食品科学2024，Vol.45Issue(19)：8-14,7.DOI:10.7506/spkx1002-6630-20230725-283
基于CARS-SPA特征提取的黄水淀粉近红外光谱定量模型优化
Optimization of Quantitative Modeling of Starch in Huangshui Based on Near-Infrared Spectral Feature Extraction Using Competitive Adaptive Reweighted Sampling Combined with Successive Projections Algorithm
摘要
Abstract
In order to improve the accuracy and efficiency of predictive modeling of the starch content of Huangshui,a byproduct of Baijiu production by solid-state fermentation,spectral information of Huangshui was collected using a Fourier transform near-infrared(FTIR)spectrometer and preprocessed by first derivative.Based on the preprocessed spectra,a predictive model for the starch content of Huangshui was developed using partial least squares regression(PLSR),and its performance was evaluated by determination coefficient(R)and root mean square error of prediction(RMSEP).As the original spectra contained a lot of redundant information,in order to effectively improve the detection accuracy and to optimize the modeling efficiency,the advantages of different feature extraction methods were combined.Finally,it was found that the PLSR model established by using the spectral features extracted by competitive adaptive reweighted sampling(CARS)combined with the successive projections algorithm(SPA)was significantly better than the model built without feature extraction or using single feature extraction.The results showed that the R2 and RMSEP of the model established using CARS were 0.965 4 and 0.201 2％,while those obtained using CARS-SPA were 0.973 8 and 0.174 8％,respectively.The spectral dimension reduced from 2 203 to 126 after the combination of CARS with SPA,which improved both the prediction accuracy and the modeling efficiency.The method proposed in this study provides an effective means to optimize near-infrared spectral quantitative modeling of starch in Huangshui.关键词
黄水/近红外光谱/竞争性自适应重加权算法/连续投影算法/偏最小二乘回归法Key words
Huangshui/near infrared spectroscopy/competitive adaptive reweighted sampling/successive projections algorithm/partial least squares regression分类
轻工业引用本文复制引用
母雯竹,张贵宇,张维,姚瑞,付妮..基于CARS-SPA特征提取的黄水淀粉近红外光谱定量模型优化[J].食品科学,2024,45(19):8-14,7.基金项目
四川省科技计划项目(2022YFS0554) （2022YFS0554）
泸州老窖研究生创新基金项目(LJCX-2022-8) （LJCX-2022-8）
酿酒生物技术及应用四川省重点实验室开放课题(NJ2022-06) （NJ2022-06）
四川轻化工大学科技成果转化专项(HXJY01) （HXJY01）
五粮液产学研合作项目(CXY2022ZR007) （CXY2022ZR007）
