Rapid discrimination of quality grade of black tea based on near-infrared spectroscopy (NIRS), electronic nose (E-nose) and data fusion.

For the manufacturing and sale of tea, rapid discrimination of overall quality grade is of great importance. However, present evaluation methods are time-consuming and labor-intensive. This study investigated the feasibility of combining advantages of near-infrared spectroscopy (NIRS) and electronic nose (E-nose) to assess the tea quality. We found that NIRS and E-nose models effectively identify taste and aroma quality grades, with the highest accuracies of 99.63% and 97.00%, respectively, by comparing different principal component numbers and classification algorithms. Additionally, the quantitative models based on NIRS predicted the contents of key substances. Based on this, NIRS and E-nose data were fused in the feature-level to build the overall quality evaluation model, achieving accuracies of 98.13%, 96.63% and 97.75% by support vector machine, K-nearest neighbors, and artificial neural network, respectively. This study reveals that the integration of NIRS and E-nose presents a novel and effective approach for rapidly identifying tea quality.

Non-targeted Metabolomic Analysis Based on Ultra-High-Performance Liquid Chromatography Quadrupole Time-of-Flight Tandem Mass Spectrometry Reveals the Effects of Grafting on Non-volatile Metabolites in Fresh Tea Leaves ( Camellia sinensis L.).

To investigate the effects of grafting on non-volatile metabolites in tea, non-targeted metabolomic analyses of fresh leaves were performed on the basis of ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF/MS). One non-grafted YingHong No. 9 and four grafted tea [grafting scion YingHong No. 9 on four different rootstocks, BaiMao No. 2 (BM2), BaiYeDanCong (BY), HeiYeShuiXian (HY), and WuLingHong (WLH)] were chosen as materials. In total, 32 differential metabolites were identified, including phenolic acids, flavan-3-ols, dimeric catechins, flavonol and flavonol/flavone glycosides, etc. Partial least squares discrimination analysis and hierarchical cluster analysis showed various effects of different rootstocks on metabolites. Thereinto, rootstocks of WLH and BY showed extremely outstanding performance in up- and downregulating these metabolites, respectively. Differential metabolites were enriched into three crucial pathways, including biosynthesis of phenylpropanoids, flavonoid biosynthesis, and flavone and flavonol biosynthesis, which might influence the quality of tea. This study provides a theoretical basis for grafting-related variations of non-volatile metabolites in fresh tea leaves.