MULTIVARIATE IMAGE ANALYSIS IN CHEMISTRY: pH MEASUREMENTS OF DRINKING WATER

Damasceno, Deangelis; Toledo, Thiago Gomes; Godinho, Mariana da Silva; Silva, Cassiano P. da; Oliveira, Sérgio Botelho de; Oliveira, Anselmo E. de

doi:10.5935/0100-4042.20150082

Cited by 12 publications

(14 citation statements)

References 4 publications

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“…The use of white light enables the differentiation between different tones, hues, and shades when histograms are constructed from a digital image. Common sources include fluorescent lamps (either external or internal to a scanner 15,21,25,28,32,[34][35][36][37][38][39][42][43][44]46,48,49,[54][55][56][57] ) and white-light LED (light-emitting diode) lamps 26,27,30,33,40,41,45,47,58,59 or LED strips, 17,31,50 and they must be suitably disposed in the system in order to avoid shadows and illumination gradients under the ROI. Ultraviolet (UV) lamps, 18,51 near infrared (NIR) LEDs, 29 internal flash lamp, 52,61 white-light-transilluminator, 53 and luminoscope 60 have been also used.…”

Section: Instrumentation For Cachasmentioning

confidence: 99%

Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

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This review systematizes for the first time the here called "Chemometricsassisted color histogram-based analytical systems" under the acronym CACHAS. A comprehensive discussion of the fundamentals, general characteristics, and applications are presented in order to direct practical aspects for developing methods that use color histograms as input data for the construction of chemometric models. For this, analytical information is rapidly acquired using a simple image acquisition device (such as digital camera, webcam, scanner, or smartphone), without need for any image processing, other than extraction of the histograms, which are constructed by counting the frequency distribution of the different color tones (conveniently specified through a color space) of all pixels delimited by a region of interest in a digital image. As a consequence, CACHAS have been increasingly used for qualitative and quantitative purposes in food, agricultural, forensic, biomedical, and microbiological analysis, reinforcing the principles of green analytical chemistry.

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Section: Instrumentation For Cachasmentioning

confidence: 99%

Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

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“…Atualmente, muitos métodos quantitativos foram propostos utilizando imagens digitais obtidas com smartphones e scanners, 22 bem como, inúmeras práticas de ensino. [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] .…”

Section: Introductionunclassified

Quantitation of Vitamin C in Supplements Using Titrimetric, Molecular Absorption Spectroscopy and Digital Imagens

Silva¹,

Pedroso²,

Jesus³

et al. 2019

Rev. Virtual Quim.

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In this research, it was presented a laboratory class where titrimetric and colorimetric methods were used to determine vitamin C levels in supplement pills. In the first part, vitamin C levels were measured in supplement pills using three titrimetric methods, back titration with sodium thiosulphate (Na2S2O3), direct titrations with potassium iodate (KIO3) and iodide (I2). Results obtained with trimetric methods were equivalent at 95 % confidence interval, methods were compared using one-way ANOVA). In the second part, a quick and low-cost colorimetric method was carried out. It was successfully used to measure vitamin C levels in supplement pills. It consists in reduction of the complex Fe 3+ and 1,10phenanthroline by vitamin C to form a reddish-orange colored complex that was measured at 510 nm. The colorimetric method was also carried out using digital images obtained with a flatbed scanner. RGB values were extracted from digital images using ImageJ's plugin ReadPlate in a simple and easy manner. The t paired test had shown that both methods were equivalent at 95 % confidence interval.

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“…Damasceno e colaboradores utilizaram a análise multivariada de imagens para estimar o pH de amostras de água potável a partir da mistura das amostras com o reagente azul de bromotimol e aplicação das informações do sistema RGB em modelo de calibração por mí-nimos quadrados parciais. 13 Lima et al introduziram a combinação de imagens digitais, obtidas por uma webcam, com um mini-sistema fluxo-batelada. O sistema foi aplicado para a determinação de ácido tânico em chá-verde, sendo obtidos resultados que demonstraram um desempenho analítico satisfatório, além de permitir uma redução significativa no consumo de reagentes e amostras, assim como a diminuição na geração de resíduos.…”

Section: Introductionunclassified

Classification of Mineral Waters Based on Digital Images Acquired by Smartphones

Neto¹,

Fonseca²,

Braga³

2016

Química Nova

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publicado na web em 25/05/2016 CLASSIFICATION OF MINERAL WATERS BASED ON DIGITAL IMAGES ACQUIRED BY SMARTPHONES. This work describes a new procedure for classification of mineral waters based on digital images acquired by smartphones. Commercial waters from eight mineral springs plus distilled water and tap water were combined with eriochrome T black or murexide and transferred to a cuvette, which was positioned into a light controlled chamber. RGB (Red, Blue and Green) measurements of cuvette images were acquired in real time, using a free smartphone app, and employed as variables for the exploratory analysis. 2D data dispersion along component B for murexide (x axis) and component R for eriochrome T black (y axis) provides the clear visualization of clusters using the raw variables. Hierarchical cluster analysis (HCA) applied to this data confirmed the efficient discrimination of samples providing the characterization of nine clusters for the ten classes of water investigated. The classification of samples based on a k-nearest neighbors (k-NN) modelled to the efficiency rate of 100% for 8 classes and of 94.4% and 50% for the remaining classes, respectively, indicating the adequate performance of the proposed strategy. Considering the facilities to acquire the data, such as low cost instrumentation and reagents, and the rapidity of the procedures, this alternative may be applied for verification of commercial water adulteration.Keywords: smartphone; mineral waters; colorimetry; exploratory analysis. INTRODUÇÃOO uso de imagens digitais como ferramenta para análises químicas tem sido amplamente explorado nos últimos anos.1 Empregandose imagens obtidas por câmeras fotográficas, scanners, webcams ou telefones celulares, conhecidos como smartphones, é possível realizar determinações qualitativas e quantitativas com desempenho adequado, sem a necessidade de instrumentos como espectrofluorímetros ou espectrofotômetros.2-4 De fato, a literatura relata que, utilizando informações simples das imagens, como os valores de cores usualmente baseadas no sistema RGB (do inglês Red, Blue e Green) consegue-se obter resultados analíticos similares àqueles adquiridos com instrumentação já bem estabelecida, caracterizando esta estratégia em uma alternativa de menor custo para a realização de determinadas medidas instrumentais.Ao se considerar as aplicações analíticas que podem ser conduzidas por meio de imagens digitais, merece destaque aquelas que envolvem a identificação de substâncias ou a discriminação/ classificação de amostras baseadas em medidas colorimétricas. 5Neste sentido, arranjos com sensores contendo diferentes reagentes colorimétricos imobilizados sobre filmes poliméricos ou de papel têm sido aplicados com sucesso na resolução de muitos desafios analíticos, como a discriminação de explosivos ou de aminas e a identificação de substâncias de interesse variado como compostos orgânicos voláteis, produtos químicos tóxicos ou aromatizantes do café.6-11 Na maioria destas aplicações, imagens do arranjo de sensores, obtidas a...

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MULTIVARIATE IMAGE ANALYSIS IN CHEMISTRY: pH MEASUREMENTS OF DRINKING WATER

Cited by 12 publications

References 4 publications

Chemometrics‐assisted color histogram‐based analytical systems

Chemometrics‐assisted color histogram‐based analytical systems

Quantitation of Vitamin C in Supplements Using Titrimetric, Molecular Absorption Spectroscopy and Digital Imagens

Classification of Mineral Waters Based on Digital Images Acquired by Smartphones

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