Tea types classification with data fusion of UV–Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis

Dankowska, Anna; Kowalewski, Wojciech

doi:10.1016/j.saa.2018.11.063

Cited by 84 publications

(39 citation statements)

References 38 publications

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“… 80 − 82 In the presence of tea extract, a peak was noted in the range of approximately 280 nm, which is a characteristic of natural phenolic. 83 , 84 A similar kind of phenomenon was also observed in an earlier report. 83 …”

Section: Resultssupporting

confidence: 87%

Hierarchical Assembly of Nanodimensional Silver–Silver Oxide Physical Gels Controlling Nosocomial Infections

et al. 2020

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Microbial infections originating from medical care facilities are raising serious concerns across the globe. Therefore, nanotechnology-derived nanostructures have been investigated and explored due to their promising characteristics. In view of this, silver-based antimicrobial hydrogels as an alternative to antibiotic-based creams could play a crucial role in combating such infections. Toward this goal, we report a simple method for the synthesis and assembly of silver nanoparticles in a biopolymer physical gel derived from Abroma augusta plant in imparting antimicrobial properties against nosocomial pathogens. Synthesized silver nanoparticles (diameter, 30 ± 10 nm) were uniformly distributed inside the hydrogel. Such synthesized hydrogel assembly of silver nanoparticles dispersed in the biopolymer matrix exhibited hemocompatibility and antimicrobial and antibiofilm characteristics against nosocomial pathogens. The developed hydrogel as a surface coating offers reduced hardness and modulus value, thereby minimizing the brittleness tendency of the gel in the dried state. Hence, we believe that the hierarchical assembly of our hydrogel owing to its functional activity, host toxicity, and stability could possibly be used as an antimicrobial ointment for bacterial infection control.

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Section: Resultssupporting

confidence: 87%

Hierarchical Assembly of Nanodimensional Silver–Silver Oxide Physical Gels Controlling Nosocomial Infections

et al. 2020

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“…However, hyperspectral sensors in the ultraviolet (UV) range have been demonstrated to detect salt stress in barley leaves [137]. UV-VIS spectroscopy has been used for the classification of tea types [138]. Whether the spectral information of the UV band or other bands is useful for the study of fruit tree phenotypes remains to be further verified in the future.…”

Section: Discussionmentioning

confidence: 99%

Phenotypic techniques and applications in fruit trees: a review

Huang

Ren

et al. 2020

Plant Methods

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Phenotypic information is of great significance for irrigation management, disease prevention and yield improvement. Interest in the evaluation of phenotypes has grown with the goal of enhancing the quality of fruit trees. Traditional techniques for monitoring fruit tree phenotypes are destructive and time-consuming. The development of advanced technology is the key to rapid and non-destructive detection. This review describes several techniques applied to fruit tree phenotypic research in the field, including visible and near-infrared (VIS-NIR) spectroscopy, digital photography, multispectral and hyperspectral imaging, thermal imaging, and light detection and ranging (LiDAR). The applications of these technologies are summarized in terms of architecture parameters, pigment and nutrient contents, water stress, biochemical parameters of fruits and disease detection. These techniques have been shown to play important roles in fruit tree phenotypic research.

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“…Aboulwafa et al found that the PCA plot of UV spectroscopic data can be used to separate two areas: low-quality Chinese tea, high-quality Chinese tea, and entire South Asian samples (from India and Sri Lanka) [ 20 ]. Dankowska and Kowalewski reported UV-Vis spectroscopy with PCA to identify six tea types; however, there were overlapping areas [ 22 ]. In terms of color difference, the brightness decreased with the grade of samples, which is consistent with the research results reported by Liang [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

“…Zhang et al identified the grade of Xinyang Maojian tea (a kind of Chinese green tea) with SVM models, and the training and testing accuracies they reported were 86.11% and 87.5%, respectively [ 25 ]. Dankowska et al proved that all the fusion data sets (synchronous fluorescence (SF) spectra + ultraviolet-visible (UV-Vis) spectra, SF + near-infrared (NIR) spectra, NIR + UV-Vis combined with the SVM method) may complement each other, having lower errors for the classification of tea type [ 22 ]. Xu et al conducted partial least squares regression (PLSR) and used SVM and RF models to classify Xihulongjing tea, and combined electronic tongue, electronic nose, and electronic eye, which produced good effects compared with independent signals [ 17 ].…”

Section: Discussionmentioning

confidence: 99%

Rapid Identification of Different Grades of Huangshan Maofeng Tea Using Ultraviolet Spectrum and Color Difference

et al. 2020

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Tea is an important beverage in humans’ daily lives. For a long time, tea grade identification relied on sensory evaluation, which requires professional knowledge, so is difficult and troublesome for laypersons. Tea chemical component detection usually involves a series of procedures and multiple steps to obtain the final results. As such, a simple, rapid, and reliable method to judge the quality of tea is needed. Here, we propose a quick method that combines ultraviolet (UV) spectra and color difference to classify tea. The operations are simple and do not involve complex pretreatment. Each method requires only a few seconds for sample detection. In this study, famous Chinese green tea, Huangshan Maofeng, was selected. The traditional detection results of tea chemical components could not be used to directly determine tea grade. Then, digital instrument methods, UV spectrometry and colorimetry, were applied. The principal component analysis (PCA) plots of the single and combined signals of these two instruments showed that samples could be arranged according to grade. The combined signal PCA plot performed better with the sample grade descending in clockwise order. For grade prediction, the random forest (RF) model produced a better effect than the support vector machine (SVM) and the SVM + RF model. In the RF model, the training and testing accuracies of the combined signal were all 1. The grades of all samples were correctly predicted. From the above, the UV spectrum combined with color difference can be used to quickly and accurately classify the grade of Huangshan Maofeng tea. This method considerably increases the convenience of tea grade identification.

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Tea types classification with data fusion of UV–Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis

Cited by 84 publications

References 38 publications

Hierarchical Assembly of Nanodimensional Silver–Silver Oxide Physical Gels Controlling Nosocomial Infections

Hierarchical Assembly of Nanodimensional Silver–Silver Oxide Physical Gels Controlling Nosocomial Infections

Phenotypic techniques and applications in fruit trees: a review

Rapid Identification of Different Grades of Huangshan Maofeng Tea Using Ultraviolet Spectrum and Color Difference

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