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Atractylodes macrocephala Koidz (AMK) is an expensive edible Chinese herb with medicinal properties. Its economic value and medicinal properties are closely related to its geographical origin. In this study, a method based on stable isotopes and multiple elements combined with chemometrics was developed to identify the geographical origin of AMK. Five stable isotope ratios, including δ2H, δ18O, δ13C, δ15N, and δ34S, and 41 elements in 281 AMK samples from 10 regions were analyzed. An analysis of variance of stable isotope ratios and elements revealed that the δ2H, δ18O, Mg, Ca, and rare‐earth element concentrations in AMK from different geographical regions were significantly different. Orthogonal partial least squares discriminant analysis proved that Ca, K, Mg, and Na can be used for classifying (variable importance >1) and accurately identifying AMK from Panan, Xianfeng, and other areas with 100% discrimination accuracy. In addition, we achieved a good identification of protected geographic indication products of similar quality. This method realized the geographical discrimination of AMK from different producing areas and could potentially control the fair trade of AMK. Practical Application: The quality of AMK is highly dependent on its geographical origin. Confusion over the origin of AMK impacts consumer rights. This study developed an accurate and effective classification method based on stable isotopes and multiple elements to ascertain the geographical origin of AMK, thereby providing an effective method for determining its quality. [ABSTRACT FROM AUTHOR]

BACKGROUND: The quality of tea is influenced by numerous factors, especially l‐theanine, which is one of the important markers used to evaluate the sweetness and freshness of tea. Sensitive, rapid, and accurate detection of l‐theanine is therefore useful to identify the grade and quality of tea. RESULTS: A high‐sensitivity, paper‐based fluorescent sensor combined with chemometrics was established to detect l‐theanine in tea water based on CdTe quantum dots / corn carbon dots and nano tetra pyridel‐porphine zinc (ZnTPyP). To verify the reliability of this method, fluorescence spectra and fluorescence‐visualized paper‐based sensors were compared. The fluorescence spectrum method demonstrated a linear range of 1 to 10 000 nmol L−1 and a limit of detection (LOD) of 0.19 nmol L−1. In the fluorescence‐visualized paper‐based sensors there was a linear range of 10–1000 nmol L−1, and the LOD was 10 nmol L−1. Partial least squares discriminant analysis (PLSDA) and partial least squares regression analysis (PLSR) were used successfully to determine l‐theanine accurately in tea water with this approach. The accuracy of the PLSDA model was 100% both in the training set and the predicting set, and the correlation coefficient between the actual concentration and the predicted concentration was greater than 0.9997 in the PLSR model. CONCLUSION: This fluorescence‐visualized paper‐based sensor, combined with chemometrics, could be applied efficiently to the practical analysis of tea water samples, which provides a new idea to ensure the flavor and quality of tea. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]