determination (

Indexed as

Aboveground biomassAllometric growth modelsMultiscale sensingOptical satelliteSpatial sampling optimizationUAV

Identifiers

PMID42038806
PMCPMC13109573

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.