Abstract
Economical to a fault, coconut oil is a commodity related to fraudulent activities such as oil adulteration for undue profits. Unfortunately, the conventional methods used in the detection of adulteration and toxicants are laborious, destructive, and time-consuming. Hence, it is imperative to engineer a non-destructive and rapid screening test with sufficient accuracy. To that end, the proposed work has an in-house developed imaging system hardware and a method to estimate relevant quality parameters from multispectral imagery. Multispectral images of adulterated coconut oil were analyzed through a cascade of statistical algorithms: Fisher Discriminant Analysis and Bhattacharyya distance respectively. In this work, a functional relationship was developed for the estimation of adulteration level that recorded an R2 of 0.9876 for the training samples and an MSE of 0.0029 for the testing samples. Besides, the proposed imaging system offers flexibility on post-processing of raw measurements as the algorithm is designed to operate from raw multispectral images. In addition, the developed imaging system is economical in its capacity to estimate the adulteration of coconut oil with remarkable accuracy considering the low cost of production. Moreover, the proposed work validates the use of multispectral imagery as an initial screening technique instead of expensive spectroscopy methods.
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Availability of data and material
The datasets analyzed during the current study are available in the Mendeley repository, https://data.mendeley.com/datasets/38sgxwkrrd/1.
Code availability
The code is available in the supplementary materials.
Abbreviations
- ATR:
-
Attenuated total reflectance
- FDA:
-
Fisher discriminant analysis
- IC:
-
Intergrated circuit
- LDA:
-
Linear discriminant analysis
- LED:
-
Light emitting diode
- MSI:
-
Multispectral imaging
- MSE:
-
Mean squared error
- PCA:
-
Principal component analysis
- PLS:
-
Partial least squares
- RBD:
-
Refined-bleached-and-deodorized
- SVM:
-
Support vector machines
- UART:
-
Universal asynchronous receiver-transmitter
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Acknowledgements
Silver Mills Group, Meerigama is acknowledged for supplying coconut oil. The authors acknowledge the assistance of Ms. E.G.T.S. Wijethunga, Department of Food Science and Technology, University of Peradeniya, Sri Lanka.
Funding
University of Peradeniya, Sri Lanka research grant (Research Grant No: URG/2017/26/E).
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SH, KW, YR, and CB conceived, carried out the experiments and wrote the manuscript; VR, RG, MP, and TM supervised the work and edited the manuscript.
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Herath, S., Weerasooriya, H.K., Ranasinghe, D.Y.L. et al. Quantitative assessment of adulteration of coconut oil using transmittance multispectral imaging. J Food Sci Technol 60, 1551–1559 (2023). https://doi.org/10.1007/s13197-023-05697-0
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DOI: https://doi.org/10.1007/s13197-023-05697-0