基于CARS-SPA特征提取的黄水淀粉近红外光谱定量模型优化OA北大核心CSTPCD
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
为提高白酒固态发酵的副产物黄水中淀粉含量预测模型精度和建模效率.采用傅里叶变换近红外光谱仪采集黄水光谱信息,利用一阶导数对光谱进行预处理,并结合偏最小二乘回归(partial least squares regression,PLSR)建立黄水淀粉定量预测模型.使用决定系数(R2)和预测均方误差(root mean square error of prediction,RMSEP)评价模型性能.光谱中含有大量冗余信息,为有效提升黄水淀粉含量检测精…查看全部>>
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 …查看全部>>
母雯竹;张贵宇;张维;姚瑞;付妮
四川轻化工大学人工智能四川省重点实验室,四川宜宾 644005四川轻化工大学人工智能四川省重点实验室,四川宜宾 644005四川轻化工大学人工智能四川省重点实验室,四川宜宾 644005四川轻化工大学人工智能四川省重点实验室,四川宜宾 644005四川轻化工大学人工智能四川省重点实验室,四川宜宾 644005
轻工业
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
Huangshuinear infrared spectroscopycompetitive adaptive reweighted samplingsuccessive projections algorithmpartial least squares regression
《食品科学》 2024 (19)
8-14,7
四川省科技计划项目(2022YFS0554)泸州老窖研究生创新基金项目(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)四川轻化工大学科技成果转化专项(HXJY01)五粮液产学研合作项目(CXY2022ZR007)
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