Evidence map›Paper›PMID 38192698›Full record

ArticleFrontiers in plant science2023

Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery.

Bo Chen, Guanmin Huang, Xianju Lu, Shenghao Gu, Weiliang Wen, Guangtao Wang, Wushuai Chang, Xinyu Guo, Chunjiang Zhao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.0field-weighted citation impact, top 5% of its field
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

12 citing papers in PubMed, 20 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Bo ChenInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Guanmin HuangInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Xianju LuInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Shenghao GuInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Weiliang WenInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Guangtao WangBeijing Key Laboratory of Digital Plant, China National Engineering Research Center for Information Technology in Agriculture, Beijing, China.
Wushuai ChangBeijing Key Laboratory of Digital Plant, China National Engineering Research Center for Information Technology in Agriculture, Beijing, China.
Xinyu GuoInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
Chunjiang ZhaoInformation Technology Research Center, Beijing Academy of Agriculture Forestry Sciences, Beijing, China.
National Engineering Research Center for Information Technology in Agriculture · CNJilin Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models. Hence, this study aimed to develop a novel method for estimating canopy chlorophyll content (represented by SPAD values) in maize (

Indexed as

canopy chlorophyllmaizeSPAD valuesUAV multispectralvertical distribution

Identifiers

PMID38192698
PMCPMC10773710
OpenAlexW4389895892

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.