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dc.contributor.authorSingh, H.-
dc.contributor.authorSingh, G.-
dc.contributor.authorKaur, N.-
dc.contributor.authorSingh, N.-
dc.date.accessioned2021-12-19T10:16:15Z-
dc.date.available2021-12-19T10:16:15Z-
dc.date.issued2021-12-19-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3326-
dc.description.abstractDespite the existing rapid and reliable analytical methods for determining biogenic amine in food matrices, recently special efforts have been devoted for development of portable and inexpensive devices for discrimination of biogenic amines (BAs) in food products to achieve onsite detection of food-spoilage. Thus, in this context, a field deployable cross-reactive sensor array and a field-portable array reader has been developed for determination of food quality. The sensor array consisting of metal complexes (C1 – C11) of single azophenol dye-based receptor generated a unique visible response on interaction with different amines (A1 – A7). Further, the colorimetric pattern and discrimination efficacy of the sensor array was evaluated using multivariate statistical techniques such as principal component analysis and linear discriminant analysis. Motivated by outstanding discriminatory power of sensor array, titration experiment was performed with BAs, and colorimetric response of array was linearly corelated to concentrations of BAs such as tryptamine and spermine with R2 values of 0.9596 and 0.967 respectively. Finally, for practical utility and the field analysis, a portable reader was developed and utilized for quantification of biogenic amines in meat and cottage cheese samples spiked with spermine and tryptamine up to the concentrations of 40 μM; therefore, apparently proving the potential applicability of the designed sensing method for food quality monitoringen_US
dc.language.isoen_USen_US
dc.subjectColorimetric arrayen_US
dc.subjectMultivariate analysisen_US
dc.subjectBiogenic aminesen_US
dc.subjectFood spoilageen_US
dc.subjectPrincipal component analysisen_US
dc.subjectSimultaneous estimationen_US
dc.titlePattern-based colorimetric sensor array to monitor food spoilage using automated high-throughput analysisen_US
dc.typeArticleen_US
Appears in Collections:Year-2022

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