Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity – A review

Organic fertilizer reduced carbon and nitrogen in runoff and buffered soil acidification in tea plantations: Evidence in nutrient contents and isotope fractionations.

Predictive geographical authentication of green tea with protected designation of origin using a random forest model

Recent techniques for the authentication of the geographical origin of tea leaves from camellia sinensis: A review

Background Keemun black tea (KBT) is one of the most popular tea beverages in China as a result of its unique flavor and potential health benefits. The geographical origin of KBT influences its quality and price. The present study aimed to apply a head-space solid phase microextraction approach and gas chromatography-mass spectrometry combined with chemometric analysis to profile the volatile compounds of KBT collected from five production areas. Results Thirty-one peaks were detected in 61 KBT samples. Hierarchical cluster analysis, principal component analysis (PCA), k-nearest neighbor (k-NN) and stepwise linear discriminant analysis (SLDA) were employed to visualize the volatile fractions. The results of unsupervised statistical tools were compared using a test for similarities and distinctions, which showed that different sources may be associated. A satisfying combination of average recognition (91.7%) and cross-validation prediction abilities (84.6%) was obtained for the PCA-k-NN. Among all of the statistical tools, SLDA provided promising results, with 100% recognition and 96.4% prediction ability. Conclusion The results obtained in the present study indicate that the volatile compounds can be used as indicators to identify the geographical origin of KBT. © 2019 Society of Chemical Industry.

Identification of geographical origin of Keemun black tea based on its volatile composition coupled with multivariate statistical analyses

Multi-element composition and isotopic signatures for the geographical origin discrimination of green tea in China: A case study of Xihu Longjing

The invention relates to a West Lake Longjing tea production place identification method based on ionomics. The method is characterized by comprising the following steps: (1) selecting a tealeaf representative sample from a West Lake Longjing tea production place; (2) preprocessing the sample; (3) analyzing and determining the sample; (4) establishing a West Lake Longjing tea production place identification technical model; (5) inputting the data of the tealeaf sample with the production place information unknown into the tealeaf production place identification technical model, and predicting the tealeaf production place information. By adopting the method, not only can the quality safety of tealeaves be satisfied, but also the counterfeiting of the tealeaves can be effectively prevented, a tealeaf product having problems can be efficiently recalled or revoked, so that the economic loss can be maximally reduced, the accurate judgment rate of the model acquired by adopting a partial least square method is 94.4 percent, the prediction accuracy is 92.0 percent, and the model is reliable.

West Lake Longjing tea production place identification method based on ionomics

The invention discloses a method for identifying the production place of flat tea The method is characterized by comprising the following steps: testing contents of rare-earth elements of tea from different production places, establishing identification models respectively, testing the contents of rare-earth elements of tea samples from unknown production places, and judging the production places of the tea samples by using the identification models Back substitution inspection and cross validation show that the back substitution distinguishing accuracy rate of the production place identification technique models is 9293%, the cross validation distinguishing rate of the production place identification technique models is 848%, and the production places of different types of flat tea can be relatively well distinguished

Method for identifying production place of flat tea

The invention provides a method for distinguishing production places of flat tea based on stable isotope proportion difference. The method is characterized by mainly comprising the following steps: (1) collecting samples and establishing a modeling sample set; (2) detecting stable isotopes, wherein determined indexes are 13C/12C, 15N/14N, 18O/16O, D/1H, 111Cd/113Cd, 206Pb/207Pb, 207Pb/208Pb and 88Sr/86Sr; (3) carrying out data standard processing and sample assignment to obtain variables Z(C), Z(N), Z(O), Z(D), Z(Cd), Z(206Pb/207Pb), Z(207Pb/208Pb) and Z(Sr); (4) establishing a decision-making tree analyzing model; (5) judging unknown samples. With the adoption of the method provided by the invention, the quality safety of tea leaves can be met, and the faking of the tea leaves can be effectively prevented; the production places are distinguished through decision-making tree analysis, the accurate distinguishing rate of a return test reaches 91.35 percent, the accuracy of an external test reaches 92 percent, and the model is reliable.

Method for distinguishing production places of flat tea based on stable isotope proportion difference

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Multi-element composition and isotopic signatures for the geographical origin discrimination of green tea in China: A case study of Xihu Longjing

West Lake Longjing tea production place identification method based on ionomics

Method for identifying production place of flat tea

Method for distinguishing production places of flat tea based on stable isotope proportion difference