CAJ | 학술논문

采用光纤漫反射光谱采集模式,采集未经预处理皮棉的近红外光谱,对比不同的光谱预处理方式,应用偏最小二乘回归建立皮棉杂质含量预测模型,判别分析法分类皮棉和杂质含量级别.采用一阶微分光谱预处理,使用3个主成分建立的杂质含最PLS模型预测相关系数r为0.906,RMSEC为0.440,RMSEP为0.823;采用判别分析,分类含有植物性杂质皮棉和纯皮棉,使用15个主成分准确度达到95.4%;判别含有多类杂质皮棉,分类准确率仅能达到80.9%.而杂质含量级别分类效果不佳.研究表明,皮棉近红外光谱可以预测皮棉中杂质含量等指标,但受到杂质含量、类型和均匀度的影响,后续研究应通过透射采集模式等方法,改善光谱质量,提高预测精度.
채용광섬만반사광보채집모식,채집미경예처리피면적근홍외광보,대비불동적광보예처리방식,응용편최소이승회귀건립피면잡질함량예측모형,판별분석법분류피면화잡질함량급별.채용일계미분광보예처리,사용3개주성분건립적잡질함최PLS모형예측상관계수r위0.906,RMSEC위0.440,RMSEP위0.823;채용판별분석,분류함유식물성잡질피면화순피면,사용15개주성분준학도체도95.4%;판별함유다류잡질피면,분류준학솔부능체도80.9%.이잡질함량급별분류효과불가.연구표명,피면근홍외광보가이예측피면중잡질함량등지표,단수도잡질함량、류형화균균도적영향,후속연구응통과투사채집모식등방법,개선광보질량,제고예측정도.
Near infrared (NIR) spectroscopy was investigated to predict trash content and classify types of ginned cotton by using a fiber-optic in diffuse reflectance mode.Different spectra preprocessing methods were compared,and partial least-squares (PLS) regression was established to predict the trash content of ginned cotton.Discriminant analysis (DA) was used to classify various types of lint and content level of trash.The correlation coefficient r was 0.906 for optimal PLS model using three factors based on first-order derivative spectra,and RMSEC and RMSEP was 0.440 and 0.823 respectively.To classify ginned cotton with and without plant trash,the accuracy rate reached 95.4% using 15 principal components (PCs) via DA,whereas the prediction accuracy rate was only 80.9% for the classification of sample types due to containing foreign fiber,and the classification result for the content level of trash in lint was not good for the samples without any preprocessing.The result indicated that the NIR spectra of sample can be used to predict trash content in ginned cotton,which is often disturbed by type,content and distribution of foreign matters,and the accuracy of some prediction model is unsatisfactory.In order to improve the prediction accuracy,some methods would he applied in future research,such as pretreatment according to acquisition request of solid sample,or using transmission mode.