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To improve tea leaves' utility as a functional crop, it is necessary to understand the distribution and alteration of bioactive secondary metabolites during different growth stages. In the present study, secondary metabolites changes in C. sinensis leaves were investigated according to growth stage using ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC–QTof MS) with multivariate analysis. Through principal component analysis of the metabolites, patterns could be distinguished from samples harvested between April and August. On the loading plot, significant changes in the contents of metabolites were found during growth, and two gallotannins (4 and 10), three flavan-3-ols (6, 7, and 17), two flavonols (14 and 16), and two theaflavins (29 and 31) were evaluated as growth markers among thirty-one isolated metabolites. In particular, the flavonols and theaflavins increased gradually, whereas gallotannins and flavan-3-ols decreased continuously depending on the growth stage. A possible pathway could be deduced using metabolomics analysis, and information regarding physiological characterization and optimal harvesting time was obtained.

In the study presented, the potential of coupling chemometrics and mass spectrometry (UPLC-QToF MS) data for distinguishing the origin and variety of citrus fruit/fruit juices was investigated. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and soft independent modelling by class analogy (SIMCA) were employed. Clustering of citrus fruits (orange, grapefruit, mandarin, and pomelo) and oranges of various geographical/botanical origin was revealed using PCA on data produced in both negative (goodness of fit, R2(cum) = 0.67–0.92, and predictability, Q2(cum) = 0.56–0.88) and positive (R2(cum) = 0.58–0.85 and Q2(cum) = 0.47–0.80) ionisation mode. PLS-DA and SIMCA confirmed the results (with 100% recognition ability obtained for citrus fruits/orange models and fresh squeezed commercial orange juice, while classification success of 80% was achieved for commercial orange juice prepared from concentrate) and showed that the category models for the class can be sensitive and highly specific. Characteristic compounds responsible for the discrimination were identified. The applicability of the models was tested with an external data set of fruit juices adulterated with other fruit juices down to 1% and diluted with water down to 5%. Using Coomans' plots, adulterated samples were easily distinguished from authentic samples showing the possibility of applying this method as a rapid screening technique to trace or confirm the origin of citrus fruit/fruit juices and detect fraud.

An untargeted metabolomics approach was applied for the discrimination of honey of various floral and geographical origins using ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-QToF MS). Evaluation of data by multivariate data analysis allowed the discrimination of New Zealand and Australian honeys from honeys originating in other countries. It was also possible to differentiate between mono- and polyfloral honeys within one region, as well as between some monofloral honeys of various geographical origins. Characteristic markers, contributing to the segregation of different honey types, were selected and characterized.