Rapid Detection and Quantification of Aflatoxin B1 in Milk Using Fourier Transform Infrared Spectroscopy
By: Jha, Shyam Narayan
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Contributor(s): Jaiswal, Pranita.
Publisher: New York Springer 2021Edition: Vol.102(1), March.Description: 259-266p.Subject(s): Civil EngineeringOnline resources: Click here
In:
Journal of the institution of engineers (India): Series ASummary: A Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis was developed to detect and quantify the contamination of aflatoxin B1 (AFB1) in pure milk. FTIR spectra of milk spiked with known AFB1 concentrations (viz. 10, 20, 30, 40 and 50 ppb) were acquired which revealed differences in absorption between pure and contaminated milk samples, specifically in the wavenumber range of 1800–1331 cm−1. Principal component analysis showed distinct segregation and clustering of AFB1 contaminated milk samples at 5% level of significance. Soft independent modelling by class analogies was used to assess the feasibility of detecting AFB1 in pure milk, and developed models could successfully classified contaminated with the pure milk samples. AFB1 concentration in milk was best predicted in the spectral range of 1484–1423 cm−1 using partial least square and multiple linear regression with coefficient of determination of 0.92, 0.90 and 0.97, 0.92 for calibration and validation, respectively.
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Articles Abstract Database
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2021-2022082 |
A Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis was developed to detect and quantify the contamination of aflatoxin B1 (AFB1) in pure milk. FTIR spectra of milk spiked with known AFB1 concentrations (viz. 10, 20, 30, 40 and 50 ppb) were acquired which revealed differences in absorption between pure and contaminated milk samples, specifically in the wavenumber range of 1800–1331 cm−1. Principal component analysis showed distinct segregation and clustering of AFB1 contaminated milk samples at 5% level of significance. Soft independent modelling by class analogies was used to assess the feasibility of detecting AFB1 in pure milk, and developed models could successfully classified contaminated with the pure milk samples. AFB1 concentration in milk was best predicted in the spectral range of 1484–1423 cm−1 using partial least square and multiple linear regression with coefficient of determination of 0.92, 0.90 and 0.97, 0.92 for calibration and validation, respectively.
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