Smartphone application-based colorimetric fish freshness monitoring using an indicator prepared by rub-coating of red cabbage on paper substrates

食物腐败 pH指示剂 红卷心菜 RGB颜色模型 肉眼 涂层 计算机科学 化学 食品科学 环境科学 材料科学 色谱法 纳米技术 渔业 生物 人工智能 有机化学 遗传学 检出限 细菌
作者
K. P. Chaithra,T. P. Vinod,Prasiddha Nagarajan
出处
期刊:Colloids and Surfaces A: Physicochemical and Engineering Aspects [Elsevier BV]
卷期号:679: 132553-132553 被引量:19
标识
DOI:10.1016/j.colsurfa.2023.132553
摘要

This work developed a simple, easy-to-prepare, and inexpensive indicator (R-Paper) based on rub-coating of red cabbage on readily available paper substrates to detect the freshness of fish in out-of-lab settings. A single-step rub-coating method was used to incorporate anthocyanins on paper substrates, without the extraction of the compound from red cabbage. The preparation of the indicator and its usage is quick and does not require additional chemicals, personnel expertise, or laboratory facilities. The functional colorimetric interface created by directly rubbing red cabbage on paper was used for fish quality monitoring, which displayed a naked-eye detectable color change from purple (for fresh fish) to blue (for spoiling fish) and then to blue-green (for spoiled fish), corresponding to total volatile basic nitrogen (TVB-N) and pH changes. To provide a user-friendly quantitative analysis of this color change, we used the free Android software Color Grab to quantify the color using L* , a* , b* , and RGB indices. To the best of our knowledge, this work is the first report on an indicator prepared by rub-coating red cabbage onto paper-based substrates for fish spoilage monitoring through smartphone-based analysis. To verify that the R-Paper indicator performs on a par with the indicators using extracted anthocyanins, its performance was compared with indicators prepared using anthocyanins extracted from red cabbage (AR-Paper). Naked-eye analysis, simple preparation, ease of use, low cost, and free smartphone-based analysis make the R-Paper indicator an appropriate food quality indicator in resource-limited areas.
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