太赫兹融合光谱结合改进Fused Lasso模型在转基因菜籽油鉴别中的应用OA北大核心CSTPCD

Existing classification and identification models for transgenic rapeseed oil based on single-spec-trum analysis suffer from limited information and high data dimensionality,leading to low operational effi-ciency and inaccurate detection results.To address these issues,a novel classification method for transgen-ic rapeseed oil was proposed,leveraging terahertz fusion spectroscopy combined with an improved Fused Lasso model.Using two types of transgenic rapeseed oil and two types of non-transgenic rapeseed oil as research subjects,the terahertz time-domain spectroscopy(THz-TDS)system was employed to obtain the terahertz absorption spectra of the four rapeseed oil samples in the frequency range of 0.2 to 1.6 THz.Features were extracted from the absorption and derivative spectra using the successive projections algo-rithm(SPA),and then fused.Introducing a regularization sparse model,Fused Lasso,which integrates feature selection and classification.This model was improved into a multi-class model using the one-vs-one(OVO)method,and Bayesian optimization(BO)was employed to optimize its regularization parame-ters.The results demonstrated that the BO-Fused Lasso model,based on fusion spectra,significantly out-performed the traditional Fused Lasso model based on a single absorption spectrum in classifying the four types of rapeseed oil.The accuracy rates for the training and testing sets were 96.88%and 95.00%,re-spectively.This study,therefore,presents a novel approach for accurately identifying transgenic and non-transgenic rapeseed oils and provides a valuable reference for the detection of other transgenic substances.