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      연속 초분광 영상 데이터 획득 장치를 이용한 고등어(Scomber japonicus) 신선도 등급 분류 및 판정 = Freshness Classification and Assessment of Mackerel Scomber japonicus Using a Continuous Hyperspectral Imaging Data Acquisition System

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      https://www.riss.kr/link?id=A109457170

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      We aimed to validate the efficacy of a freshness classification model developed through continuous acquisition of hyperspectral data from 500 fresh mackerel Scomber japonicus, speciments. Samples were procured immediately following an auction from the Busan Cooperative Fish Market and subjected to refrigerated storage for 72 h. A custom- designed continuous spectral data acquisition device collected 256 spectral bands within the wavelength range of 900–1,700 nm. Spectral noise reduction was achieved using standard normal variate (SNV) and Savitzky-Golay (SG) filters. Progressive spoilage was confirmed through total volatile basic-nitrogen (TVB-N) analysis, with values increasing from 14.2 to 35.8 mg/100 g over ther 72 h storage duration. Principal components analysis (PCA) revealed spectral pattern variations throughout the storage period, accounting for 96.68% of the total expressed variance. The hyperspectral mean reflectance spectra exhibited primary absorption bands at 1,100, 1,200, and 1,300 nm. A freshness classification model employing partial least squares discriminant analysis (PLS-DA) exhibited robust predictive performance, attaining a maximum accuracy of 93.01%. The devised system demonstrated efficacy in continuous spectral data acquisition for real-time mackerel freshness classification. This device provides foundational data for the future advancement of nondestructive analysis techniques through the refinement of classification models via machine learning and algorithm development.
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      We aimed to validate the efficacy of a freshness classification model developed through continuous acquisition of hyperspectral data from 500 fresh mackerel Scomber japonicus, speciments. Samples were procured immediately following an auction from the...

      We aimed to validate the efficacy of a freshness classification model developed through continuous acquisition of hyperspectral data from 500 fresh mackerel Scomber japonicus, speciments. Samples were procured immediately following an auction from the Busan Cooperative Fish Market and subjected to refrigerated storage for 72 h. A custom- designed continuous spectral data acquisition device collected 256 spectral bands within the wavelength range of 900–1,700 nm. Spectral noise reduction was achieved using standard normal variate (SNV) and Savitzky-Golay (SG) filters. Progressive spoilage was confirmed through total volatile basic-nitrogen (TVB-N) analysis, with values increasing from 14.2 to 35.8 mg/100 g over ther 72 h storage duration. Principal components analysis (PCA) revealed spectral pattern variations throughout the storage period, accounting for 96.68% of the total expressed variance. The hyperspectral mean reflectance spectra exhibited primary absorption bands at 1,100, 1,200, and 1,300 nm. A freshness classification model employing partial least squares discriminant analysis (PLS-DA) exhibited robust predictive performance, attaining a maximum accuracy of 93.01%. The devised system demonstrated efficacy in continuous spectral data acquisition for real-time mackerel freshness classification. This device provides foundational data for the future advancement of nondestructive analysis techniques through the refinement of classification models via machine learning and algorithm development.

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      참고문헌 (Reference)

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      5 Lin X, "Research advances in browning of button mushroom(Agaricus bisporus) : Affecting factors and controlling methods" 90 : 63-75, 2019

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      1 Inanli AG, "The impact of chitosan on seafood quality and human health : A review" 97 : 404-416, 2020

      2 Sivakumar S, "The feasible screening of genuine fresh palmyrah toddy and sugar or rice toddy using near-infrared spectroscopy" 10 : e31516-, 2024

      3 Wilson RH, "Review of short-wave infrared spectroscopy and imaging methods for biological tissue characterization" 20 : 030901-, 2015

      4 Wang H, "Research and application of intelligent hyperspectral analysis technology for Chinese materia medica" 48 : 4320-4327, 2023

      5 Lin X, "Research advances in browning of button mushroom(Agaricus bisporus) : Affecting factors and controlling methods" 90 : 63-75, 2019

      6 Wu D, "Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system" 726 : 57-66, 2012

      7 Li P, "Quantitative analysis of fish meal freshness using an electronic nose combined with chemometric methods" 179 : 109484-, 2021

      8 Hyldig G, "Quality index method-An objective tool for determination of sensory quality" 13 : 71-80, 2005

      9 Hassoun A, "Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods : Advantages and limitations" 57 : 1976-1998, 2015

      10 Nagy MM, "Quality analysis and authentication of nutraceuticals using near IR(NIR)spectroscopy : A comprehensive review of novel trends and applications" 123 : 290-309, 2022

      11 Elmasry G, "Principles and applications of hyperspectral imaging in quality evaluation of agro-food products : A review" 52 : 999-1023, 2012

      12 Huang M, "Prediction of color and moisture content for vegetable soybean during drying using hyperspectral imaging technology" 128 : 24-30, 2014

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      29 Özogul Y, "Freshness assessment of European eel(Anguilla anguilla)by sensory, chemical and microbiological methods" 92 : 745-751, 2005

      30 Folli GS, "Food analysis by portable NIR spectrometer" 1 : 100074-, 2022

      31 Moosavi-Nasab M, "Evaluation of the total volatile basic nitrogen(TVB-N)content in fish fillets using hyperspectral imaging coupled with deep learning neural network and meta-analysis" 11 : 5094-, 2021

      32 Tsai CL, "Effects of blanching and refrigerated storage on quality attributes of hybrid abalone(Haliotidae discushannai×H. diversicolor diversicolor)" 42 : e13608-, 2018

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      35 Cho JS, "Determination of freshness of mackerel(Scomber japonicus)using shortwave infrared hyperspectral imaging" 12 : 2305-, 2023

      36 Park JJ, "Detection of red pepper powder adulteration with allura red and red pepper seeds using hyperspectral imaging" 12 : 3471-, 2023

      37 Jang EH, "Correlation between physicochemical properties of japonica and indica rice starches" 66 : 530-537, 2016

      38 Benjakul S, "Comparative study on physicochemical changes of muscle proteins from some tropical fish during frozen storage" 36 : 787-795, 2003

      39 Yang D, "Combination of spectral and textural information of hyperspectral imaging for the prediction of the moisture content and storage time of cooked beef" 83 : 206-216, 2017

      40 Šimat V, "Chater two-sustainable sources for antioxidant and antimicrobial compounds used in meat and seafood products" 97 : 55-118, 2021

      41 Sohn SI, "An overview of near infrared spectroscopy and its applications in the detection of genetically modified organisms" 22 : 9940-, 2021

      42 Taheri-Garavand A, "An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique" 87 : 434-443, 2015

      43 Kang Z, "Advances in machine learning and hyperspectral imaging in the food supply chain" 14 : 596-616, 2022

      44 Abbas KA, "A review on correlations between fish freshness and pH during cold storage" 4 : 416-421, 2008

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