Evidence map›Paper›PMID 41829783›Full record

ArticlePlants (Basel, Switzerland)2026

Estimation of Nitrogen Content in Alfalfa Plants Based on Multi-Source Feature Fusion.

Jiapeng Zhu, Haohao Dang, Demin Fu, Guangping Qi, Yanxia Kang, Yanlin Ma, Siqin Zhang, Chungang Jing, Bojie Xie, Yuanbo Jiang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (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

13 authors.

Jiapeng ZhuCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Haohao DangCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Demin FuCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Guangping QiCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Yanxia KangCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Yanlin MaCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Siqin ZhangCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Chungang JingQingyang Hydrological and Water Resources Survey Center, Qingyang 745000, China.
Bojie XieCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Yuanbo JiangCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Jinxi ChenCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Boda LiCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.
Jun YuCollege of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.

Funding

Gansu Agricultural University Discipline Team Development Special Project "Innovation in Effi-cient Utilization of Water and Soil Resources for Specialty Crops in Northwest Arid Areas" (GAU-XKTD-2022-09)Gansu Provincial Key R&D Program (23YFFA0020)Gansu Provincial Water Resources Science Experiment Research and Technology Promotion Project (GSAU-JSFW-2023-144, 26GSLK075, 26GSLK077)National Natural Science Foundation of China (52269009; 52469007)
6 · The paper itself

Abstract

Plant nitrogen content (PNC) is a core physiological parameter characterizing crop nitrogen nutrition status. Its precise and dynamic monitoring is crucial for crop growth diagnosis, optimizing nitrogen fertilizer management, enhancing fertilizer use efficiency, and reducing agricultural nonpoint source pollution. This study utilized multispectral imagery from unmanned aerial vehicles (UAVs) to extract vegetation indices (VIs) and texture feature values (TFVs) during critical growth stages of alfalfa. By combining TFVs to construct texture indices (TIs), variables exhibiting extremely significant correlations with alfalfa PNC (

Indexed as

alfalfafeature fusionmachine learningplant nitrogen contentUAV multispectral

Identifiers

PMID41829783
PMCPMC12987103

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.