Determination of acrylamide in toasts using digital image colorimetry by smartphone

Sáez-Hernández, Roberto; Ruiz, Pablo D.; Mauri-Aucejo, Adela R.; Yusà, Vicent; Cervera, M. Luisa

doi:10.1016/j.foodcont.2022.109163

Cited by 15 publications

(6 citation statements)

References 33 publications

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“…Similarly, using a simple, inexpensive lab-made apparatus, SDIC was employed to determine the amount of protein (in milk, lentils, and beans) [58], sterols in vegetable oils [59], and alkaline phosphatase in raw milk samples [70]. Furthermore, the applicability of SDIC to detect contaminants and adulterants in complex food matrices has been reported [71][72][73].With the proliferation of smartphones in low-and middle-income countries and the rapid advances in SDIC's analytical applications, SDIC holds a high prospect of providing an accessible approach for analytical measurements across different disciplines in resource-limited settings for research and pedagogical uses.…”

Section: Application Of Smartphone Digital Image Colorimetrymentioning

confidence: 99%

Smartphone Digital Image Colorimetry: An Affordable Easy-To-Use Approach for Hands-On Training in Resource-Limited Settings

Markus,

Paul,

Marks

et al. 2024

Preprint

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Analytical instruments used for scientific research and education are often expensive. This limitation poses a challenge for schools and educators in low-income countries to provide practical science training to students. To address this problem, the improvisation of analytical instruments and instructional materials has emerged as a viable solution. By incorporating practical experiments into science education, students have the opportunity to engage directly with scientific instruments, conduct investigations, and collect data. This hands-on approach fosters a deeper understanding of scientific principles, enhances critical thinking skills, and cultivates scientific mindsets among students. Herein, we review and discuss, step-by-step, the approach of using a smartphone for quantitative analysis, referred to as smartphone digital image colorimetry (SDIC). SDIC, with its practicality and accessibility, utilizes smartphone digital cameras for image acquisition and the freely available image processing programs, such as ImageJ and smartphone Apps, for image quantification. Using SDIC can enable students in low-income countries to develop essential scientific skills, including critical thinking, data interpretation, and an evidence-based approach to scientific research. By leveraging the ubiquity and affordability of smartphone technology, SDIC offers an accessible and cost-effective approach to practical science education, bridging the gap between theory and practice in resource-constrained settings.

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Section: Application Of Smartphone Digital Image Colorimetrymentioning

confidence: 99%

Smartphone Digital Image Colorimetry: An Affordable Easy-To-Use Approach for Hands-On Training in Resource-Limited Settings

Markus,

Paul,

Marks

et al. 2024

Preprint

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“…Second, the heat reaction of protein and amino acids can also generate AA (Figu 1b). The proteins in coffee, particularly aspartic acid, were degraded to free amino acid Then, aspartic acid underwent decarboxylation and deamination to form AA under hig temperature conditions [1,26]. Given that extremely high temperatures are applied durin First, lipid reactions are an important indicator affecting the quality of coffee and could lead to the production of AA (Figure 1a).…”

Section: Pathway Of Aa Formation In Coffeementioning

confidence: 99%

“…The proteins in coffee, particularly aspartic acid, were degraded to free amino acids. Then, aspartic acid underwent decarboxylation and deamination to form AA under hightemperature conditions [1,26]. Given that extremely high temperatures are applied during coffee roasting, the amino acids also participate in the formation of melanoidins, which contribute to the black color of coffee.…”

Section: Pathway Of Aa Formation In Coffeementioning

confidence: 99%

Production and Inhibition of Acrylamide during Coffee Processing: A Literature Review

Cao

2023

Molecules

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Coffee is the third-largest beverage with wide-scale production. It is consumed by a large number of people worldwide. However, acrylamide (AA) is produced during coffee processing, which seriously affects its quality and safety. Coffee beans are rich in asparagine and carbohydrates, which are precursors of the Maillard reaction and AA. AA produced during coffee processing increases the risk of damage to the nervous system, immune system, and genetic makeup of humans. Here, we briefly introduce the formation and harmful effects of AA during coffee processing, with a focus on the research progress of technologies to control or reduce AA generation at different processing stages. Our study aims to provide different strategies for inhibiting AA formation during coffee processing and investigate related inhibition mechanisms.

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“…However, Foods 2023, 12, 1896 2 of 15 visual colorimetry is less accurate than photoelectric colorimetry because it is difficult to distinguish subtle color differences by observing the target color level with the naked eye [13]. Nowadays, the combination of colorimetric methods, image acquisition tools (such as cell phones, cameras, and scanners), and processing software (such as Adobe Photoshop [14], Image J [15], MATLAB [16], Pantone Studio [17], etc.) provides a new method for simple and accurate colorimetric detection, which can eliminate the subjective error of the observer and further improve the accuracy of visual observation in the field [18].…”

Section: Introductionmentioning

confidence: 99%

Visual Colorimetric Detection of Edible Oil Freshness for Peroxides Based on Nanocellulose

Jiang

Cheng

Yang

et al. 2023

Foods

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Traditional methods for evaluating the edibility of lipids involve the use of organic reagents and complex operations, which limit their routine use. In this study, nanocellulose was prepared from bamboo, and a colorimetric reading strategy based on nanocellulose composite hydrogels was explored to monitor the freshness of edible oils. The hydrogels acted as carriers for peroxide dyes that changed color according to the freshness of the oil, and color information was digitized using UV-vis and RGB analysis. The sensitivity and accuracy of the hydrogel were verified using H2O2, which showed a linear relationship between absorbance and H2O2 content in the range of 0–0.5 and 0.5–11 mmol/kg with R2 of 0.9769 and 0.9899, respectively, while the chromatic parameter showed an exponential relationship with R2 of 0.9626. Surprisingly, the freshness of all seven edible oil samples was correctly identified by the hydrogel, with linear correlation coefficients greater than 0.95 in the UV-vis method and exponential correlation coefficients greater than 0.92 in the RGB method. Additionally, a peroxide value color card was established, with an accuracy rate of 91.67%. This functional hydrogel is expected to be used as a household-type oil freshness indicator to meet the needs of general consumers.

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Determination of acrylamide in toasts using digital image colorimetry by smartphone

Cited by 15 publications

References 33 publications

Smartphone Digital Image Colorimetry: An Affordable Easy-To-Use Approach for Hands-On Training in Resource-Limited Settings

Smartphone Digital Image Colorimetry: An Affordable Easy-To-Use Approach for Hands-On Training in Resource-Limited Settings

Production and Inhibition of Acrylamide during Coffee Processing: A Literature Review

Visual Colorimetric Detection of Edible Oil Freshness for Peroxides Based on Nanocellulose

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