采用近红外光谱法对慈竹密度、 抗弯强度和顺纹抗拉强度进行快速预测。 利用反向区间偏最小二乘法(BiPLS)优选光谱区间, 建立原始光谱和不同预处理(一阶微分、 二阶微分、 卷积平滑和归一化处理)光谱分析模型, 同时应用偏最小二乘法(PLS)在全谱范围350～2 500 nm建立各光谱分析模型, 并对所建模型进行比较分析。 结果表明: 同全谱PLS模型相比, BiPLS能够有效选择光谱区间, 并且提高模型预测精度, 其中, 密度、 抗弯强度和顺纹抗拉强度分别选用归一化处理光谱、 二阶微分光谱和一阶微分光谱, BiPLS将全光谱分别划分为30, 20和30个区间时, 建立的密度、 抗弯强度和顺纹抗拉强度BiPLS模型预测效果最好, 预测模型相关系数(R)分别为0.85, 0.88和0.88, 预测标准差(RMSEP)分别为0.052 4, 0.018 5和0.029 2, 表明近红外光谱法可以实现慈竹物理力学性质的预测。

Near infrared spectroscopy was applied to rapidly predict density, modulus of rupture and tensile strength parallel to grain of neosinocalamus affinins. Backward interval partial least squares (BiPLS) was used to find the most informative spectrum ranges, and build models based on raw spectra and pretreated spectra, including first derivative spectra, second derivative spectra, Savitzky-Golay smoothing spectra and standard normalized variate spectra. And partial least squares (PLS) models were also developed in the whole wavelength range 350～2 500 nm. The results show that compared with PLS models, BiPLS could effectively find the optimal spectrum regions and improve the predictive ability of models. The optimal models of density, modulus of rupture and tensile strength parallel to grain were obtained through BiPLS method that separated the whole spectra pretreated by standard normalized variate, second derivative and first derivative respectively into 20, 30 and 20 intervals. And the prediction models of density, modulus of rupture and tensile strength parallel to grain had correlation coefficient (r) 0.85, 0.88 and 0.88, as well as root mean standard error of prediction (RMSEP) 0.052 4, 0.018 5 and 0.029 2, respectively. The relation between NIR predicted values and actual values was good in all cases. Therefore, the experimental results demonstrated that NIR spectroscopy was promising for predicting the physical and mechanical properties of neosinocalamus affinins.