Evidence map›Paper›PMID 38881027›Full record

ArticleApplied spectroscopy2024

Characterization of Near Infrared-Dye Colored Fabrics Using Hyperspectral Imaging.

Rajbir Kaur, Muhammad Mudassir Arif Chaudhry, Catherine Findlay, Mohammad Nadimi, Mashiur Rahman, Jitendra Paliwal

Abstract read
In one paragraph

Article in Applied spectroscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Rajbir KaurDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.
Muhammad Mudassir Arif ChaudhryDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.
Catherine FindlayDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.
Mohammad NadimiDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.
Mashiur RahmanDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.
Jitendra PaliwalDepartment of Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3 T 5V6, Canada.ORCID 0000-0002-1665-3626

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Near-infrared (NIR) dyes have a unique ability to interact favorably with light in the NIR region, which is particularly interesting where stealth and camouflage are paramount, such as in military uniforms. Characterization of cotton fabric dyed with NIR-absorbing dyes using visible-NIR (Vis-NIR) and short-wave infrared (SWIR) hyperspectral imaging was done. The aim of the study was to discern spectral changes caused by variations in dye concentration and dyeing temperature as these parameters directly influence color- and crocking-fastness of fabrics impacting the camouflage effect. The fabric was dyed at three concentrations (2.5, 5, and 10%) and two dyeing temperatures (55 °C and 85 °C) and principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed on the spectra to discriminate the fabrics based on dye concentrations. The PCA models successfully segregated the fabrics based on the dye concentration and dyeing temperature, while PLS-DA models demonstrated classification accuracies between 75 and 100% in the Vis-NIR range. Spectra in the SWIR region could not be used to detect the differences in the concentrations of the NIR dyes. This finding is promising, as it aligns with the objective of creating NIR-dyed camouflage fabrics that remain indistinguishable under varying dye concentrations. These results open possibilities for further exploration in enhancing the stealth capabilities of textiles in military applications.

Indexed as

detectabilitydiscriminationhyperspectral imagingnear-infrared dyespartial least squares discriminate analysisPCAPLS-DAprincipal component analysisTextiles

Identifiers

PMID38881027
PMCPMC11491044

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Registered trials

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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.