Rapid and nondestructive detection of marine fishmeal adulteration by hyperspectral imaging and machine learning
文献类型： 外文期刊
作者： Kong, Dandan 1 ; Sun, Dawei 3 ; Qiu, Ruicheng 1 ; Zhang, Wenkai 1 ; Liu, Yufei 1 ; He, Yong 1 ;
作者机构： 1.Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310058, Peoples R China
2.Minist Agr & Rural Affairs, Key Lab Spect Sensing, Hangzhou 310058, Peoples R China
3.Zhejiang Acad Agr Sci, Inst Agr Equipment, Hangzhou 310021, Peoples R China
关键词： Fishmeal; Binary adulteration; Processed animal protein; NIR hyperspectral imaging; Support vector machine; Wavelength selection
期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.831； 五年影响因子：4.073 ）
ISSN： 1386-1425
年卷期： 2022 年 273 卷
页码：
收录情况： SCI
摘要： Pure fishmeal (PFM) from whole marine-origin fish is an expensive and indispensable protein ingredient in most aquaculture feeds. In China, the supply shortage of domestically produced PFM has caused frequent PFM adulteration with low-cost protein sources such as feather meal (FTM) and fishmeal from by-products (FBP). The aim of this study was to develop a rapid and nondestructive detection method using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms for the identification of PFM adulterated with FTM, FBP, and the binary adulterant (composed of FTM and FBP). A hierarchical modelling strategy was adopted to acquire a better classification accuracy. Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) coupled with four spectral preprocessing methods were employed to construct classification models. The SVM with baseline offset (BO-SVM) model using 20 effective wavelengths selected by successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) achieved classification accuracy of 100% and 99.43% for discriminating PFM from the adulterants (FTM, FBP) and adulterated fishmeal (AFM), respectively. This study confirmed that NIR-HSI offered a promising technique for feed mills to identify AFM containing FTM, FBP, or binary adulterants. (c) 2022 Elsevier B.V. All rights reserved.
- 相关文献
作者其他论文 更多>>
-
An automated lightweight approach for detecting dead fish in a recirculating aquaculture system
作者：Zhou, Chengquan;Wang, Chenye;Sun, Dawei;Hu, Jun;Ye, Hongbao;Wang, Chenye
关键词：YOLO; Dead fish; RAS; Image processing; Lightweight framework
-
Fd-CasBGRel: A Joint Entity-Relationship Extraction Model for Aquatic Disease Domains
作者：Ye, Hongbao;Lv, Lijian;Ye, Hongbao;Lv, Lijian;Zhou, Chengquan;Sun, Dawei;Ye, Hongbao;Zhou, Chengquan;Sun, Dawei
关键词：relational extraction; aquatic diseases; Casrel; fine-tuned pretrained model; self-attention mechanisms; relative position coding; BiLSTM; GHM loss function
-
3D-based precise evaluation pipeline for maize ear rot using multi-view stereo reconstruction and point cloud semantic segmentation
作者：Yang, Rui;He, Yong;Lu, Xiangyu;Liu, Fei;Zhao, Yiying;Li, Yanmei;Yang, Yinhui;Kong, Wenwen
关键词：Maize ear rot; Multi-view stereo reconstruction; Point cloud; 3D semantic segmentation; Deep learning
-
Development and comparison of classification models on VIS-NIR hyperspectral imaging spectra for qualitative detection of the Staphylococcus aureus in fresh chicken breast
作者：Qiu, Ruicheng;Qiu, Ruicheng;Kong, Dandan;Wu, Na;He, Yong;Qiu, Ruicheng;Kong, Dandan;Wu, Na;He, Yong;Zhao, Yinglei
关键词：Food pathogens; Hyperspectral imaging; Convolutional neural network; Deep learning; Chicken
-
Classification of multi-year and multi-variety pumpkin seeds using hyperspectral imaging technology and three-dimensional convolutional neural network
作者：Li, Xiyao;Fang, Hui;Yang, Ningyuan;Yang, Guofeng;Yu, Zeyu;He, Yong;Feng, Xuping;Shen, Jia;Geng, Wei
关键词：Classification; Seed; Hyperspectral imaging; Deep learning
-
Dynamic UAV Phenotyping for Rice Disease Resistance Analysis Based on Multisource Data
作者：Bai, Xiulin;He, Yong;Zhang, Jinnuo;Tao, Mingzhu;Wu, Qingguan;Yang, Guofeng;Feng, Xuping;Fang, Hui;Wei, Yuzhen;Tang, Yu;Tang, Lie;Lou, Binggan;Deng, Shuiguang;Yang, Yong
关键词：
-
Spatial heterogeneity analysis of silique chlorophyll a fluorescence-based photosynthetic traits for rapeseed yield and quality assessment
作者：Zhai, Li;Abdalla, Alwaseela;Zhou, Yu-an;Cen, Haiyan;Zhai, Li;Abdalla, Alwaseela;Zhou, Yu-an;Cen, Haiyan;Zhou, Weijun;Zhou, Weijun;Sun, Dawei
关键词：Oilseed rape; Silique; Photosynthesis; Yield and quality; Spatial heterogeneity
