Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis
In order to quickly, nondestructively, and effectively distinguish red jujube varieties, based on the combination of fuzzy theory and improved LDA (iLDA), fuzzy improved linear discriminant analysis (FiLDA) algorithm was proposed to classify near-infrared reflectance (NIR) spectra of red jujube samp...
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MDPI AG
2022-03-01
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Online Access: | https://www.mdpi.com/2304-8158/11/5/763 |
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author | Zuxuan Qi Xiaohong Wu Yangjian Yang Bin Wu Haijun Fu |
author_facet | Zuxuan Qi Xiaohong Wu Yangjian Yang Bin Wu Haijun Fu |
author_sort | Zuxuan Qi |
collection | DOAJ |
description | In order to quickly, nondestructively, and effectively distinguish red jujube varieties, based on the combination of fuzzy theory and improved LDA (iLDA), fuzzy improved linear discriminant analysis (FiLDA) algorithm was proposed to classify near-infrared reflectance (NIR) spectra of red jujube samples. FiLDA shows performs better than iLDA in dealing with NIR spectra containing noise. Firstly, the portable NIR spectrometer was employed to gather the NIR spectra of five kinds of red jujube, and the initial NIR spectra were pretreated by standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Savitzky-Golay smoothing (S-G smoothing), mean centering (MC) and Savitzky-Golay filter (S-G filter). Secondly, the high-dimensional spectra were processed for dimension reduction by principal component analysis (PCA). Then, linear discriminant analysis (LDA), iLDA and FiLDA were applied to extract features from the NIR spectra, respectively. Finally, K nearest neighbor (KNN) served as a classifier for the classification of red jujube samples. The highest classification accuracy of this identification system for red jujube, by using FiLDA and KNN, was 94.4%. These results indicated that FiLDA combined with NIR spectroscopy was an available method for identifying the red jujube varieties and this method has wide application prospects. |
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language | English |
last_indexed | 2024-03-09T20:38:40Z |
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spelling | doaj.art-24deba893c624fa797e1d6d6ad213d212023-11-23T23:02:06ZengMDPI AGFoods2304-81582022-03-0111576310.3390/foods11050763Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant AnalysisZuxuan Qi0Xiaohong Wu1Yangjian Yang2Bin Wu3Haijun Fu4School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaResearch Institute of Zhejiang University-Taizhou, Taizhou 317700, ChinaDepartment of Information Engineering, Chuzhou Polytechnic, Chuzhou 239000, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, ChinaIn order to quickly, nondestructively, and effectively distinguish red jujube varieties, based on the combination of fuzzy theory and improved LDA (iLDA), fuzzy improved linear discriminant analysis (FiLDA) algorithm was proposed to classify near-infrared reflectance (NIR) spectra of red jujube samples. FiLDA shows performs better than iLDA in dealing with NIR spectra containing noise. Firstly, the portable NIR spectrometer was employed to gather the NIR spectra of five kinds of red jujube, and the initial NIR spectra were pretreated by standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Savitzky-Golay smoothing (S-G smoothing), mean centering (MC) and Savitzky-Golay filter (S-G filter). Secondly, the high-dimensional spectra were processed for dimension reduction by principal component analysis (PCA). Then, linear discriminant analysis (LDA), iLDA and FiLDA were applied to extract features from the NIR spectra, respectively. Finally, K nearest neighbor (KNN) served as a classifier for the classification of red jujube samples. The highest classification accuracy of this identification system for red jujube, by using FiLDA and KNN, was 94.4%. These results indicated that FiLDA combined with NIR spectroscopy was an available method for identifying the red jujube varieties and this method has wide application prospects.https://www.mdpi.com/2304-8158/11/5/763red jujubenear-infrared spectroscopyfeature extractionfuzzy set theoryclassification |
spellingShingle | Zuxuan Qi Xiaohong Wu Yangjian Yang Bin Wu Haijun Fu Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis Foods red jujube near-infrared spectroscopy feature extraction fuzzy set theory classification |
title | Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis |
title_full | Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis |
title_fullStr | Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis |
title_full_unstemmed | Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis |
title_short | Discrimination of the Red Jujube Varieties Using a Portable NIR Spectrometer and Fuzzy Improved Linear Discriminant Analysis |
title_sort | discrimination of the red jujube varieties using a portable nir spectrometer and fuzzy improved linear discriminant analysis |
topic | red jujube near-infrared spectroscopy feature extraction fuzzy set theory classification |
url | https://www.mdpi.com/2304-8158/11/5/763 |
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