Smartphone-based Image Analysis Research Articles

Multiplexed colorimetry collaborated with smartphone-based image analysis for simultaneous and fast visualization of dyes in both environmental and food samples

In this work, a multiplexed colorimetric strategy was initiated for simultaneous and fast visualization of dyes using low-cost and easy-to-prepare indicator papers as sorbents. Response surface methodology (RSM) was employed to model statistically and optimize the process variables for dyes extraction and colorimetric assays. Multiplexed colorimetry was realized by virtue of synchronous color alignments from different dimensions of multiple dyes co-stained colorimetric cards under RSM-optimized conditions, and smartphone-based image analysis was subsequently performed from different modes to double-check the credibility of colorimetric assays. As concept-to-proof trials, simultaneous visualization of dyes in both beverages and simulated dye effluents was experimentally proved with results highly matched to HPLC or spiked amounts at RSM-predicted staining time as short as 50 s ∼3 min, giving LODs as low as 0.97 ± 0.22/0.18 ± 0.08 μg/mL (tartrazine/brilliant blue) for multiplexed colorimetry, which much lower than those obtained by single colorimetry. Since this is the first case to propose such a RSM-guided multiplexed colorimetric concept, it will provide a reference for engineering of other all-in-one devices which can realize synchronous visualization applications within limited experimental steps.

Double phage displayed peptides co-targeting-based biosensor with signal enhancement activity for colorimetric detection of Staphylococcus aureus

The development of simple, fast, sensitive, and specific strategies for the detection of foodborne pathogenic bacteria is crucial for ensuring food safety and promoting human health. Currently, detection methods for Staphylococcus aureus still suffer from issues such as low specificity and low sensitivity. To address this problem, we proposed a sensitivity enhancement strategy based on double phage-displayed peptides (PDPs) co-targeting. Firstly, we screened two PDPs and analyzed their binding mechanisms through fluorescent localization, pull-down assay, and molecular docking. The two PDPs target S. aureus by binding to specific proteins on its outer membrane. Based on this phenomenon, a convenient and sensitive double PDPs colorimetric biosensor was developed. Double thiol-modified phage-displayed peptides (PDP-SH) enhance the aggregation of gold nanoparticles (AuNPs), whereas the specific interaction between the double PDPs and bacteria inhibits the aggregation of AuNPs, resulting in an increased visible color change before and after the addition of bacteria. This one-step colorimetric approach displayed a high sensitivity of 2.35 CFU/mL and a wide detection range from 10–2 × 108 CFU/mL. The combination with smartphone-based image analysis improved the portability of this method. This strategy achieves the straightforward, highly sensitive and portable detection of pathogenic bacteria.

Molecularly imprinted polymer on cotton materials as substrates for smartphone-based image and distance-based analysis of Cu(II) in water samples.

Cotton fabric was used as a substrate for smartphone-based image analysis of Cu(II) in drinking water. To enhance its selective and specific binding sites on the cotton surface, a molecularly imprinted polymer (MIP) was introduced using color complexes of 4-(2-pyridylazo)resorcinol-Cu(II) (PAR-Cu(II)) as the template molecule, 3-aminopropyltriethoxysilane (APTES) as the functional monomer, tetraethoxysilane (TEOS) as the crosslinker and NH3 as the catalyst. After achieving optimum conditions, the obtained CF-MIP/PAR-Cu(II) presented a red color, which was changed to yellow upon the removal of Cu(II) with 1.5 M HCl. After using CF-MIP/PAR to detect Cu(II), the red, green and blue intensities of the images captured using a smartphone were analyzed using the ImageJ program. For the calibration curve plotted between Δgreen intensity and Cu concentration, the linear range was 0.10-1.0 mg L-1 with the best correlation coefficient (R2) of 0.999. The limit of detection (LOD) and the limit of quantification (LOQ) were found to be 0.038 and 0.11 mg L-1, respectively. To obtain a distance-based device, MIP-modified cotton thread (CT-MIP/PAR) with a four-channel design was used as an alternative device. The distance of red color development was measured after using CT-MIP/PAR to detect Cu(II). The linear range was 0.50-3.0 mg L-1 with an R2 of 0.997. The LOD and LOQ were 0.18 and 0.56 mg L-1, respectively. The proposed methods provide simple, portable and inexpensive devices with high accuracy and precision for the detection of Cu(II) in drinking water.

Smart salt-responsive thread for highly sensitive microfluidic glucose detection in sweat.

Thread-based microfluidic colorimetric sensors have been deemed a potential tool that may be incorporated into textiles for non-invasive sweat analysis. Nevertheless, their poor performance significantly limits their practical uses in sweat glucose detection down to 20 μM. Herein, a microfluidic glucose sensing device containing a salt-responsive thread is developed for the highly sensitive detection of glucose in human sweat. By grafting a zwitterionic polymer brush-which could react to ionic strength by changing the conformation of the polymer chains from the collapsing state to the stretching state-onto the cotton thread, the salt-responsive thread was created. Compared to the pristine cotton thread, the modified thread has better ion-capture capabilities, a more noticeable swelling effect, and a higher ability to absorb water. These enable a significant enrichment of glucose when the saline solution passes through it. The salt-responsive thread was employed to construct a thread/paper-based microfluidic sensing device for the monitoring of glucose in artificial sweat, exhibiting a sensitivity of -0.255 μM-1 and a detection limit of 14.7 μM. In comparison to the pristine cotton thread-based device, the performance is significantly superior. Using a hydrophobic fabric and salt-responsive threads, a glucose-sensing headband was prepared for on-body sweat glucose monitoring. With the use of a smartphone-based image analysis system, the headband can detect the concentration of glucose in a volunteer's perspiration. Using the thread-based salt-responsive zwitterionic polymer brush might offer a novel approach to creating wearable sweat sensors with extremely high sensitivity.

A low-cost goniometer for contact angle measurements using drop image analysis: Development and validation

Contact angle measurements are a widely used method for evaluating surface wettability, but their accessibility is limited by the high cost of commercial goniometers. To address this issue, we developed a low-cost prototype goniometer using locally available materials and a smartphone-based image analysis system to measure contact angles. We validated our approach by comparing its results with those of a standard goniometer for both organic and inorganic materials. For organic samples, the accuracy is greater than 86%, and for inorganic samples, it is greater than 94%. The good agreement between the two methods demonstrates the feasibility of our proposed method for accurate contact angle measurements at a lower cost.

Semiquantitative color catcher and smartphone-based analysis of synthetic food dyes in alcohol containing beverages

Solid phase extraction, based on the use of color catcher sheets, was successfully employed for the preconcentration of food dyes from alcohol containing beverages. The photos of color catcher sheets with the adsorbed dyes were taken with a mobile phone. The smartphone-based image analysis of the photos was performed using Color Picker application. The values of several color spaces were collected. Specific values from RGB, CMY, RYB and LAB color spaces were proportional to the dye concentration in the analyzed samples. The described inexpensive, simple and elution free assay enables analysis of dyes concentration in various solutions.

Smartphone-based colorimetric detection of cardiac troponin T via label-free aptasensing

We report an aptasensing platform for the detection of cardiac troponin T (cTnT) in the immediate and early phases of acute myocardial infarction (AMI). High-flow filter paper was used to fabricate a microfluidic paper-based analytical device (μ-PAD), which was further modified with gold-decorated polystyrene microparticles functionalized with a highly specific cTnT aptamer. Herein, cTnT detection is presented in two linear ranges (0.01-0.8 μg/ml and 6.25-50 μg/ml) with an LoD of 3.9X10−4 μg/ml, which is in agreement with reference values determined by the American Heart Association. The proposed platform showed remarkable selectivity against AMI-associated cardiac biomarkers such as TNF-alpha, interleukin-6, cardiac troponin I, and reactive protein-C. This aptasensor is a label-free assay that relies only on smartphone-based image analysis and takes less processing time in comparison with traditional methods like ELISA. Furthermore, it exhibits outstanding stability over 23 days when devices are stored at 4 °C. The reported platform is a stable and cost-effective method for the on-site and user-friendly detection of cTnT in normal saline buffer and diluted human serum.

On-site colorimetric detection of Salmonella typhimurium

Rapid qualitative and quantitative detection of Salmonella typhimurium (S. typhimurium) takes an important role in ensuring food safety. Herein, a colorimetric assay aptasensor for S. typhimurium utilizing intrinsic peroxidase-like activity of gold nanoparticles embedded spherical covalent organic framework and the affinity and specificity of S. typhimurium-aptamer has been explored. This aptasensor can capture the S. typhimurium via the selective binding effect of aptamer, and the catalytically active sites were shielded. As a result, the colorimetric signals of the 3,3′,5,5′-tetramethylbenzidine-H2O2 system were turned off. Under optimum conditions, the aptasensor gave a linear response over the range of 10 to 107 CFU/mL for S. typhimurium. The detection limit of 7 CFU/mL was obtained within 45 min and was effectively applied to detect S. typhimurium in milk and lake water samples with recoveries in the range from 96.4 to 101.0%. More importantly, combined with a self-developed smartphone-based image analysis system, the proposed aptasensor can be used for point-of-care testing applications.

Purge and trap in-tube colorimetric detection method for the determination of ethanol in alcoholic and non-alcoholic beverages

• Purge and trape coupled with smartphone-based detection were for the first time introduced for ethanol analysis. • Improvements in mass transfer efficiency were achieved with low reagent consumption. • The methodology showed good reproducibility with low operational costs. • The workflow is easily performed and it is suitable for low-source countries. • A low limit of detection (0.05 %v/v) was achieved. A simple and cost-effective analytical approach based on the combination of purge and trap technique coupling with smartphone-based image analysis was developed for the sensitive detection of ethanol. Herein, the dichromate solution was used as the detection reagent to determine the ethanol concentration in alcoholic beverages. The ethanol from the sample solution was purged by the airstream and then trapped into a 1-mL Eppendorf tube containing the detection reagent. During the process, ethanol is oxidized by dichromate reagent to form ethanoic acid, and the orange color of the dichromate ion is started to become darker after one minute. The color image of the Eppendorf tube was taken by smartphone in a controlled-light box and then analyzed by the laptop ImageJ software. Experimental parameters affecting the method sensitivity, such as extraction time, stirring rate, and dichromate concentration, were studied. Under the optimal conditions, the calibration curve was linear for the ethanol concentrations ranging from 0.15 and 3.0 %v/v (R 2 >0.993). The limit of detection of 0.05 %v/v was obtained. The intra- and inter-assay results (RSD%) were less than 1.0% and 2.0%, respectively. The developed approach has been successfully applied to determine ethanol percentage in beverage samples (alcoholic beer, brandy, and non-alcoholic beer), with relative recoveries ranging from 86-112%. Finally, the accuracy was assessed by comparison of the results obtained by our method and the UV-Vis spectrophotometric method, which agreed at the 95% confidence level.

Smartphone-Based Image Analysis for Rapid Evaluation of Kiwifruit Quality during Cold Storage.

As a vitamin C–rich fruit, choosing the eating time for kiwifruit with the best quality during the shelf period is still a problem for consumers. This paper mainly focuses on the correlation between cold storage time, quality indexes, volatile flavor compounds of postharvest kiwifruit and RGB value readouts from photos taken by mobile phone. Results indicated that the R to B ratio values (Central R/B) and B to G ratio values (Central B/G) of the central site of kiwifruit were strongly associated with storage time and all quality indicators. The central R/B was negatively correlated with titratable acidity, vitamin C and 2,6-Nonadienal contents and firmness and positively correlated with storage time, weight loss, soluble solids content, total soluble sugars, total plate counts and 1,3-Cyclooctadiene. We provide a novel and smart strategy to predict the shelf life and quality parameters of kiwifruit by capturing and calculating RGB values using a smartphone.

Colorimetric Measurements of Vegetable Oils by Smartphone-Based Image Analysis

Abstract One of the most important indicators of quality of vegetable oils is colour, which can be detected with colorimetric measurements. The determination of colour is traditionally done using colorimeters, spectrometers, tintometers, and other analytical equipment. As an alternative to replace the classical analytical methods, smartphone-based colorimetry using digital image analysis can be used. For colorimetric detection of colour in vegetable oils, a Huawei P30 lite smartphone and android application “Colour Picker” with an image matching algorithm RGB model was used. The image of sample and standard solutions was captured in a polyvinyl chloride box with light-emitting diode (LED) lamps. The aim of the study was to detect the colour of vegetable oils with smartphone-based image analysis. The detected colour of eleven vegetable oils (sea buckthorn, sunflower, rice, macadamia nut, hemp, corn, grape, linseed, rapeseed, olive, and milk thistle oils) was compared with standard solutions of iodine with a concentration range from 0 to 100 mg·100 ml−1. The results show that smartphone-based colorimetry can be used for detection of the colour of vegetable oils and it is possible to compare the colour with standard solutions of iodine. The colour of vegetable oils was expressed as the colour number obtained from an iodine standard solution prepared in deionised water.

Commercially available color-catching sheets for magnetic textile solid phase extraction of water-soluble dyes

Magnetic textile solid phase extraction, based on the use of magnetically separable color-catching sheets, was successfully employed for the preconcentration of water-soluble dyes methylene blue and crystal violet from water solutions. The photos of color-catching sheet squares with the adsorbed dye were taken with a mobile phone. The computer-based image analysis of the photos was performed using ImageJ freeware while smartphone-based image analysis employed On Color Measure application. The values of saturation from HSB (hue – saturation – brightness) color space, as well as red channel values from RGB (red – green – blue) color space were proportional to the methylene blue and crystal violet concentration in the analyzed samples. This novel method has a potential to be a useful semiquantitative determination procedure for dye analysis.

Colorimetric allergenic fungal spore detection using peptide-modified gold nanoparticles

The rapid and sensitive detection of allergenic fungal spores is of great interest owing to the potentially negative impact of these spores on personal and public health and safety. We present a simple and prompt colorimetric strategy for detecting Aspergillus niger based on interactions between fungal spores and gold nanoparticles (AuNPs) modified with a specific binding peptide. The A. niger spore-binding peptide ligand was identified by phage display screening, which exhibited enhanced affinity through multivalent effects with specificity over common airborne bacteria. Immobilization of peptide ligands on AuNPs enabled rapid binding to A. niger spores, resulting in a visible change in the color intensity of the supernatant after sedimentation of the spores. This simple colorimetric approach displayed a high sensitivity of ∼50 spores and a rapid detection time of <10 min when used with a smartphone-based image analysis application. This strategy can be adapted for the simple and rapid detection of target microorganisms of relatively large size by exploiting the specificity of ligands and the optical properties of gold nanoparticles.

Smartphone-based image analysis coupled to paper-based colorimetric devices

Advancements in technology have led to the use of smartphones as biosensor detectors. However, it is difficult to obtain stable color information of colorimetric sensors using multiple smartphones owing to different light conditions and image correction operations. In this study, we attempted color detection of the colorimetric paper chip using smartphone-embedded light-emitting diode (LED) and simple transformation calculation. This method enables the acquisition of stable color information using different smartphones by reducing the influence of external light sources. Moreover, we studied characteristics such as convergence and distinction of detection result details by the manufacturers and smartphones. These findings suggested the necessity of classification criteria for the use of smartphones to achieve optimal detection. In addition, white and black references were used to set the standard for color correction of various light sources. Based on our results, we conclude that this approach presents the possibility of smartphone-based colorimetric detection in practical applications.

Smartphone-based image analysis for evaluation of magnetic textile solid phase extraction of colored compounds

Novel modern easily feasible methods for direct evaluation of a new, simple preconcentration analytical procedure have been developed. Two types of smartphone image analysis applications (ON Color Measure and Color Lab) were evaluated to obtain RGB and HSV color spaces data for the quantification of Magnetic textile solid phase extraction of colored compounds (e.g. water-soluble organic dyes). Both direct measurement of color spaces values via the smartphone camera and image analysis of the photograph can be used successfully. The obtained data were similar to those obtained by previously examined professional ImageJ software. The saturation (S) values of the HSV color space are directly proportional to the concentrations of the analyzed dye.

Urinalysis for diaper-wearing elderly people using a combination of cotton-based diagnostic devices and smartphone-based image analysis

Background: Urinary tract infection (UTI) is one of the most common bacterial infections, annually affecting 150 million people worldwide. The highest prevalence of UTI in the overall elderly population. However, practical problems have occurred in urine sampling in diaper-wearing elderly people. Our aim is to develop a new type of the in-vitro diagnostic devices based on “cotton”, which allows us to detect the nitrite concentrations in urine (i.e., biomarker for urinary tract infection). The combination of cotton-based diagnostic device and a smartphone-based image analysis would help the healthcare people early diagnose urinalysis-based diseases such as UTI, and improve the life quality in elderly populations around the world. Methods: Our diagnostic device integrated into diaper is made up with three primary parts: a test pad, a flow channel made by hydrophobic and hydrophilic cotton and plastic packaging substrates. The smartphone-based image analysis (a specific APP) solved recording issues including variances in either light or focal distance. The mean value was calculated and analyzed based on 8-bit grayscale using ImageJ software and defined as 255– [experiment zone intensity]. Results: The nitrite test color changes from colorless to purple, correlating positively to concentration (from 0.156 to 5 µM) in both test paper only and test pad integrated with diaper and the mean value is calculated and analyzed. Conclusions: Since this device is inexpensive, portable, simple, structurally integrating with diapers and functionally integrated with the smartphone-based application, it would have a wild range potential of becoming a commercially viable diagnostic system, in particular, for the daily healthcare of elderly people.

Electrogenerated chemiluminescence on smartphone with graphene quantum dots nanocomposites for Escherichia Coli detection

Graphene quantum dots (GQDs) have recently exhibited great potential in electrogenerated chemiluminescence (ECL) due to their catalyst and amplification effect towards luminophores. Here, we prepared GQDs nanocomposites to amplify the ECL signals in tris(2,2′-bipyridyl)ruthenium(II)/tripropylamine (Ru(bpy)32+/TPA) assay. Universal serial bus interface on smartphone was used as the excitation source for ECL. The luminescence signals were then captured by the smartphone camera and processed by a smartphone-based image analysis application (APP). By immobilizing layer of sensitive Escherichia coli (E.coli) antibody on the electrode surface, our smartphone-based ECL system exhibited excellent linear response towards detection of E.coli in the concentration range of 10 cfu/mL to 107 cfu/mL. Due to the vast popularity and portability of smartphone, the scope of application in our system would be able to greatly satisfy the need for point-of-care testing. Thus, in this work, the quantum dots-amplified luminescence detection was integrated with portable analytical devices, offering low-cost and real-time electrochemical analysis.

Smartphone-based image analysis and chemometric pattern recognition of the thin-layer chromatographic fingerprints of herbal materials

A Pharmacopeia-based TLC method was coupled with a smartphone app for the in-field screening of herbal materials.

Colorimetric-Luminance Readout for Quantitative Analysis of Fluorescence Signals with a Smartphone CMOS Sensor.

Smartphones have shown promise as an enabling technology for portable and distributed point-of-care diagnostic tests. The CMOS camera sensor can be used for detecting optical signals, including fluorescence for applications such as isothermal nucleic acid amplification tests. However, such analysis is typically limited mostly to end point detection of single targets. Here we present a smartphone-based image analysis pipeline that utilizes the CIE xyY (chromaticity-luminance) color space to measure the luminance (in lieu of RGB intensities) of fluorescent signals arising from nucleic acid amplification targets, with a discrimination sensitivity (ratio between the positive to negative signals), which is an order of magnitude more than traditional RGB intensity based analysis. Furthermore, the chromaticity part of the analysis enables reliable multiplexed detection of different targets labeled with spectrally separated fluorophores. We apply this chromaticity-luminance formulation to simultaneously detect Zika and chikungunya viral RNA via end point RT-LAMP (Reverse transcription Loop-Mediated isothermal amplification). We also show real time LAMP detection of Neisseria gonorrhoeae samples down to a copy number of 3.5 copies per 10 μL of reaction volume in our smartphone-operated portable LAMP box. Our chromaticity-luminance analysis is readily adaptable to other types of multiplexed fluorescence measurements using a smartphone camera.

Smartphone supported backlight illumination and image acquisition for microfluidic-based point-of-care testing.

A smartphone-based image analysis system is advantageous for point-of-care testing applications. However, the processes of observation and image recording rely heavily on an external attachment that includes additional light sources. Moreover, microfluidic point-of-care devices are highly miniaturized, and can be clearly observed only under magnification. To address these issues, the present work proposes a novel imaging box for converting the built-in light source of a smartphone into uniform backlight illumination to avoid interference arising from reflections. A multi-piece orthoscopic lens is embedded in the imaging box to enable the imaging of micro-sized samples. As such, the colorimetric signal of a microchannel with a width as small as 25 µm can be faithfully recorded. Protein concentration quantification based on the bicinchoninic acid assay method was demonstrated with the proposed smartphone/imaging box system from an analysis of colorimetric signals. In addition, a microfluidic chip for conducting ABO blood typing was fabricated, and the microscopic imaging of induced blood coagulation can be clearly observed in a 3 µL sample using the proposed system. These results highlight the potential for adopting smartphone-based analysis systems in point-of-care testing applications.