Detection of Adulteration of Tapioca Starch with Dolomite by near Infrared Hyperspectral Imaging

Abstract

Tapioca starch adulterated with dolomite is sold in markets, but this adulteration cannot be identified by normal visual inspection. Near infrared (NIR) hyperspectral imaging has been successfully used as a non-destructive method of identifying various characteristics of food, therefore it was tested to identify dolomite adulteration. Adulterated tapioca starch samples were prepared by adding dolomite in the range of 0.5-100% (wt/wt). Samples (N=400) of pure tapioca starch (0) and adulterated tapioca starch (1) were divided into calibration set (N=300) and a prediction set (N=100). All samples were scanned using NIR hyperspectral imaging (935-1720 nm) and spectra were pre-processed using Savitzky-Golay first derivative differentiation pretreatment in order to obtain the optimal conditions for establishing a classification model. Partial least squares-discriminant analysis was carried out to evaluate the accuracy of classification tapioca starch adulterated with dolomite. The results showed the total accuracy of prediction for classification was 100%. Therefore, NIR hyperspectral imaging was demonstrated to have a potential for use in detecting adulteration of tapioca starch with dolomite.

A Review of the Use of Near-Infrared Hyperspectral Imaging (NIR-HSI) Techniques for the Non-Destructive Quality Assessment of Root and Tuber Crops

“…For preprocessing, Savitzky-Golay's first derivative differentiation was utilized to create the ideal environment for the classification model. The model's classification of pure and contaminated tapioca was assessed to be 100% accurate [84]. Although there are many practical applications using NIR-HSI for other root and tuber crops, especially potato and sweet potatoes (Table 1), only a few studies were reported on using NIR-HSI for quality characterization of cassava and yam tubers.…”

Research and Application of Several Key Techniques in Hyperspectral Image Preprocessing

“…The black-and-white correction method (Esfahani et al, 2020;Xin et al, 2020) is the most widely used method for the correction of noise in dark currents. Because the hyperspectral image is a two-dimensional image in the spatial dimension, the individual bands can be denoised using classical image denoising methods; the spectral dimension is often denoised using Savitzky-Golay (SG) filtering (Wang et al, 2019;Ayaz et al, 2020;Jiang et al, 2020;Khamsopha and Teerachaichayut, 2020;Li et al, 2020;Ye et al, 2020).…”