果皮对脐橙可溶性固形物可见/近红外检测精度的影响

利用可见/近红外半透射光谱技术对未剥皮(完整)和剥皮脐橙的可溶性固形物(SSC)进行检测，探索果皮对脐橙SSC检测精度的影响。采用QualitySpec型光谱仪获取未剥皮和剥皮脐橙在350~1 000 nm波段的可见/近红外光谱，并从光谱和模型性能两方面分析果皮的影响。对未剥皮和剥皮脐橙平均光谱进行比较，并提取前20个主成分进行多元方差分析；应用偏最小二乘(PLS)回归结合不同预处理方法分别建立未剥皮和剥皮脐橙SSC的预测模型，对预测模型性能进行比较，并对预测集样本的预测残差平方进行方差分析。结果表明，在5%置信水平下，果皮对脐橙SSC检测精度的影响是显著的。未剥皮和剥皮脐橙SSC的最优PLS模型的预测集相关系数和预测均方根误差分别为0.888，0.456%和0.944，0.324%。

Effect of Pericarp on Prediction Accuracy of Soluble Solid Content in Navel Oranges by Visible/Near Infrared Spectroscopy

Visible/near infrared (Vis/NIR) spectroscopy was used to determine soluble solid content (SSC) of navel oranges with pericarp and without pericarp, and the effect of pericarp on prediction accuracy of SSC of navel oranges was investigated. In addition, Vis/NIR spectra of navel oranges with pericarp and without pericarp were acquired by a QualitySpec spectrometer in the wavelength range of 350~1 000 nm, and the effect of pericarp was analyzed from two aspects of spectrum and model performance. The average spectra of navel oranges with pericarp and without pericarp were compared, and 20 principal components that obtained were used for multivariate analysis of variance (MANOVA). Moreover, partial least squares (PLS) regression combined with different pretreatment methods was used to develop calibration models of SSC for navel oranges with pericarp and without pericarp. Furthermore, the performance of models was compared, and square of prediction residuals of samples in prediction set were used for analysis of variance (ANOVA). The results indicate that the effect of pericarp on prediction accuracy of soluble solid content in navel oranges is significant at 5% confidence level. The correlation coefficients of prediction set and root mean square errors of prediction (RMSEPs) of PLS of SSC for navel oranges with pericarp and without pericarp are 0.888, 0.456% and 0.944, 0.324%, respectively.