In NPJ science of food
The geographic origin of agri-food products contributes greatly to their quality and market value. Here, we developed a robust method combining metabolomics and machine learning (ML) to authenticate the geographic origin of Wuyi rock tea, a premium oolong tea. The volatiles of 333 tea samples (174 from the core region and 159 from the non-core region) were profiled using gas chromatography time-of-flight mass spectrometry and a series of ML algorithms were tested. Wuyi rock tea from the two regions featured distinct aroma profiles. Multilayer Perceptron achieved the best performance with an average accuracy of 92.7% on the training data using 176 volatile features. The model was benchmarked with two independent test sets, showing over 90% accuracy. Gradient Boosting algorithm yielded the best accuracy (89.6%) when using only 30 volatile features. The proposed methodology holds great promise for its broader applications in identifying the geographic origins of other valuable agri-food products.
Peng Yifei, Zheng Chao, Guo Shuang, Gao Fuquan, Wang Xiaxia, Du Zhenghua, Gao Feng, Su Feng, Zhang Wenjing, Yu Xueling, Liu Guoying, Liu Baoshun, Wu Chengjian, Sun Yun, Yang Zhenbiao, Hao Zhilong, Yu Xiaomin
2023-Mar-16
