Beyond Conventional Methods: Rapid and Precise Quantification of Polyphenols in

Hao Liang, Xin Yang, Nan Wang, Xinyue Lu, Wenwu Zou, Aicun Zhou, Xiongwei Lou, Yufei Lin

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

8 authors.

Hao LiangCollege of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China.ORCID 0009-0007-4832-0694

Xin YangCollege of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China.

Nan WangCollege of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China.

Xinyue LuCollege of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China.

Wenwu ZouInstitute of Modern Agriculture and Health Care Industry, Wencheng 325300, China.

Aicun ZhouNational Key Laboratory for Development and Utilization of Forest Food Resources, Zhejiang A&F University, Hangzhou 311300, China.

Xiongwei LouCollege of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China.

Yufei LinWenzhou Key Laboratory of AI Agents for Agriculture, Wenzhou Academy of Agricultural Sciences, Wenzhou 325006, China.ORCID 0000-0001-7183-9477

Funding

Natural Science Foundation of Zhejiang Province Grant No. LQN25C160004Postdoctoral Research Program of Zhejiang Province Grant No. ZJ2024132Scientific Research Foundation of Zhejiang A&F University Grant No. 2022LFR107Zhejiang Provincial Cooperative Forestry Science and Technology Project Grant No. 2026SY15

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Hyperspectral ImagingPolyphenolsVignaConvolutional Neural NetworksNeural Networks, ComputerPolyphenolshyperspectral imagingnondestructive detectionpolyphenol contentresidual convolutional neural networkVigna umbellata

Identifiers

PMID42076465

DOI10.3390/s26082356

PMCPMC13120397

What Socratic 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 Socratic graph.