Journal of Zhejiang Agricultural Sciences ›› 2024, Vol. 65 ›› Issue (7): 1567-1570.DOI: 10.16178/j.issn.0528-9017.20230527

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Differential analysis of internal substances in tea under different tree management modes

LI Jinlong1,2(), LONG Yaqin1,3,*(), YIN Liqiong1, TONG Jiayin1, LUO Ziwen1, QU Hao1, LIU Fuqiao3, CHEN Linbo1,3,*()   

  1. 1. Institute of Tea Research, Yunnan Academy of Agricultural Sciences, Kunming 650000, Yunnan
    2. Puer Agricultural Science Research Institute,Puer 665000, Yunnan
    3. Shuangjiang Mengku Tea Co. Ltd., Lincang 677300, Yunnan
  • Received:2023-05-16 Online:2024-07-11 Published:2024-07-17

Abstract:

In Haigong Village, Shuangjiang County, tea plants under four tree management modes of rattan tea (big), rattan tea (small), breed tea and tableland tea were sampled, detected and analyzed, and the principal component analysis method was used to analyze the internal substance contents of the four tree management modes, and the differential internal substance contents of tea that determined to distinguish the four tree management modes were screened out. The results showed that the four tree management modes could be divided into two categories by principal component analysis, one was rattan tea(small)and rattan tea(big), and the other was breed tea and tableland tea. Among all the inclusions, water extract accounted for the highest proportion, tea polyphenols accounted for the second proportion, followed by catechins. Among the amino acid components, theanine accounted for the highest proportion, and the others were all below 1%. Phosphoserine, asparagine, etc. can better represent the characteristics of rattan tea(small) and rattan tea(big). Water extract and epigallocatechin can better represent the characteristics of breed tea and tableland tea. Through the analysis of the tea contents of four tree management modes, namely rattan tea(small), rattan tea(big), breed tea and tableland tea, the tea characteristics of different tree management modes can be clearly distinguished.

Key words: tea, tree management, internal substance, principal component analysis

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