Evidence map›Paper›PMID 41374747›Full record

ArticleSensors (Basel, Switzerland)2025

Impact Mechanism of Spectral Differentiation on PV Performance and Optimization of PV Systems in Shaded Forest Environments.

Dongxiao Yang, Yuan He, Latai Ga, Daochun Xu, Xiaopeng Bai, Wenbin Li

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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.

Dongxiao YangSchool of Technology, Beijing Forestry University, Beijing 100083, China.
Yuan HeSchool of Technology, Beijing Forestry University, Beijing 100083, China.
Latai GaSchool of Renewable Energy, Inner Mongolia University of Technology, Ordos 017010, China.
Daochun XuSchool of Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0003-0827-8712
Xiaopeng BaiSchool of Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0002-9520-6137
Wenbin LiSchool of Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0001-8821-8992

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global low-carbon transition is driving the use of renewable energy for ecological monitoring. Traditional power supply for forest monitoring sensor equipment is constrained by high wired costs, frequent battery replacement, and the limitations of low light levels and special spectra under forest canopies on photovoltaic (PV) compatibility. Existing research lacks exploration of the correlation between under-forest spectra and PV performance. This study measured the summer understory light spectra of five tree species in Beijing, evaluated the performance of three types of PV cells-monocrystalline silicon, polycrystalline silicon, and amorphous silicon-and designed a low-light energy harvesting circuit. Results indicate that spectral differences under tree canopies are concentrated from 380-680 nm, exhibiting a distinctive forest-specific spectral feature of "high-band enrichment" above 680 nm. Under low-light conditions, polycrystalline silicon photovoltaics demonstrates optimal performance when adapted to this high-band spectrum. The designed circuit can activate at 5 W/m

Indexed as

forest monitoring sensorsPV systemshaded forest environmentsilicon-based PV cellsunderstory spectral differentiation

Identifiers

PMID41374747
PMCPMC12694442

What OpenQuestion holds

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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.