Identification of the Origin of White Tea Based on Mineral Element Content
Total Page：16
File Type：pdf, Size：1020Kb
Food Anal. Methods (2017) 10:191–199 DOI 10.1007/s12161-016-0568-5 Identification of the Origin of White Tea Based on Mineral Element Content Xiaohui Ye1,2 & Shan Jin 1 & Danhong Wang3 & Feng Zhao4 & Ying Yu 1 & Deyong Zheng5 & Naixing Ye1 Received: 11 January 2016 /Accepted: 5 June 2016 /Published online: 18 June 2016 # Springer Science+Business Media New York 2016 Abstract In recent years, the white tea industry has (KNN) methods, the majority of tea samples from differ- emerged. However, white tea market prices mainly based ent origins could be successfully differentiated according on the place of origin face certain challenges, such as to their mineral elements. The accuracy of origin-based shoddy and false advertising. To study origin identifica- identification using mineral element analyses reached tion technology, 64 white tea samples were collected from 98.44, 95.31, and 100 %, respectively. Therefore, mineral their main origins (Fuding City, Zhenghe County, and elements can be used to identify the origin of white tea Jianyang City) and analyzed for 26 mineral elements (P, samples, providing a reference for white tea identification. K, Fe, Ca, Mg, Al, Mn, and others) using inductively coupled plasma optical emission spectrometry (ICP- Keywords White tea . Mineral elements . Origin OES) and inductively coupled plasma mass spectrometry identification . Statistical methods (ICP-MS). Results showed that white tea samples from different origins had different mineral contents, and sam- ples collected from Zhenghe contained higher amounts of Introduction 10 mineral elements than samples from Fuding and Jianyang. By linear discriminant analysis (LDA), support In China, 90 % of white tea is produced in Fujian Province, vector machines (SVM) analysis, and K-Nearest Neighbor where Fuding, Zhenghe, and Jianyang produce 60–70, 24–34, and5%,respectively(Ye2010). In the last few years, follow- ing BPu’er,^ BJinjunmei,^ and Bdark green tea,^ Bwhite tea^ has become an emerging trend, with a large number of black Xiaohui Ye and Shan Jin contributed equally to this work. tea and green tea manufacturers turning to white tea (Ye * Deyong Zheng 2010). However, the increasing complexity of origin, process, [email protected] and variety has resulted in great difficulty in effectively iden- * Naixing Ye tifying its quality. Some businessmen sell poor-quality prod- [email protected] ucts for profit. Therefore, a reliable and effective analytical technique should be developed to identify, monitor, and trace 1 College of Horticulture, Fujian Agriculture and Forestry University, label information, thereby providing powerful technological Fuzhou, Fujian 350002, China support for the tea industry. 2 Fujian Tea Import & Export Company Limited, International scholars have conducted a series of explorato- Fuzhou, Fujian 350014, China ry studies on product traceability, mainly by analyzing mineral 3 Food Inspection Institute, Fujian Inspection and Research Institute elements, isotopes, and other specific indicators that represent for Product Quality, Fuzhou, Fujian 350002, China geographical information of products from different regions. 4 Technology Center of Inspection and Quarantine, Fujian Entry-Exit Mineral element analysis has been widely used to identify the Inspection and Quarantine Bureau, Fuzhou, Fujian 350002, China origin of beer, honey, olive oil, and cheese (Rolf et al. 2013; 5 College of Materials Engineering, Fujian Agriculture and Forestry Geana et al. 2013;Karabagiasetal.2003, 2014; Urska et al. University, Fuzhou, Fujian 350002, China 2010; Beltrán et al. 2015; Federica et al. 2010; Camin et al. 192 Food Anal. Methods (2017) 10:191–199 2012). James et al. (2010) identified the origin of five types of et al. (2011) and Marcelo et al. (2014). Approximately 0.3 g of tea (green tea, black tea, and others) by analyzing the contents pulverized sample powder was weighed and transferred to the of 14 mineral elements and probabilistic neural network, 55-mL polytetrafluorethylene (PTFE) flask (CEM, USA). reaching an accuracy of 97 %. Fernandez et al. (2002)detect- Subsequently,5.00mLofnitricacidand2mLof30%hy- ed mineral elements in tea and conducted diversity analysis, drogen peroxide were added to the flask. Then, the flask was showing that mineral elements can be used to distinguish closed with a screw cap and placed in a High Throughput gruel, instant tea, and carbonated drinks effectively. Pilgrim Microwave Digestion System (CEM, USA) for 0.5 h at et al. (2010) measured the mineral element content of samples 1600 Wand 180 °C. After the period, the mixture was allowed from India (Nilgiri, Assam, and Darjeeling), China (Taiwan to cool to room temperature and quantitatively transferred to a and mainland), Sri Lanka, and other Asian countries with volumetric polypropylene vial where the volume of the solu- organic and inorganic isotope techniques, and conducted dis- tion was adjusted to 50 mL using water. The volume of 50 mL criminant analyses of their origins based on the mineral ele- was set aside for further tests. ment content, reaching an accuracy of 97.6 %. Numerous investigations on mineral elements in tea in China have been Instruments and Reagents conducted. These studies mostly focused on the relationship between mineral elements, as well as the quality and function OPTIMA 8000 ICP-OES (Perkin Elmer, USA) and X series 2 of mineral elements dissolved from gruel on human health. ICP-MS (Thermo, US) were employed for the quantification For example, Tang and Zhu (2010) studied the dissolution of of the investigated elements using a standard operating mode. mineral elements from decocted scented tea, and demonstrat- The investigated elements and operating parameters for ICP- ed that scented tea dissolves higher amounts of beneficial OES and ICP-MS are shown in Table 1. microelements (Cu, Zn, Mn, and Ni) and lower amounts of The 26 mineral elements for standard solutions were pro- harmful heavy metals. Li et al. (2005) measured mineral ele- vided by the Shanghai Institute of Measurement Technology. ments in brick tea with inductively coupled atomic emission Serial solutions for standard curves of Al, Ba, Ca, Fe, K, Mg, spectroscopy, showing that brick tea contains higher amounts Mn, S, Si, Sr, and Zn were 0.0, 0.2, 0.4, 1.0, 5.0, and 10.0 μg/ of Al, Mn, Fe, Ca, and Mg than ordinary tea. Lv et al. (2013) L. Standard solutions of P were 0.0, 0.4, 0.8, 2.0, 10.0, and recently found that eight mineral elements (i.e., Ca, Fe, Al, K, 20.0 μg/L. Standard solutions of Na were 0.0, 0.7, 1.3, 3.2, Mg, S, Ni, and Co) differ in four regions, and speculated that 16.0, and 32.0 μg/L. Serial solutions for standard curves of Li, this difference has great potential in identifying the origin of B, V, Cr, Co, Ni, Cu, As, Se, Mo, Cd, Pb, and Bi were 0.0, pure tea and protecting its origin. Liu et al. (2014)identified 0.002, 0.01, 0.02, and 0.04 μg/L. the origin of Pu’er tea samples from different regions using their rare earth element content, and reported an accuracy of 93.3, 87.9, and 90.9 %. However, identification of the origin Statistical Analysis of white tea is rarely reported locally and abroad. In this study, the mineral element content of 64 white tea SPSS 21.0 data processing software was used for variance samples collected from Fuding City, Zhenghe County, and analysis, correlation analysis, and discriminant analysis. In Jianyang City were analyzed by ICP-OES and ICP-MS, and linear discriminant analysis (LDA), variables were selected ’ compared by combining variance analysis, correlation analy- by statistical Wilks l least value principle to conduct stepwise sis, and principal component analysis to discriminate their discriminant analysis and then establish a discriminant equa- origin and provide technical support for the development of tion. SPSS 21.0 data processing software was also used for the white tea industry. two other methods of multivariate classification, K-Nearest Neighbor (KNN) and support vector machines (SVM). Materials and Methods Results and Discussion Samples and Sample Preparation Content Analysis for Mineral Elements of White Tea Sixty-four white tea samples were respectively collected in from Different Origins Fuding City (28 samples), Zhenghe County (20 samples), and Jianyang City (16 samples), and geographical locations The Mann–Whitney non-parametric U test was conducted to of the three white tea sampling sites are as shown in Fig. 1.All analyze 26 mineral elements in 64 white tea samples collected samples were collected in March 2013. from three locations. The results are shown in Table 2.The The white tea samples were treated before mineral element mineral element contents of white tea samples between identification by improving the previously used methods of Li Fuding and Zhenghe, Fuding and Jianyang, as well as Food Anal. Methods (2017) 10:191–199 193 China Fujian Fig. 1 Geographical location plan of white tea sampling sites. In the left starred areas are three sampling sites of white tea, respectively, being map of China, gray area in southeast is Fujian Province, the right block Jianyang, Zhenghe, and Fuding diagram is enlarged view of northern part of Fujian Province, and the Zhenghe and Jianyang were compared to determine signifi- from the three provinces were consistent with previous results cant differences. The results are shown in Table 3. on mineral element content in soil. Zhenghe tea gardens main- With respect to changes in the mean value of tea samples ly rely on red loam, with sandy loam–medium loam for the from different origins, the Cu and Cd contents among the three surface and light loam–heavy loam for the undersurface. Such origins showed minimal differences. The Na, Cr, Li, and Bi gardens contain abundant mineral elements, so they are con- contents in white tea samples sourced from Zhenghe and sidered the most satisfactory condition for tea tree growth Fuding also exhibited minor differences; however, they were (2013).