## 3 Results and Discussion
### PCA Score Images  
PCA was conducted on hyperspectral images to form a score image at each PC to qualitatively identify the differences among tea leaves from different geographical origins. In this study, score images of the first ten PCs were obtained for the two spectral ranges (shown in Figures S1 and S2). To conduct PCA, leave-one-out cross validation was used.  
Figure S1 shows the score images of the first ten PCs of spectral range 1. These first ten PCs explained over 99% of the data viability. Indeed, the first three PCs already explained over 99% of data viability. The other seven PCs explained less than 1% of data viability. Although these PCs explained less data viability, they also contained information about samples. Thus, score images of these PCs were also studied. As shown in Figure S1, tea leaves from different geographical origins were distinguished according to color differences. Samples from Meijiawu Village had the lowest score and the bluest color in PC2 image, which was preliminary identified. In PC3 image, the score of samples from TongWu Village was relatively low, which was identified. In addition, samples from Tiedian Village were distinguished from other geographical origins in PC4 image since the score of samples from Tiedian Village was lower and the color was bluish. In addition, samples from Meijiawu Village, Xinxin Village, and Hujialing Village were intuitively distinguished from samples from the other geographical origins in score images of PC5, PC6, and PC9, respectively. These results illustrate that although the remaining seven PCs (PC4-PC10) explained less than 1% of data viability, they also contained useful information contributing to the identification of the geographical origins of Longjing tea.  
Figure S2 shows the score images of the first ten PCs at spectral range 2. These first ten PCs explained over 99% of the data viability. Similarly, tea leaves from different geographical origins were distinguished according to color differences. For example, in PC1 and PC2 images, the pixel scores of samples from Bashan Village and Meijiawu Village were relatively higher than those of samples from the other geographical origins. In PC3 images, the score of samples from Hujialing Village was relatively high and was distinguished from the others. In addition, in PC7 images, the color of samples from Tiedian Village was relatively blue, which was distinguished preliminarily. In PC10 image, samples from Meijiawu Village could be further identified because of their high score. These results also illustrate that apart from the first three PCs, the other PCs also contained useful information contributing to the identification of the geographical origins of Longjing tea, even though they explained little of the data viability.  
Figure 2: Average spectra with standard deviation of each wavelength of tea samples from six different geographical origins at two different spectral ranges: (**a**) spectral range 1: 502–947 nm (the standard deviations of 533, 543, 585, 616, 634, and 672 nm are presented.) and (**b**) spectral range 2: 975–1646 nm (the standard deviations of 1200, 1500, 1106, 1308, and 1615 nm are presented).