ArticleACS omega2018
Single-Image-Referenced Colorimetric Water Quality Detection Using a Smartphone.
Article in ACS omega, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Colorimetric Ready-to-Use Microfluidic Chips for Rapid Antibiotic Susceptibility Testing of Methicillin-ResistantACS omega · 2026Article
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- Portable Multispectral Imaging System for Sodium Nitrite Detection via Griess Reaction on Cellulose Fiber Sample Pads.Sensors (Basel, Switzerland) · 2025Article
- Accessible water quality monitoring through hybrid human-machine colorimetric methods.Environmental monitoring and assessment · 2025Article
- Research on Water Quality Chemical Oxygen Demand Detection Using Laser-Induced Fluorescence Image Processing.Sensors (Basel, Switzerland) · 2025Article
- Anthocyanin-rich black carrot (Daucus carota ssp. sativus var. atrorubens Alef.) and red cabbage (Brassica oleracea) extracts incorporated biosensor for colorimetric detection of Helicobacter pylori with color image processing.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023Article
- Red cabbage extract-mediated colorimetric sensor for swift, sensitive and economic detection of urease-positive bacteria by naked eye and Smartphone platform.Scientific reports · 2023Article
- A Simple Technique Based on Digital Images for Determination of Nitrogen Dioxide in Ambient Air.Water, air, and soil pollution · 2021Article
- Article
- Determination of acid dissociation constants of Alizarin Red S, Methyl Orange, Bromothymol Blue and Bromophenol Blue using a digital camera.RSC advances · 2020Article
- Article
- Current Trends in the Biosensors for Biological Warfare Agents Assay.Materials (Basel, Switzerland) · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we present a smartphone platform for colorimetric water quality detection based on the use of built-in camera for capturing a single-use reference image. A custom-developed app processes this image for training and creates a reference model to be used later in real experimental conditions to calculate the concentration of the unknown solution. This platform has been tested on four different water quality colorimetric assays with various concentration levels, and results show that the presented platform provides approximately 100% accuracy for colorimetric assays with noticeable color difference. This portable, cost-effective, and user-friendly platform is promising for application in water quality monitoring.
Identifiers
What OpenQuestion holds
Registered trials
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.