Effects of sample surface on the accuracy of near infrared predictive model of air dried density of bamboo

The objective of this study is to investigate the feasibility of using near infrared spectroscopy(NIR) combined with chemometrics analysis to rapidly predict the air-dried density of Phyllostachys pubescens Mazei ex H.de Lebaie.Especially,this study focused on the effects of spectrum collection methods on the accuracy of near infrared predictive model.For comparison,no spectrum treatment procedure was adopted when establishing all the NIR models.The results indicated that the accuracy of models was influenced by the sample surface from which NIR spectra were obtained.The model based on transverse section of bamboo owned the highest accuracy,followed sequentially by the models respectively based on the inner and outer surfaces of bamboo.It was also found that the model accuracy can be substantially improved if the model was based on the average spectra obtained from the outer and inner surfaces of bamboo.This model was then used to predict the air-dried density of 30 unknown bamboo samples,and a good correlation between the measured and predicted values was obtained.