Abstract: In order to study the change of water content of tobacco leaf with their drying time, we explored an effective V-NIR spectral monitoring model of the water content of tobacco leaf through drying experiment in this article. Contraposing the primitive spectral data to the preprocessed spectral data, we built a regression model through cross validation of partial least squares (PLS). It had been found that the PLS model of smoothing data cloud monitor the water content of tobacco leaf very well. In the regression model basing on all wavelengths, there were the regression coefficient r=0.9771, RMSE=0.0742 in training set, r=0.9573, RMSE=0.1009 in cross validation set, and r=0.9683, RMSE=0.0862 in prediction set. The experiment results showed that it was feasible to monitor the water content of tobacco leaf by the PLS model basing on the smoothing primitive spectral data of all wavelengths.