Abstract: In order to investigate the adaptability of NIR spectroscopy-based quantitative nicotine model to distinguish flue-cured tobacco leaves from different growing areas, an NIR quantitative nicotine model in flue-cured tobacco was established by taking Guizhou tobacco leaves as input samples. The adaptability of the established Guizhou model was determined via principal component analysis (PCA), Mahalanobis distance analysis and predicted data relative error analysis using tobacco samples from different areas. The results indicated that:1) The Guizhou model could be adapted to all leaf samples from Zhaotong, Chuxiong, Baoshan in Yunnan and Dechang in Sichuan and some leaf samples from Chenzhou in Hunan with relative error from -5% to 5%, while it did not adapt well to the samples from Sanming in Fujian, Baofeng in Henan and Meizhou in Guangdong with large relative error (higher than 5% or lower than -5%). 2) A merged model was established by using the samples from Yunnan, Sichuan and Guizhou and was compared with the Guizhou model. The results indicated that the merged model was superior to the Guizhou model. The RMSECs of the merged and Guizhou models were 0.072 6 and 0.079 9, respectively. The predictive ability of the merged model to Yunnan, Sichuan and Guizhou samples was better than that of the Guizhou model, the RMSEP of the merged model was 0.076 0 and 0.079 9 for Yunnan and Sichuan samples and Guizhou samples respectively, and that of the Guizhou model was 0.109 0 and 0.084 6, respectively. The merged model improved the predictive ability to the samples from Yunnan, Sichuan and Guizhou. The results of this study provide references for improving the adaptability of NIR quantitative model for the nicotine in flue-cured tobacco.