现代食品科技2017，Vol.33Issue(6)：158-165,8.DOI:10.13982/j.mfst.1673-9078.2017.6.023
旋转速度对壶瓶枣损伤检测影响的研究
Effect of Fruit Rotation Speed on the Detection of Damage in 'Huping' Jujube Fruits
摘要
Abstract
Using a laboratory-installed near-infrared spectroscopy system,three kinds of damaged ‘Huping’ jujube samples,and intact samples,were examined and identified to explore the influence of rotation speed on the detection of damage.Spectral information on fruits with different degrees of damage at three rotation speeds of 1.5 r/min,2.0 r/min,and 2.5 r/min were collected by Fieldspec 3 spectrometer,and the results were calculated based on the measured rotation speed.The partial least squares (PLS) model was built and several discriminant indices were used to determine the best spectral pre-processing method from 13 methods at three rotation speeds.The partial least-squares regression coefficient (PLSRC) method and successive projections algorithm (SPA) were used to extract the characteristic wavelengths of spectra before calibration.The partial least squares-discriminant analysis (PLS-DA),extreme learning machine (ELM),and least squares support vector machines (LS-SVM) were used to establish discrimination models.The results showed that rotation speed had an impact on the detection of the damage in ‘Huping’ jujube fruits.The optimal models at the rotation speeds of 1.5 r/min,2.0 r/min,and 2.5 r/min were PLSRC-LS-SVM,PLSRC-PLS-DA,and PLSRC-PLS-DA,respectively,and the corresponding discrimination accuracies were 92.30％,88.46％,and 86.54％,respectively.The highest damage identification rate was found in the PLSRC-LS-SVM model established at the rotation speed of 1.5 r/min.In addition,with increasing rotation speed,the damage identification rate showed a downward trend.This study provides a theoretical reference for the development of online detection instruments for fresh jujubes.关键词
可见近红外光谱/鲜枣/检测/旋转速度Key words
visible/near infrared spectroscopy/fresh jujube/detection/rotation speed引用本文复制引用
刘蒋龙,张淑娟,王斌,薛建新,赵旭婷..旋转速度对壶瓶枣损伤检测影响的研究[J].现代食品科技,2017,33(6):158-165,8.基金项目
国家自然科学基金资助项目(31271973) （31271973）
