Determination of invert syrup adulterated in acacia honey by terahertz spectroscopy with different spectral features

Li, Wen; Zhang, Yuying; Li, Ming; Han, Dong

doi:10.1002/jsfa.10202

Cited by 19 publications

(5 citation statements)

References 43 publications

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“…The successive projections algorithm (SPA) is a forward variable selection method, and it is used to reduce the collinearity of different variables (Liu et al 2020). In the SPA process, the maximum number of selected variables is first set, and an initial vector (M is the original variable) is chosen in the m-dimensional space.…”

Section: Modeling Methodsmentioning

confidence: 99%

Identification of different parts of Panax notoginseng based on terahertz spectroscopy

Li¹,

Han²,

Hui-zhou³

et al. 2022

J Anal Sci Technol

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In this paper, the combined terahertz time-domain spectroscopy (THz-TDS) and chemometrics method is proposed to identify four different parts of Panax notoginseng rapidly and nondestructively. The research objects of the taproot, scissor, rib, and hairy root of P. notoginseng are taken. The refractive index, absorption coefficient, time-domain, and frequency-domain spectra of the samples are analyzed. It is found that the terahertz spectra of different parts of P. notoginseng are significantly different, so the absorption coefficient of samples is selected to establish models. Firstly, the baseline correction, multiple scattering correction, and normalization algorithms are used to preprocess the absorption coefficient in 0.5–2.0 THz to remove noise. Then, the Kennard–Stone (KS) algorithm is used to divide the model set and the prediction set at the ratio of 3:1, and the successive projection algorithm (SPA) is used to select the characteristic frequency points of the samples. Finally, the chosen characteristic variables are input into the support vector machine (SVM) and linear discriminant analysis (LDA) algorithm to establish the qualitative analysis models, respectively. In the SPA-SVM models, the performance of the SPA-SVM model under the linear kernel function by baseline is best, the accuracy of the training set of it is 99.50%, and the accuracy of the test set of it is 99.25%. In the SPA-LDA models, the performance of the SPA-LDA model by baseline is best, and the accuracy of the training set of it is 100%, and the accuracy of the test set of it is 100%. And the value of cumulative variance contribution is proposed to assess whether the variable is good or bad to model. The results show that the combined THz-TDS and chemometrics method can be used to realize rapid, accurate, and nondestructive identification of different parts of P. notoginseng.

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Section: Modeling Methodsmentioning

confidence: 99%

Identification of different parts of Panax notoginseng based on terahertz spectroscopy

Li¹,

Han²,

Hui-zhou³

et al. 2022

J Anal Sci Technol

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“…Where, Pij is the component ij of the normalized GLCM, N is the total number of gray levels in the image, N-1 is the limit of the comparative analysis of the system of interest, σ is the mean of the system with defined boundaries, and σ2 is the fluctuation of pixels (Liu et al, 2020).…”

Section: Gray-scale Co-occurrence Matrixmentioning

confidence: 99%

Detection of infestation by striped stem‐borer (Chilo suppressalis) in rice based on hyperspectral imaging

Wan

Ouyang

Liu

et al. 2022

J Food Process Engineering

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Striped stem‐borer (SSB) larvae are one of the most serious insect pests that damages rice. In this study, the combined hyperspectral imaging and chemometric method are proposed detect the early SSB larvae infestation in rice stems. Firstly, hyperspectral reflectance data (390–1040 nm) of rice stems were collected for normal, 3 days of infection, 6 days of infection, and 9 days of infection, respectively. On the spectra, the average spectra of the region of interest of the rice stalk samples were extracted, and 19 characteristic wavelengths were screened by the successive projection algorithm (SPA). Morphological processing was performed on the pseudo‐color (generally known as RGB) images of rice stalk samples on the images. Then five image texture features based on the gray‐scale co‐occurrence matrix (GLCM) and nine image color features based on color moments were obtained. The evaluation models of SSB larval infestation based on full spectra, characteristic wavelengths, GLCM, color moments, and data fusion were developed using partial least squares discriminant analysis (PLS‐DA), respectively. The results show that performance of the PLS‐DA model based on the fusion of characteristic wavelengths and GLCM is best. The accuracy of both the comprehensive modeling set and the prediction set is above 97%. The accuracy of the degree of infestation classification is good for all categories, and only the samples on the third day of infection are slightly less accurate. In conclusion, the hyperspectral imaging technology can be used to effectively detect the infection degree situation of early SSB larval infestation. Practical Applications Chemical control using insecticides to manage SSB infestation on rice is still the farmers' first choice. However, in the middle and late stages of rice growth, SSB larvae may moth into the inside of the rice stalk, and the rice provides a shelter for SSB so that the sprayed pesticides cannot reach SSB larvae, which produce a large number of overwintering SSB. This leads to the misuse of chemical pesticides, which causes serious pollution to the environment, pesticide residues also cause serious harm to the human body, and it also makes the pest resistance to pesticides rapidly increase. Therefore, it is necessary to find a rapid and effective detection method to detect the early infestation of SSB larvae on rice to reduce the use of pesticides and improve rice yield.

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“…There are a limited number of studies on the use of THz spectroscopy for the determination of food adulteration, which were previously compiled by Afsah-Hejri [115] and He [116]. Adulteration of milk with a fat powder [117], discrimination of honey samples [118], and determination of honey adulteration [119] were some of the recent study topics.…”

Section: Other Spectroscopic Techniquesmentioning

confidence: 99%

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Hassoun

Måge

Schmidt

et al. 2020

Foods

111

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Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

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Determination of invert syrup adulterated in acacia honey by terahertz spectroscopy with different spectral features

Cited by 19 publications

References 43 publications

Identification of different parts of Panax notoginseng based on terahertz spectroscopy

Identification of different parts of Panax notoginseng based on terahertz spectroscopy

Detection of infestation by striped stem‐borer (Chilo suppressalis) in rice based on hyperspectral imaging

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

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