Spectroscopic fingerprint of tea varieties by surface enhanced Raman spectroscopy

Abstract

The fingerprinting method is generally performed to determine specific molecules or the behavior of specific molecular bonds in the desired sample content. A novel, robust and simple method based on surface enhanced Raman spectroscopy (SERS) was developed to obtain the full spectrum of tea varieties for detection of the purity of the samples based on the type of processing and cultivation. For this purpose, the fingerprint of seven different varieties of tea samples (herbal tea (rose hip, chamomile, linden, green and sage tea), black tea and earl grey tea) combined with silver colloids was obtained by SERS in the range of 200-2000 cm −1 with an analysis time of 20 s. Each of the thirty-nine tea samples tested showed its own specific SERS spectra. Principal Component Analysis (PCA) was also applied to separate of each tea variety and different models developed for tea samples including three different models for the herbal teas and two different models for black and earl grey tea samples. Herbal tea samples were separated using mean centering, smoothing and median centering pre-processing steps while baselining and derivatisation pre-processing steps were applied to SERS data of black and earl grey tea. The novel spectroscopic fingerprinting technique combined with PCA is an accurate, rapid and simple methodology for the assessment of tea types based on the type of processing and cultivation differences. This method is proposed as an alternative tool in order to determine the characteristics of tea varieties.

Effect of Drying on Quality and Sensory Attributes of Lemongrass (Cymbopogon citratus) Tea

“…Shaw et al (2007), reported about the colour changes occurring during drying of most of the leaves using microwave drying process. There is increasing need for methods and tools for determining the characteristics of tea varieties (Buyukgoz et al, 2016). 6.67 ± 0.00 a 6.67 ± 0.01 a 6.67 ± 0.02 a 6.67 ± 0.03 a 7.78 ± 1.92 a 6.67 ± 0.03 a pH 5.89 ± 0.02 d 6.25 ± 0.02 a 6.06 ± 0.09 b 5.98 ± 0.01 c 5.96 ± 0.03 cd 5.97 ± 0.01 cd Mean scores in the same row with different superscripts are significantly different (p < 0.05).…”

Insights into chemometric algorithms for quality attributes and hazards detection in foodstuffs using Raman/surface enhanced Raman spectroscopy

“…On the other hand, PCA through analysis of variance produced much lower accuracy for the strains with both linear discrimination analysis (72.7%) and linear SVM classification (68.2%). In addition to different beverages (Mandrile et al., 2016; Mendes et al., 2003; Nordon et al., 2005; Pierna et al., 2012; Silveira Jr et al., 2009; Wu et al., 2015; Zanuttin et al., 2019), the chemometric‐based Raman/SERS approach has also been extended to all sorts of foodstuffs quality monitoring, such as dairy products, (Almeida et al., 2011; Caponigro et al., 2019; de Oliveira Mendes et al., 2019; Júnior et al., 2016; Karunathilaka et al., 2016; Liu et al., 2020; Moros et al., 2007; Nedeljkovic et al., 2017; Nieuwoudt et al., 2017; Richardson et al., 2019; Stefanov et al., 2013; Taylan et al., 2020; Zhao et al., 2020), vegetables (Sebben et al., 2018), wheat, flour (Cebi et al., 2017; Czaja et al., 2016; Liu et al., 2019), tea, and coffee (Buyukgoz et al., 2016; El‐Abassy et al., 2011; Figueir, 2019; Liao & Chen, 2017; Luna et al., 2019). The wide literature indicates the applicability of chemometric algorithms in Raman/SERS‐based quality monitoring of foodstuffs (Table 2).…”

Analysis of Biomolecules Based on the Surface Enhanced Raman Spectroscopy

“…Data processing method of Principal Component Analysis (PCA) was used to separate tea species and several models for different tea samples. The combined method of fingerprinting-PCA was accurate and rapid for the evaluation of different tea species [ 112 , 113 ].…”