Smartphone digital image colorimetry combined with solidification of floating organic drop-dispersive liquid-liquid microextraction for the determination of iodate in table salt

Caleb, Jude; Alshana, Usama; Ertaş, Nusret

doi:10.1016/j.foodchem.2020.127708

Cited by 32 publications

(10 citation statements)

References 36 publications

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“…DBP-DIT has explored the practicality of learning a material model for a latex material directly from digital image correlation (DIC) data ( Fan et al, 2021 ). The suggested technique has shown that the learned solution operators substantially outperform the traditional constitutive model ( Caleb et al, 2021 ). The primary goal is to research and enhance the current image analysis for new applications, including 3D applications where appropriate ( Lürig et al, 2021 ).…”

Section: Summary Of Digital Image Technologymentioning

confidence: 99%

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Chen

et al. 2022

Front. Genet.

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Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today’s microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized via digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%.

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Section: Summary Of Digital Image Technologymentioning

confidence: 99%

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Chen

et al. 2022

Front. Genet.

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“…Moreover, as an alternative to conventional chromatography, the detection of analytes using digital image measurements (DIM) has emerged as an increasingly viable and practical strategy. [59][60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78] DIMs are based on colorimetric analysis by scanning images on electronic devices such as smartphones and digital cameras. Compared to digital cameras, smartphones are easily operable, lightweight, portable, and widely used for image capture.…”

Section: Introductionmentioning

confidence: 99%

Development of an Environmentally Friendly Extraction Method Using Smartphone-Based Digital Images for the Determination of Total Sulfonamides in Meat Samples

Maroubo¹,

Melchert²

2023

J. Braz. Chem. Soc.

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Sulfonamides (SAs) are low-cost synthetic antimicrobials widely used in veterinary and human medicine to treat diseases and prevent infections. However, long periods of exposure to sulfonamides can cause adverse effects such as allergic reactions. This work aims to study dispersive solid-liquid microextraction as an alternative method for extracting total SAs in meat samples. The procedure uses a colorimetric reaction based on the formation of a pink compound (imine salt) to determine total sulfonamides (sulfamethazine, sulfadimethoxine, sulfathiazole) with digital measurements. A linear response was observed between 33-233 μg kg-1 for total sulfonamides, and the coefficient of variation (n = 11; 67 μg kg-1 of total SAs) and the limit of detection were estimated to be 0.63% and 10 μg kg-1, respectively. For a 750 mg meat sample, 0.11 mg of 4-dimethylaminocinnamaldehyde, 2.60 mg of sodium dodecyl sulfate, and 275 μL of 1-butanol were consumed per sample, and consequently, generating only 335 μL of residue. Besides this, addition-recovery tests were performed, resulting in a 71-100% recovery range, indicating the trueness of the proposed method.

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“…On-site quantitative detection shows great demand in many areas, including clinical diagnostics [1][2][3], environmental monitoring [4,5], and food analysis [6,7]. The quantitative detection methods used in the laboratory include spectrophotometry [8], colorimetry [9], fluorometry [10], electrochemistry [11][12][13][14], high-performance liquid chromatography [15], and gas chromatography [16]. Among these methods, electrochemistry has received considerable attention because of its advantages of high sensitivity, low cost, rapid detection, and little sample consumption.…”

Section: Introductionmentioning

confidence: 99%

Smartphone‐based Electrochemical On‐site Quantitative Detection Device for Nonenzyme Lactate Detection

Zhang

Wei

et al. 2022

Electroanalysis

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On‐site quantitative detection provides the opportunity for accurate and timely health care, clinical diagnosis, environmental monitoring, and food analysis. A variety of portable electrochemical detection instruments have been developed at present for on‐site quantitative detection use, including commercially available portable potentiostats, but the reality is that these electrochemical detection devices still have the problem of narrow output voltage range and detection current range, and their performance of output voltage resolution and detection current resolution is still unsatisfactory. The narrow voltage or current range makes it difficult for some chemical reactions with peaks outside the range to proceed, and the insufficiency of voltage resolution and detection current resolution are key parameters restricting the detection accuracy of existing devices. In this regard, it is urgent to carry out partial transformation of the existing device to increase the use range and detection accuracy of the device. In the current work, a smartphone‐based electrochemical on‐site quantitative detection device was developed. The device comprises a portable small potentiostat, a smartphone equipped with a specially designed Android electrochemical detection application, and a disposable sensor (NiONP modified screen‐printed electrode [SPE]). The potentiostat can realize electrochemical detection methods, including cyclic voltammetry, chronoamperometry, and differential pulse voltammetry. In addition, the potentiostat can output a potential range −2.047∼+2.047 V with a current detection sensitivity scale 1×10−8∼1×10−3 A, and the current detection range could reach ±10 nA∼±10 mA. Most importantly, the current detection resolution of the potentiostat can reach 0.003 % (3.125 pA on ±10 nA range). The smartphone was used for communicating with the potentiostat, setting detection parameters, and mapping voltammograms in real time. The SPE was modified with nickel oxide nanoparticles and perfluorinated resin solution, which were employed as sensors to convert and amplify the electrochemical current response during the on‐site quantitative detection. Results indicated that the device features excellent performance for the lactate detection. The device covered a linear range 0.1∼30 mM on lactate detection with the correlation coefficient (R2) reaching 0.997.

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Smartphone digital image colorimetry combined with solidification of floating organic drop-dispersive liquid-liquid microextraction for the determination of iodate in table salt

Cited by 32 publications

References 36 publications

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Mathematical model and genomics construction of developmental biology patterns using digital image technology

Development of an Environmentally Friendly Extraction Method Using Smartphone-Based Digital Images for the Determination of Total Sulfonamides in Meat Samples

Smartphone‐based Electrochemical On‐site Quantitative Detection Device for Nonenzyme Lactate Detection

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