Metabolomics Provides A Novel Interpretation of the Changes in Main Compounds during Black Tea Processing through Different Drying Methods

This study aimed to compare the effect of hot roller (HR) drying and hot air (HA) drying on the sensory evaluation, chemical quality, antioxidant activity, and metabolic profile of Yihong Congou black tea processed from E’cha NO1. The Yihong Congou black tea dried with HA obtained higher sensory scores and better chemical qualities such as the hue of tea brew color (a and b), content of theaflavins, thearubigins, water extract, free amino acids, tea polyphenol, and the ratio of polyphenol to amino acids as well as higher antioxidant capacities compared to that dried with HR. The HA drying tea increased the contents of volatile compounds that had positive correlation with sweet and flowery flavor, while the HR drying tea increased the contents of volatile compounds related to fruity flavor. Moreover, non-targeted metabolomics data indicated that the levels of most free amino acids significantly increased, while the levels of most soluble sugars reduced in the HA drying method compared to the HR drying method. The metabolic analysis was also consistent with the above results and revealed that D-ribose and gallic acid were the main characteristic metabolites of HA drying. Our results could provide a technical reference and theoretical guide to processing a high quality of Yihong Congou black tea.     

天然抗氧化剂茶多酚

抗氧化剂是指能防止或延缓食品成分氧化变质的食品添加剂.茶多酚是目前尚不能人工合成的纯天然、多功能、高效能的抗氧化剂和自由基净化剂,可用超临界CO2萃取法、离子沉淀提取法、树脂吸附分离法、有机溶剂萃取法提取.采用酒石酸亚铁比色法测定茶多酚含量.     

Widely Targeted Metabolomics Analysis Reveals Great Changes in Nonvolatile Metabolites of Oolong Teas during Long-Term Storage

As a semifermented tea, oolong is exceedingly popular worldwide for its elegant, flowery aroma and mellow, rich taste. However, recent marketing trends for old oolong teas and their chemical quality largely remain unexplored. In this study, we applied widely targeted metabolomics using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) combined with multivariate analysis to investigate the chemical change of oolong teas in the aging process. With the increasing of store time, most nongalloylated catechins; tannins, including TFs and proanthocyanidins; flavonols and glycosylated flavonols; amino acids and their derivatives; nucleotides and their derivatives; and lots of alkaloids and phospholipids declined, while most fatty acids and organic acids increased, and galloylated catechins, GA, and caffeine were almost stable. The result also suggested that approximately seven years (but not an infinite extension) was a special period for oolong tea storage, which brings about excellent taste.     

加速溶剂萃取-固相萃取净化-气相色谱-串联质谱法检测茶叶中9种拟除虫菊酯类农药残留

建立了加速溶剂萃取（ASE）-固相萃取净化（SPE）-气相色谱-串联质谱（GC-MS/MS）同时测定茶叶中9种拟除虫菊酯类农药残留的方法。ASE萃取溶剂为丙酮-正己烷（1：1,v/v）,萃取温度为100℃,萃取压力为10 MPa,加热时间为3 min,静态萃取时间为5 min,循环1次,冲洗体积为40%萃取池体积,氮气吹扫100 s。萃取结束后用Cleanert TPT固相萃取柱净化,净化液浓缩定容后,采用GC-MS/MS测定,外标法定量。9种拟除虫菊酯类农药在2~1000 μg/L范围内呈现良好的线性关系,相关系数（r²）均大于0.99,方法检出限为0.2~4.5 μg/kg,定量限为0.8~15.0 μg/kg。在绿茶、红茶空白基质中做加标回收试验,添加水平为0.02、0.1、0.4 mg/kg以及定量限水平,得到的平均回收率为69.87%~110.0%,相对标准偏差（RSD）为0.7%~11.2%。该方法背景干扰低、灵敏度高、重现性好、回收率稳定,适用于茶叶中拟除虫菊酯类农药残留量的检测。     

Analysis of Protein Moiety of Polysaccharide Conjugates Water-extracted from Low Grade Green Tea

Tea polysaccharide conjugates(TPCs) were water-extracted and purified from low-grade green tea. Although TPC contains 1.97% covalent binding proteins, Coomassie brilliant blue G250 and R250 could not detect this protein. The "should-shape" absorption peak observed at 250-280 nm in the UV-Vis spectrum was caused by quinone compounds derived from polyphenol oxidation during TPC extraction. The UV-Vis spectrum could be used to detect the decolorizing degree of TPC. TPC aqueous solution merely presented the negative charge properties of its polysaccharides instead of the acid-base property of its protein section, and exhibited higher stability at pH greater than 5.0. No precipitation or haze occurred in three TPC/epigallocatechin gallate(EGCG) aqueous mixtures during 12 h storage. TPC had emulsifying activity, which indicated that its protein moiety formed hydrophobic groups. It is proposed that some of the physicochemical properties of the TPC protein moiety are shielded by its polysaccharide chain.     

基于手机APP实现驻波法对声速的测量

介绍了一种利用普通智能手机和一根两端开口奶茶管基于声驻波现象来测量声速的方法。这种实验方法所用的实验仪器随手可得,无需学生再到学校的实验室进行实验,激发了学生的学习兴趣,增强了学生的动手能力。     

祁门红茶加工中氨基酸和儿茶素快速检测模型建立

氨基酸与儿茶素是茶叶品质的重要组成成分。祁门红茶在加工过程中,氨基酸与儿茶素含量发生了显著的变化,而且不同加工阶段差异性很大,但目前在生产中缺乏快速在线检测方法。为了实现对祁门红茶加工过程中氨基酸和儿茶素含量快速测定,试验以鲜叶、萎凋叶、揉捻叶、发酵叶和干燥后毛茶为原料,获取近红外光谱并利用化学方法检测氨基酸和儿茶素含量。对采集的原始光谱进行标准正态变量变换(SNVT)预处理,利用联合区间偏最小二乘回归法(Si-PLS)构建氨基酸和儿茶素含量近红外回归模型,相关系数与交互验证均方根误差作为评价模型的有效指标。结果表明,利用Si-PLS方法建立氨基酸含量的模型最优组合包含20个光谱区间并联合4个子区间和9个主成分因子,校正集的相关系数、校正均方根误差分别为0.955 8和1.768;预测集的相关系数、预测均方根误差分别为0.949 5和2.16。儿茶素含量的模型最优组合包含20个光谱区间并联合3个子区间和10个主成分因子,校正集的相关系数、校正均方根误差分别为0.940 1和1.22;预测集的相关系数、预测均方根误差分别为0.938 5和1.17。所建立模型准确性较好,这为茶叶加工过程中茶叶品质的在线监控提供了理论依据。     

Production mechanism of proepitheaflagallin, a precursor of benzotropolone-type black tea pigment, derived from epigallocatechin via a bicyclo[3.2.1]octane-type intermediate

An unstable intermediate proepitheaflagallin B (2), a precursor of proepitheaflagallin (3), was isolated as an enzymatic oxidation product of (−)-epigallocatechin (1), and the structure of 2 was determined based on spectroscopic data. The structure and its decomposition revealed that the detailed production mechanism of proepitheaflagallin (3) via a bicyclo[3.2.1]octane-type intermediate was related to that of major black tea pigments, theaflavins.     

潮汕工夫茶中的化学智慧

潮汕工夫茶中蕴含了丰富的化学文化。长期以来,潮汕人在凤凰单枞茶的品种选育、种植、加工以及品饮等诸多方面, 十分关注影响茶叶品质与风味的儿茶素、茶氨酸、咖啡因、可溶性糖、色素、萜类等化学物质,并在生产、加工中对这些化学成分的含量及生化转化精细控制,形成了凤凰单枞茶特有的品质与风味;同时,针对凤凰单枞茶活性成分的组成特点,摸索出一套科学的冲泡程式,充分展现出潮汕工夫茶文化中的化学智慧。     

基于遗传算法的安溪铁观音品质快速评价研究

为探究一种快速无损的安溪铁观音品质评价方法,利用遗传算法(GA)对茶样的近红外光谱特征波长进行筛选,结合偏最小二乘(PLS),建立全谱段的PLS定量模型与GA-PLS模型。结果表明,傅里叶变换近红外(FT-NIR)全谱段光谱在经过平滑+二阶导数+归一化处理后,PLS模型预测性能最高,建模结果为：校正集相关系数R_C=0.921,校正集均方根误差RMSEC=0.543,验证集相关系数R_P=0.913,验证集均方根误差RMSEP=0.665。选用近红外光谱6 670～4 000 cm-1谱区,采用遗传算法进行特征波长筛选,参与建模数据点数从1 557缩减到408个。优选波段后,GA-PLS建模结果为：校正集相关系数R_C=0.959,校正集均方根误差RMSEC=0.413,验证集相关系数R_P=0.940,验证集均方根误差RMSEP=0.587。可见,GA-PLS模型的校正集和验证集的预测结果均优于全谱段PLS模型。结果说明,在传统的近红外光谱技术结合化学计量学方法的建模基础上,加入遗传算法进行波长筛选,能有效提高模型预测能力,实现方法学的创新研究,且GA-PLS品质评价模型具有较强的参考和推广价值,为提高我国茶叶品质的检测技术水平提供新的方法借鉴。