Academic Journal

Research on Detection of Multi-adulteration of Sesame Oils by Near-infrared Spectroscopy

التفاصيل البيبلوغرافية
العنوان: Research on Detection of Multi-adulteration of Sesame Oils by Near-infrared Spectroscopy
المؤلفون: LUO, Qing-song, YU, Ya-ru, XU, Qiang, CHEN, Yang, ZHENG, Xiao
المصدر: DEStech Transactions on Computer Science and Engineering; 2nd International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA 2018) ; 2475-8841
بيانات النشر: DEStech Publications, Inc.
سنة النشر: 2019
المجموعة: DPI Journals (Destech Publications)
مصطلحات موضوعية: Multi-adulteration, Sesame oil, Near-infrared spectroscopy, Support vector machine
الوصف: Aiming at the adulteration of sesame oil, our research is focused on using near-infrared spectroscopy combined with chemometrics to achieve rapid detection. The near-infrared spectrum of the sample was collected, and the data analysis and modeling were conducted on MATLAB. The raw spectral data was pretreated using multiplicative scatter correction (MSC) and standard normal variate (SNV). Support vector machine (SNM) model was established by using competitive adaptive reweighed sampling (CARS) and combined synergy interval partial least squares (SiPLS) to select characteristic spectral data. The highest correct recognition rate of the qualitative model is 100%, the mean square error MSE of the quantitative model is 0.0829, and the correlation error R is 99.0772%. The results prove that the support vector machine classification model established by near-infrared spectroscopy combined with chemometrics can qualitatively detect whether sesame oil is adulterated. In the meanwhile, the SNM model can quantitatively predict the content of active components.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
Relation: https://www.dpi-journals.com/index.php/dtcse/article/view/27557
DOI: 10.12783/dtcse/msota2018/27557
الاتاحة: https://www.dpi-journals.com/index.php/dtcse/article/view/27557
https://doi.org/10.12783/dtcse/msota2018/27557
Rights: Copyright (c) 2019 DEStech Transactions on Computer Science and Engineering
رقم الانضمام: edsbas.2A2B8652
قاعدة البيانات: BASE
الوصف
DOI:10.12783/dtcse/msota2018/27557