Adampourezare Mina, Nikzad Behzad, Sajedi-Amin Sanaz, Rahimpour Elaheh
Research Center of Bioscience and Biotechnology, University of Tabriz, Tabriz, Iran.
Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
BMC Chem. 2024 Apr 22;18(1):80. doi: 10.1186/s13065-024-01181-8.
In the current work, a rapid, simple, low-cost, and sensitive smartphone-based colorimetric sensor array coupled with pattern-recognition methods was proposed for the determination and differentiation of some organic and inorganic bases (i.e., OH, CO, PO, NH, ClO, diethanolamine, triethanolamine) as model compounds. The sensing system has been designed based on color-sensitive dyes (Fuchsine, Giemsa, Thionine, and CoCl) which were used as sensor elements. The color changes of a sensor array were observed by the naked eye. The color patterns were recorded using digital imaging in a three-dimensional (red, green, and blue) space and quantitatively analyzed with color calibration techniques. Distinctive colorimetric patterns for target bases via linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA) were observed. The results indicated that the analytes related to each class (at the different concentration levels in the range of 0.001-1.0 mol L) were clustered together in the canonical discriminant plot and HCA dendrogram with high sensitivity and an overall precision of 85%. Furthermore, the first function factor of LDA correlated with the concentration of each target analyte in a correlation coefficient (R) range of 0.864-0.996. These described procedures based on the colorimetric sensor array technique could be a promising candidate for practical applications in package technology and facile detection of pollutants.
在当前工作中，提出了一种基于智能手机的快速、简单、低成本且灵敏的比色传感器阵列，并结合模式识别方法，用于测定和区分一些有机和无机碱（即OH、CO、PO、NH、ClO、二乙醇胺、三乙醇胺）作为模型化合物。传感系统基于用作传感器元件的颜色敏感染料（品红、吉姆萨、硫堇和CoCl）进行设计。通过肉眼观察传感器阵列的颜色变化。使用数字成像在三维（红、绿、蓝）空间中记录颜色模式，并采用颜色校准技术进行定量分析。通过线性判别分析（LDA）和层次聚类分析（HCA）观察到目标碱的独特比色模式。结果表明，与每个类别相关的分析物（在0.001 - 1.0 mol L范围内的不同浓度水平）在典型判别图和HCA树状图中聚集在一起，具有高灵敏度且总体精度为85%。此外，LDA的第一功能因子与每个目标分析物的浓度在相关系数（R）范围为0.864 - 0.996时相关。这些基于比色传感器阵列技术所描述的程序在包装技术和污染物的便捷检测的实际应用中可能是一个有前景的候选方法。
