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Optimizing Rice Near-Infrared Models Using Fractional Order Savitzky–Golay Derivation (FOSGD) Combined with Competitive Adaptive Reweighted Sampling (CARS)

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成果类型:
期刊论文
作者:
Xia, Zhenzhen;Yang, Jie;Wang, Jing;Wang, Shengpeng;Liu, Yan*
通讯作者:
Liu, Yan
作者机构:
[Yang, Jie; Xia, Zhenzhen; Wang, Jing] Minist Agr, Inst Agr Qual Stand & Testing Technol Res, Hubei Acad Agr Sci, Lab Qual & Safety Risk Assessment Agroprod Wuhan, Wuhan, Peoples R China.
[Wang, Shengpeng] Hubei Acad Agr Sci, Inst Fruit & Tea, Wuhan, Peoples R China.
[Liu, Yan] Wuhan Polytech Univ, Coll Food Sci & Engn, Wuhan, Peoples R China.
[Liu, Yan] Wuhan Polytech Univ, Xue Fu South Rd 68, Wuhan 430023, Peoples R China.
通讯机构:
[Liu, Yan] W
Wuhan Polytech Univ, Xue Fu South Rd 68, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
NIR;PLS;Rice quality;competitive adaptive reweighted sampling;fractional order Savitzky-Golay derivation;near-infrared spectroscopy;partial least squares
期刊:
Applied Spectroscopy
ISSN:
0003-7028
年:
2020
卷:
74
期:
4
页码:
417-426
基金类别:
youth foundation of Hu Bei Academy of Agricultural Sciences [2017NKYJJ15]
机构署名:
本校为通讯机构
院系归属:
食品科学与工程学院
摘要:
Developing a rapid and stable method for analyzing the quality parameters of rice is important. Near-infrared (NIR) spectroscopy combined with chemometric techniques have been used to predict the critical contents of rice and shown its accuracy and stability. To further improve the predictive ability, we combine the derivative method of fractional order Savitzky–Golay derivation (FOSGD) with the wavelength selection method of competitive adaptive reweighted sampling (CARS). Compared with the traditional integer order Savitzky–Golay derivation...

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