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Use of near infrared hyperspectral imaging as a nondestructive method of determining and classifying shelf life of cakes
Author(s)
Date Issued
January 1, 2021
Type
Article
Abstract
Many types of cake deteriorated rapidly due to microbial infection, which gives them a short shelf life. Accordingly, near-infrared hyperspectral imaging (NIR-HSI), in the range of range of 935–1720 nm, was tested to determinate whether it could be used as a nondestructive method to determine the shelf life and classify cakes based on microorganism infections during storage. The average spectrum from a region of interest (ROI) in the spectral image of each sample was acquired by NIR-HSI. Partial least squares regression (PLSR) was used to establish the model in order to predict storage time of sponge cakes. The model proved accurate with a correlation coefficient (R) of 0.835 and the root mean square error of prediction (RMSEP) of 1.242 days. Partial least squares discriminant analysis (PLS-DA) was applied to establish the classification model for distinguishing between non-expired and expired of sponge cakes. The results showed the accuracy of prediction was 91.3%. The predictive images showed different colors based on their storage time that could be inspected visually. Therefore NIR-HSI was shown to have potential to be used for predicting storage time of cakes and classifying cakes into expired and non-expired, which has potential for application in the bakery industry.
Citation
Lwt, 136, 2021