کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7062933 | 1459782 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification of oil, sugar and crude fiber during tobacco (Nicotiana tabacum L.) seed development based on near infrared spectroscopy
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کلمات کلیدی
PLSRC2RP2LVSSNVLS-SVMRPDMSCRMSEPRMSECVRBFNIRStandard normal variate - استاندارد عادیstandard deviation - انحراف معیارSeed composition - ترکیب دانهmultiplicative scatter correction - تصحیح پراکندگی multiplicativeSeed development - توسعه بذرPartial least squares - حداقل مربعات جزئی Radial basis function - عملکرد پایه شعاعیSVM - ماشین بردار پشتیبانیSupport vector machine - ماشین بردار پشتیبانیLatent variables - متغیرهای باقیماندهNear Infrared spectroscopy - نزدیک به طیف سنجی مادون قرمزleast-squares support vector machine - کمترین مربعات دستگاه بردار پشتیبانی می کند
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
تکنولوژی و شیمی فرآیندی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Tobacco seeds are a potential feedstock for biofuels. To insure make full use of tobacco seed biomass, the present study was carried out to estimate seed oil, sugar and crude fiber during seed development through near infrared spectroscopy (NIRS) nondestructive determination. Four pre-processing methods, Savitzky-Goly after standard normal variate (SNV-SG), first Savitzky-Goly derivative after standard normal variate (SNV-SG-1stD), Savitzky-Goly after multiplicative scatter correction (MSC-SG) and first Savitzky-Goly derivative after multiplicative scatter correction (MSC-SG-1stD), were respectively performed to optimize the original spectra before establishment of the calibration models. Then linear partial least squares (PLS) and nonlinear least-squares support vector machine (LS-SVM) methods were utilized to develop the calibration models, in which the LS-SVM models were found to have better performance than PLS models. The best LS-SVM models of oil, sugar and crude fiber were established after pre-processed by MSC-SG-1st D. These results indicated that NIRS was suitable to rapidly and accurately analyze tobacco seed composition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biomass and Bioenergy - Volume 111, April 2018, Pages 39-45
Journal: Biomass and Bioenergy - Volume 111, April 2018, Pages 39-45
نویسندگان
Zhan Li, Cheng Li, Yue Gao, Wenguang Ma, Yunye Zheng, Yongzhi Niu, Yajing Guan, Jin Hu,