Abstract
［［Objective ］］ To improve the classification accuracy of edible vegetable oils,an identification model based on three -dimensional fluorescence spectroscopy and ISSA -SVM was established.［［Methods ］］ Combining the feature information of three -dimensional fluorescence spectroscopy,an improved sparrow search algorithm was used to optimize the parameters of the SVM model,constructing an edible vegetable oil identification method that integrates the characteristics of three -dimensional fluorescence spectroscopy information and the ISSA -SVM model.［［Results］］ Compared with the SVM model,GA -SVM model,PSO -SVM model,and SSA -SVM model,the classification accuracy of the ISSA -SVM model for edible vegetable oils reached 100%.［［Conclusion ］］ The ISSA -SVM model has higher convergence efficiency,system stability,and the ability to avoid local optimal solutions,which can effectively cope with complex and variable sample classification tasks.
Publication Date
2-18-2025
First Page
53
Last Page
61
DOI
10.13652/j.spjx.1003.5788.2024.60122
Recommended Citation
Jing, ZHANG; Guohong, QI; Jingzhao, CHEN; Xiaoli, CAO; and Lili, LI
(2025)
"Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM,"
Food and Machinery: Vol. 40:
Iss.
10, Article 8.
DOI: 10.13652/j.spjx.1003.5788.2024.60122
Available at:
https://www.ifoodmm.cn/journal/vol40/iss10/8
References
[1] 程朋飞,朱燕萍,潘金燕,等.三维荧光光谱结合 IGOA-SVM分类鉴别油类污染物 [J].光谱学与光谱分析,2024,44（4）:1 031-1 038.CHENG P F,ZHU Y P,PAN J Y,et al.Classification and identification of oil pollutants based on three-dimensional fluorescence spectroscopy combined with IGOA-SVM [J].Spectroscopy and Spectral Analysis,2024,44（4）:1 031-1 038.
[2] 王书涛,刘娜,程琪,等.三维荧光光谱结合 GA-SVM 对多环芳烃的分类鉴别 [J].光谱学与光谱分析,2020,40（4）:1 149-1 155.WANG S T,LIU N,CHENG Q,et al.Classification and identification of polycyclic aromatic hydrocarbons based on three-dimensional fluorescence spectroscopy combined with GA-SVM [J].Spectroscopy and Spectral Analysis,2020,40（4）:1 149-1 155.
[3] 徐瑞煜,朱焯炜,胡扬俊,等.三维荧光光谱结合 PCA-SVM 对几种浓香型白酒的鉴别 [J].光谱学与光谱分析,2016,36（4）:1 021-1 026.XU R Y,ZHU Z W,HU Y J,et al.Identification of several strong aroma wine types based on three-dimensional fluorescence spectroscopy combined with PCA-SVM [J].Spectroscopy and Spectral Analysis,2016,36（4）:1 021-1 026.
[4] SIKORSKA E,GÓRECKI T,KHMELINSKII I V,et al.Classification of edible oils using synchronous scanning fluorescence spectroscopy [J].Food Chemistry,2005,89（2）:217-225.
[5] POULLI K I,MOUSDIS G A,GEORGIOU C A.Synchronous |fluorescence spectroscopy for quantitative determination of virgin olive oil adulteration with sunflower oil [J].Analytical & Bioanalytical Chemistry,2006,386（5）:1 571-1 575.
[6] NTAKATSANE M P,LIU X M,ZHOU P.Short communication:rapid detection of milk fat adulteration with vegetable oil by fluorescence spectroscopy [J].Journal of Dairy Science,2013,96（4）:2 130-2 136.
[7] GUZMÁN E,BAETEN V,PIERNA J A F,et al.Evaluation of the overall quality of olive oil using fluorescence spectroscopy[J].Food Chemistry,2015,173:927-934.
[8] STOKES T D,FOTEINI M,BROWNFIELD B,et al.Feasibility assessment of synchronous fluorescence spectral fusion by application to argan oil for adulteration analysis [J].Applied Spectroscopy,2018,72（3）:432-441.
[9] 王书涛,刘诗瑜,王志芳,等.基于 ICSO-SVM 和三维荧光光谱的山梨酸钾浓度检测 [J].光谱学与光谱分析,2020,40（5）:1 614-1 619.WANG S T,LIU S Y,WANG Z F,et al.Detection of potassium sorbate concentration based on ICSO-SVM and three-dimensional fluorescence spectroscopy [J].Spectroscopy and Spectral Analysis,2020,40（5）:1 614-1 619.
[10] 王书涛,彭涛,李明珊,等.基于三维荧光光谱和 PSO-SVM对胭脂红含量的测定 [J].光谱学与光谱分析,2019,39（1）:150-155.WANG S T,PENG T,LI M S,et al.Determination of carmine content based on three-dimensional fluorescence spectroscopy and PSO-SVM [J].Spectroscopy and Spectral Analysis,2019,39（1）:150-155.
[11] 陈珏,李佳琮,刘翠玲,等.荧光光谱技术结合机器学习算法检测大白菜中吡虫啉含量 [J].食品安全质量检测学报,2023,14（13）:134-140.CHEN J,LI J C,LIU C L,et al.Determination of imidacloprid in cabbage by fluorescence spectroscopy combined with machine learning algorithms [J].Journal of Food Safety and Quality,2023,14（13）:134-140.
[12] 吴梅凤,李杨,李敏敏,等.三维荧光光谱法快速检测橄榄油中掺假廉价油 [J].食品安全质量检测学报,2024,15（5）:289-297.WU M F,LI Y,LI M M,et al.Rapid detection of adulterated cheap oil in olive oil by three-dimensional fluorescence spectrometry [J].Journal of Food Safety and Quality,2024,15（5）:289-297.
[13] XUE J,SHEN B.A novel swarm intelligence optimization approach:sparrow search algorithm [J].Systems Science & Control Engineering:An Open Access Journal,2020,8（1）:22-34.
[14] 黄崇富,常宇,刘力超.基于改进鲸鱼算法和神经网络的食品 机 器 人 能 耗 轨 迹 规 划 [J].食 品 与 机 械,2022,38（9）:108-113.HUANG C F,CHANG Y,LIU L C.Energy consumption path planning of food robot based on improved whale algorithm and neural network [J].Food & Machinery,2022,38（9）:108-113.[15] TUERXUN W,CHANG X,GUO H Y,et al.Fault diagnosis of wind turbines based on a support vector machine optimized by the sparrow search algorithm [J].IEEE Access,2021,9:69 307-69 315.
[16] 王少英.基于改进型循环神经网络算法的食品包装智能实时识别系统研究 [J].食品与机械,2023,39（9）:110-116.WANG S Y.Research on intelligent real-time identification system of traffic signs based on improved recurrent neural network algorithm [J].Food & Machinery,2023,39（9）:110-116.
[17] DORNAIKA F,BOSAGHZADEH A,SALMANE H,et al.Graph-based semi-supervised learning with local binary patterns for holistic object categorization [J].Expert Systems with Applications,2014,41（17）:7 744-7 753.
[18] LIU W,DUAN C W,YU B,et al.Multi-pose pedestrian detection based on posterior HOG feature [J].Acta Electronica Sinica,2015,43（2）:217-224.
[19] 赖嘉雯,汪宇玲,蔡晓宇,等.基于 CNN-SVM 的多维度信息融合半月板撕裂分类方法 [J].波谱学杂志,2023,40（4）:423-434.LAI J W,WANG Y L,CAI X Y,et al.Multidimensional information fusion method for meniscal tear classification based on CNN-SVM [J].Chinese Journal of Magnetic Resonance,2023,40（4）:423-434.
[20] 李旭东,李艳军,曹愈远,等.基于 CNN-SVM 的飞机 EHA故障 诊 断 算 法 研 究 [J].西 北 工 业 大 学 学 报,2023,41（1）:230-240.LI X D,LI Y J,CAO Y Y,et al.Study on fault diagnosis algorithms of EHA based on CNN-SVM [J].Journal of Northwestern Polytechnical University,2023,41（1）:230-240.
[21] 方明明,刘静.基于回归卷积神经网络的近红外光谱苹果脆片品质评价方法研究 [J].食品科技,2020,45（7）:303-308.FANG M M,LIU J.Evaluation method of apple chips quality by near infrared spectroscopy based on regressive convolutional neural network [J].Food Science and Technology,2020,45（7）:303-308.
[22] 王浩云,李晓凡,李亦白,等.基于高光谱图像和 3D-CNN的苹果多品质参数无损检测 [J].南京农业大学学报,2020,43（1）:178-185.WANG H Y,LI X F,LI Y B,et al.Research on non-destructive detection of apple multi-quality parameters based on hyperspectral imaging technology and 3D-CNN [J].Journal of Nanjing Agricultural University,2020,43（1）:178-185.
[23] LIU Y,ZENG L,HUANG Y.An efficient HOG-ALBP feature for pedestrian detection [J].Signal Image and Video Processing,2014,8（1）:125-134.
[24] XUE D X,ZHANG R,FENG H,et al.CNN-SVM for microvascular morphological type recognition with data augmentation [J].Journal of Medical and Biological Engineering,2016,36（6）:755-764.
[25] VALAPPIL N K,MEMON Q A.CNN-SVM based vehicle detection for UAV platform [J].International Journal of Hybrid Intelligent Systems,2021,17（1）:1-12.
