Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor Analysis as a Complementary Technique for Green Tea Characterization

Hailong, 刘海龙 Liu; Xijun, 吴希军 Wu; Guangjun, 田广军 Tian

doi:10.3788/cjl20083505.0685

Cited by 7 publications

(3 citation statements)

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“…Three distinct peaks can be observed in figure 1(b), with excitation/emission wavelengths at 250 nm∼300 nm/300 nm∼350 nm, 350 nm∼ 400 nm/450 nm∼500 nm and 450 nm∼500 nm/ 500 nm∼550 nm respectively. According to previous research [22,23], the excitation/emission peak around 280 nm/311 nm was assigned to catechins, structurally primarily flavonols. The optimal excitation/ emission spectral range of flavanols is around 480-500 nm/510-520 nm as shown in figure 1, and excitation/emission peak around 365-390 nm/ 450-470 nm was considered as flavonols.…”

Section: Syf Spectra Of Green Teamentioning

confidence: 96%

“…Operation parameters were excitation and emission slit widths set as 5.0 nm, PMT voltage as 700 V, scan speed as 1200 nm min −1 . SyF excitation spectra were recorded in the region of 240-550 nm, in which flavonoid excitation wavelength dominate [22,23]. The wavelength characteristic of the equipment has been measured by using Rhodamine B as a standard.…”

Section: Syf Spectra Measurementmentioning

confidence: 99%

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Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

Shan

Wang

Han

et al. 2018

Methods Appl. Fluoresc.

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Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

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Section: Syf Spectra Of Green Teamentioning

confidence: 96%

Section: Syf Spectra Measurementmentioning

confidence: 99%

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

Shan

Wang

Han

et al. 2018

Methods Appl. Fluoresc.

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“…The producer, grade, productive year, and the number of samples are shown in Table 1. Tea infusions were prepared as follows [44,45]: 0.50 g of matcha tea sample was mixed with 50 mL of distilled water at 80 • C, then water bath heat preservation was conducted at 80 • C for 30 min, followed by centrifugation and collection of the supernatant. The supernatant was diluted ten times to ensure a good performance when scanning the fluorescence spectroscopy, which requires the maximum intensity of fluorescence spectroscopy to be less than 8000 during a test.…”

Section: Matcha Tea Collection and Preparationmentioning

confidence: 99%

Identifying the Producer and Grade of Matcha Tea through Three-Dimensional Fluorescence Spectroscopy Analysis and Distance Discrimination

Xu,

Zhou,

Lei

2023

Foods

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The three-dimensional fluorescence spectroscopy features the advantage of obtaining emission spectra at different excitation wavelengths and providing more detailed information. This study established a simple method to discriminate both the producer and grade of matcha tea by coupling three-dimensional fluorescence spectroscopy analysis and distance discrimination. The matcha tea was extracted three times and three-dimensional fluorescence spectroscopies of these tea infusions were scanned; then, the dimension of three-dimensional fluorescence spectroscopies was reduced by the integration at three specific areas showing local peaks of fluorescence intensity, and a series of vectors were constructed based on a combination of integrated vectors of the three tea infusions; finally, four distances were used to discriminate the producer and grade of matcha tea, and two discriminative patterns were compared. The results indicated that proper vector construction, appropriate discriminative distance, and correct steps are three key factors to ensure the high accuracy of the discrimination. The vector based on the three-dimensional fluorescence spectroscopy of all three tea infusions resulted in a higher accuracy than those only based on spectroscopy of one or two tea infusions, and the first tea infusion was more sensitive than the other tea infusion. The Mahalanobis distance had a higher accuracy that was up to 100% when the vector is appropriate, while the other three distances were about 60–90%. The two-step discriminative pattern, identifying the producer first and the grade second, showed a higher accuracy and a smaller uncertainty than the one-step pattern of identifying both directly. These key conclusions above help discriminate the producer and grade of matcha in a quick, accurate, and green method through three-dimensional fluorescence spectroscopy, as well as in quality inspections and identifying the critical parameters of the producing process.

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Tea and coffee powders

Huang,

Zhang

2024

Handbook of Food Powders

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Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor Analysis as a Complementary Technique for Green Tea Characterization

Cited by 7 publications

References 0 publications

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

Identifying the Producer and Grade of Matcha Tea through Three-Dimensional Fluorescence Spectroscopy Analysis and Distance Discrimination

Tea and coffee powders

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