A novel method to determine total sugar of Goji berry using FT-NIR spectroscopy with effective wavelength selection

Li, Qi; Yu, Xiuzhu; Gao, Jin‐Ming

doi:10.1080/10942912.2017.1299759

Cited by 11 publications

(9 citation statements)

References 30 publications

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“…Wang [ 10 ] et al (2016) used near-infrared diffuse reflectance spectroscopy (NIDRS) to evaluate the amount of Chinese wolfberry polysaccharides (LBPs). Li [ 11 ] et al (2017) used a fourier transform near-infrared (FT-NIR) spectrometer to determine the total sugar content of Chinese wolfberry. Shen [ 12 ] et al (2016) used NIRS to determinate geographical origins of Chinese wolfberries and flavonoids content related to origins.…”

Section: Introductionmentioning

confidence: 99%

Application of near-infrared hyperspectral imaging to discriminate different geographical origins of Chinese wolfberries

et al. 2017

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Near-infrared (874–1734 nm) hyperspectral imaging (NIR-HSI) technique combined with chemometric methods was used to trace origins of 1200 Chinese wolfberry samples, which from Ningxia, Inner Mongolia, Sinkiang and Qinghai in China. Two approaches, named pixel-wise and object-wise, were investigated to discriminative the origin of these Chinese wolfberries. The pixel-wise classification assigned a class to each pixel from individual Chinese wolfberries, and with this approach, the differences in the Chinese wolfberries from four origins were reflected intuitively. Object-wise classification was performed using mean spectra. The average spectral information of all pixels of each sample in the hyperspectral image was extracted as the representative spectrum of a sample, and then discriminant analysis models of the origins of Chinese wolfberries were established based on these average spectra. Specifically, the spectral curves of all samples were collected, and after removal of obvious noise, the spectra of 972–1609 nm were viewed as the spectra of wolfberry. Then, the spectral curves were pretreated with moving average smoothing (MA), and discriminant analysis models including support vector machine (SVM), neural network with radial basis function (NN-RBF) and extreme learning machine (ELM) were established based on the full-band spectra, the extracted characteristic wavelengths from loadings of principal component analysis (PCA) and 2nd derivative spectra, respectively. Among these models, the recognition accuracies of the calibration set and prediction set of the ELM model based on extracted characteristic wavelengths from loadings of PCA were higher than 90%. The model not only ensured a high recognition rate but also simplified the model and was conducive to future rapid on-line testing. The results revealed that NIR-HSI combined with PCA loadings-ELM could rapidly trace the origins of Chinese wolfberries.

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Section: Introductionmentioning

confidence: 99%

Application of near-infrared hyperspectral imaging to discriminate different geographical origins of Chinese wolfberries

et al. 2017

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“…This is the first attempt of TA prediction in the goji berry with spectral data. Comparing these results with the prediction of TA in the grape tomato, despite the lowest R 2 Cal and R 2 pred , we had the smallest prediction error (RMSP 0.04% vs. 0.072%) [ 47 ]. Furthermore, Figure 5 B expresses the concentration of TA in the goji berry across four different maturity stages.…”

Section: Resultsmentioning

confidence: 97%

Comparison Performance of Visible-NIR and Near-Infrared Hyperspectral Imaging for Prediction of Nutritional Quality of Goji Berry (Lycium barbarum L.)

Fatchurrahman

Nosrati

Amodio

et al. 2021

Foods

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The potential of hyperspectral imaging for the prediction of the internal composition of goji berries was investigated. The prediction performances of models obtained in the Visible-Near Infrared (VIS-NIR) (400–1000 nm) and in the Near Infrared (NIR) (900–1700 nm) regions were compared. Analyzed constituents included Vitamin C, total antioxidant, phenols, anthocyanin, soluble solids content (SSC), and total acidity (TA). For vitamin C and AA, partial least square regression (PLSR) combined with different data pretreatments and wavelength selection resulted in a satisfactory prediction in the NIR region obtaining the R2pred value of 0.91. As for phenols, SSC, and TA, a better performance was obtained in the VIS-NIR region yielding the R2pred values of 0.62, 0.94, and 0.84, respectively. However, the prediction of total antioxidant and anthocyanin content did not give satisfactory results. Conclusively, hyperspectral imaging can be a useful tool for the prediction of the main constituents of the goji berry (Lycium barbarum L.).

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“…Goji berry contains polysaccharides, flavonoids, carotenoids, vitamin C, scutellarin, amino acids, and trace elements and other nutrients and has very high medicinal value, such as strengthening the immune system, lowering blood sugar, lowering blood fat, and fighting tumors [1][2][3][4][5]. However, the storage period of fresh goji fruits is very short.…”

Section: Introductionmentioning

confidence: 99%

Infrared Spectrum Analysis of Goji Berry during Electrohydrodynamic Drying

Ding

Zhang

et al. 2020

Journal of Spectroscopy

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This paper aims to study the effects of different needle spacings on goji berry structure during electrohydrodynamic (EHD) drying. The drying characteristics and the product quality parameters of goji berry during the drying process were measured. The infrared spectrum of the dried product was analyzed in detail. The results showed that the average drying rate of goji berry under different needle spacing conditions was significantly higher than that of the control group, and the average drying rate decreased with the increase of needle spacing. The change of needle spacing has great influence on goji berry polysaccharide content and flavonoid content. Fourier transform infrared spectroscopy showed that the infrared spectra of goji berry in each treatment group were generally similar. The first-order infrared spectra of different treatment groups were mainly different in the range of 1740 cm−1 and 2800 cm−1–2950 cm−1. The shape and intensity of the absorption peaks of the second derivative infrared spectrum of goji berry in different needle spacing treatment groups were different. When the needle spacing is 2 cm and 4 cm, there is a highly variant peak ratio and a low common peak ratio, which proves that the best drying effect is at 2 cm and 4 cm. It provides experimental and theoretical basis for the study of the application and drying mechanism of infrared spectroscopy in the field of electrohydrodynamic drying.

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A novel method to determine total sugar of Goji berry using FT-NIR spectroscopy with effective wavelength selection

Cited by 11 publications

References 30 publications

Application of near-infrared hyperspectral imaging to discriminate different geographical origins of Chinese wolfberries

Application of near-infrared hyperspectral imaging to discriminate different geographical origins of Chinese wolfberries

Comparison Performance of Visible-NIR and Near-Infrared Hyperspectral Imaging for Prediction of Nutritional Quality of Goji Berry (Lycium barbarum L.)

Infrared Spectrum Analysis of Goji Berry during Electrohydrodynamic Drying

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