Nondestructive detection for adulteration of panax notoginseng powder based on hyperspectral imaging combined with arithmetic optimization algorithm‐support vector regression

Journal of Food Process Engineering(2022)

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Abstract
Illegal merchants adulterate the powder of panax notoginseng rhizome and main root with the powder of panax notoginseng fibrous root, which reduces the efficacy and hygiene of panax notoginseng powder. To detect the adulteration of panax notoginseng powder nondestructively and rapidly, in this study, the hyperspectral images of 80 samples of adulterated rhizome powder and adulterated main root powder (AR & AM) were collected by using a hyperspectral image acquisition system (400-1000 nm). Then, Savitzky-Golay and standard normalized variable (SG-SNV) were used to preprocess the spectrum and improve the signal-to-noise ratio of the data. Next, competitive adaptive reweighed sampling (CARS) and iteratively retains informative variables (IRIV) methods were respectively adopted to select feature wavelengths from the spectra data after pretreatment. Subsequently, support vector regression (SVR) was used to establish the prediction models based on the selected variables and the full spectra data. Also, the arithmetic optimization algorithm (AOA) was used to optimize the parameters of the SVR model. The results showed that CARS-AOA-SVR was the optimal model for AR & AM, achieving RP2$$ {\mathrm{R}}_{\mathrm{P}}<^>2 $$ of .9693 and .9667, RMSEP of .0266 and .0264, respectively. Therefore, the hyperspectral imaging combined with the CARS-AOA-SVR is a feasible method to detect the adulteration concentration of panax notoginseng powder. Practical Applications The traditional detection methods for adulteration of panax notoginseng powder depended on manual detection and chemical analysis. In order to detect the adulterated concentration of panax notoginseng powder rapidly and accurately, the adulterated panax notoginseng powder was studied based on hyperspectral imaging. The results showed that hyperspectral imaging combined with CARS-AOA-SVR model could be used to quantitatively detect the adulteration concentration of panax notoginseng powder, which could be a fast, accurate, and nondestructive method for adulteration detection of panax notoginseng powder and other powdery materials.
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Key words
adulteration detection,arithmetic optimization algorithm,hyperspectral imaging,Panax notoginseng powder,support vector regression
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