Vis/NIR Spectroscopy and Chemometrics for Non-Destructive Estimation of Chlorophyll Content in Different Plant Leaves.

Qiang Huang, Meihua Yang, Liao Ouyang, Zimiao Wang, Jiayao Lin

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. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

1 citing paper in PubMed.

Plant stress early detection through a low-cost multispectral device: Toward safer and more sustainable agricultural practices.iScience · 2026
Article

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

5 authors.

Qiang HuangSchool of Materials and Environmental Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China.

Meihua YangDepartment of Environmental Engineering, Yuzhang Normal University, Nanchang 330103, China.

Liao OuyangSchool of Materials and Environmental Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China.

Zimiao WangSchool of Materials and Environmental Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China.

Jiayao LinSchool of Materials and Environmental Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vegetation biochemical and biophysical variables, especially chlorophyll content, are pivotal indicators for assessing drought's impact on plants. Chlorophyll, crucial for photosynthesis, ultimately influences crop productivity. This study evaluates the mean squared Euclidean distance (MSD) method, traditionally applied in soil analysis, for estimating chlorophyll content in five diverse leaf types across various months using visible/near-infrared (vis/NIR) spectral reflectance. The MSD method serves as a tool for selecting a representative calibration dataset. By integrating MSD with partial least squares regression (PLSR) and the Cubist model, we aim to accurately predict chlorophyll content, focusing on key spectral bands within the ranges of 500-640 nm and 740-1100 nm. In the validation dataset, PLSR achieved a high determination coefficient (R

Indexed as

ChemometricsChlorophyllPlant LeavesCalibrationLeast-Squares AnalysisSpectroscopy, Near-InfraredChlorophyllchlorophyll contentMSD methodsvis/NIR spectroscopy

Identifiers

PMID40292752

DOI10.3390/s25061673

PMCPMC11944571

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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.