Validation of origins of tea samples using partial least squares analysis and Euclidean distance method with near-infrared spectroscopy data.

In today's global food markets, the ability to trace the origins of agricultural products is becoming increasingly important. We developed an efficient procedure for validating the authenticity and origin of tea samples where Partial Least Squares and Euclidean Distance methods, based on near-infrared spectroscopy data, were combined to classify tea samples from different tea producing areas. Four models for identification of authenticity of tea samples were constructed and utilized in our two-step procedure. High accuracy rates of 98.60%, 97.90%, 97.55%, and 99.83% for the calibration set, and 97.19%, 97.54%, 97.83%, 100% for test set, were achieved. After the first identification step, employing the four origin authenticity models, followed by the second step using the Euclidean Distance method, accuracy rates for specific origin identification were 98.43% in the calibration set and 96.84% in the test set. This method, employing two-step analysis of multi-origin model, accurately identified the origin of tea samples collected in four different areas. This study provided a potential reference method for the detection of "geographical indication" of agricultural products' and is available for use in traceability of origin studies.