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Study on Moisture Content Prediction of Tobacco Leaf Based on Near Infrared Spectroscopy

文献类型： 会议论文

第一作者： Fushan Sun

作者： Fushan Sun 1 ; Hao Liu 1 ; Lingfeng Meng 1 ; Songfeng Wang 1 ; Aihua Wang 1 ; Haina Du 2 ; Panzhen Zhao 2 ;

作者机构： 1.Key Laboratory of Tobacco Biology and Processing, Ministry of Agriculture Institute of Tobacco Research of CAAS, Qingdao, China

2.Key Laboratory of Tobacco Biology and Processing, Ministry of Agriculture Institute of Tobacco Research of CAAS, Qingdao, China|Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China

关键词： Adaptation models;Spectroscopy;Computational modeling;Noise;Moisture;Interference;Predictive models

会议名称： Asian Conference on Artificial Intelligence Technology

主办单位：

页码： 1413-1418

摘要： In order to realize rapid nondestructive testing of moisture content of fresh tobacco leaves, near infrared spectroscopy was used to collect fresh tobacco leaves.The effects of four pretreatment methods, Multiple scatter correction (MSC), Standard normal variate (SNV), Normalize and Autoscales, on the accuracy of the model were compared.It was found that the model established after pretreatment with MSC had the best effect, Model R2 was 0.8145 and RMSE was 0.1185.Two feature band screening methods, continuous projection method (SPA) and competitive adaptive weighted weight algorithm (CARS), were selected for wavelength selection based on the spectral data pretreated by MSC.The results showd that the established MSC-CARS-SVM model has the best effect, with the R2 was 0.8381 and the root mean square error was 0.1158.It was proved that the near infrared spectroscopy technique could be used to detect the moisture content of fresh tobacco leaf rapidly and nondestructively.

分类号： tp18-53

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