Identification of the varietal origin of processed loose-leaf tea based on analysis of a single leaf by SNP nanofluidic array

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• 作者：Wanping Fang^a ; ^b ; Lyndel W. Meinhardt^b ; Huawei Tan^a ; Lin Zhou^a ; Sue Mischke^b ; Xinghua Wang^c ; Dapeng Zhang^b ; ^{Dapeng.Zhang@ars.usda.gov" class="auth_mail" title="E-mail the corresponding author}
• 关键词：IFC ; integrated fluidic circuit ; PCoA ; principal coordinates analysis ; PIC ; polymorphism information content ; PID ; probability of identity ; PID-sib ; probability of identity among siblings ; STA ; specific target amplification
• 刊名：The Crop Journal
• 出版年：2016
• 出版时间：August 2016
• 年：2016
• 卷：4
• 期：4
• 页码：304-312
• 全文大小：401 K

文摘

Tea is an important cash crop, representing a $40 billion-a-year global market. Differentiation of the tea market has resulted in increasing demand for tea products that are sustainably and responsibly produced. Tea authentication is important because of growing concerns about fraud involving premium tea products. Analytical technologies are needed for protection and value enhancement of high-quality brands. For loose-leaf teas, the challenge is that the authentication needs to be established on the basis of a single leaf, so that the products can be traced back to the original varieties. A new generation of molecular markers offers an ideal solution for authentication of processed agricultural products. Using a nanofluidic array to identify variant SNP sequences, we tested genetic identities using DNA extracted from single leaves of 14 processed commercial tea products. Based on the profiles of 60 SNP markers, the genetic identity of each tea sample was unambiguously identified by multilocus matching and ordination analysis. Results for repeated samples of multiple tea leaves from the same products (using three independent DNA extractions) showed 100% concordance, showing that the nanofluidic system is a reliable platform for generating tea DNA fingerprints with high accuracy. The method worked well on green, oolong, and black teas, and can handle a large number of samples in a short period of time. It is robust and cost-effective, thus showing high potential for practical application in the value chain of the tea industry.