A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy
To establish a model based on near-infrared (NIR) spectra for quickly detecting the freshness of frozen crayfish, NIR spectra of thawed crayfish (tail, meat, and mince) were collected, and data were pretreated by first derivative, multiple scattering correction, wavelet transform (WT), or standard n...
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| Format: | Article |
| Language: | English |
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China Food Publishing Company
2024-01-01
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| Series: | Shipin Kexue |
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| Online Access: | https://www.spkx.net.cn/fileup/1002-6630/PDF/2024-45-2-037.pdf |
| _version_ | 1797303301125963776 |
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| author | ZHAN Ke, CHEN Jiwang, XU Yan, NI Yangfan, LIU Yan, ZOU Shengbi |
| author_facet | ZHAN Ke, CHEN Jiwang, XU Yan, NI Yangfan, LIU Yan, ZOU Shengbi |
| author_sort | ZHAN Ke, CHEN Jiwang, XU Yan, NI Yangfan, LIU Yan, ZOU Shengbi |
| collection | DOAJ |
| description | To establish a model based on near-infrared (NIR) spectra for quickly detecting the freshness of frozen crayfish, NIR spectra of thawed crayfish (tail, meat, and mince) were collected, and data were pretreated by first derivative, multiple scattering correction, wavelet transform (WT), or standard normal transform. The original and pretreated spectral data were correlated to total volatile basic nitrogen (TVB-N) contents using partial least squares (PLS) or convolutional neural network (CNN), and different quantitative prediction models were established and compared. The best model was selected to investigate its accuracy and applicability. The results showed that pretreatment methods had a significant influence on the accuracy of the model, and the CNN model established after spectral preprocessing had a better ability to predict the TVB-N content of crayfish compared with the PLS model. The CNN model based on the WT pretreated spectra of crayfish meat had the highest prediction accuracy for the validation set with correlation coefficients of 0.97 and 0.96, and root mean square errors of 1.26 and 0.93 mg/100 g for the calibration set and validation set, respectively. Moreover, the accuracy, precision, and sensitivity of the NIR method were within reasonable limits, and it had good figures of merit. According to the requirements of fast operation, accurate results, and low damage in practice, the WT-CNN-crayfish meat model was determined as the optimal model for predicting the TVB-N content in frozen crayfish. These results suggested that the WT-CNN-crayfish meat model have a great potential for predicting the TVB-N content and rapidly evaluating the freshness of frozen crayfish. |
| first_indexed | 2024-03-07T23:50:55Z |
| format | Article |
| id | doaj.art-3e0e30042bbe4d7c90d59fa12a06b0ee |
| institution | Directory Open Access Journal |
| issn | 1002-6630 |
| language | English |
| last_indexed | 2024-03-07T23:50:55Z |
| publishDate | 2024-01-01 |
| publisher | China Food Publishing Company |
| record_format | Article |
| series | Shipin Kexue |
| spelling | doaj.art-3e0e30042bbe4d7c90d59fa12a06b0ee2024-02-19T05:50:22ZengChina Food Publishing CompanyShipin Kexue1002-66302024-01-0145229930710.7506/spkx1002-6630-20230418-177A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared SpectroscopyZHAN Ke, CHEN Jiwang, XU Yan, NI Yangfan, LIU Yan, ZOU Shengbi0(1. College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China; 2. Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), Wuhan 430023, China; 3. National Research & Development Branch Center for Crayfish Processing (Qianjiang), Qianjiang 433100, China; 4. Wuhan Agricultural Inspection Center, Wuhan 430016, China)To establish a model based on near-infrared (NIR) spectra for quickly detecting the freshness of frozen crayfish, NIR spectra of thawed crayfish (tail, meat, and mince) were collected, and data were pretreated by first derivative, multiple scattering correction, wavelet transform (WT), or standard normal transform. The original and pretreated spectral data were correlated to total volatile basic nitrogen (TVB-N) contents using partial least squares (PLS) or convolutional neural network (CNN), and different quantitative prediction models were established and compared. The best model was selected to investigate its accuracy and applicability. The results showed that pretreatment methods had a significant influence on the accuracy of the model, and the CNN model established after spectral preprocessing had a better ability to predict the TVB-N content of crayfish compared with the PLS model. The CNN model based on the WT pretreated spectra of crayfish meat had the highest prediction accuracy for the validation set with correlation coefficients of 0.97 and 0.96, and root mean square errors of 1.26 and 0.93 mg/100 g for the calibration set and validation set, respectively. Moreover, the accuracy, precision, and sensitivity of the NIR method were within reasonable limits, and it had good figures of merit. According to the requirements of fast operation, accurate results, and low damage in practice, the WT-CNN-crayfish meat model was determined as the optimal model for predicting the TVB-N content in frozen crayfish. These results suggested that the WT-CNN-crayfish meat model have a great potential for predicting the TVB-N content and rapidly evaluating the freshness of frozen crayfish.https://www.spkx.net.cn/fileup/1002-6630/PDF/2024-45-2-037.pdfnear-infrared spectroscopy; crayfish; total volatile basic nitrogen; rapid detection; convolutional neural network; wavelet transform |
| spellingShingle | ZHAN Ke, CHEN Jiwang, XU Yan, NI Yangfan, LIU Yan, ZOU Shengbi A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy Shipin Kexue near-infrared spectroscopy; crayfish; total volatile basic nitrogen; rapid detection; convolutional neural network; wavelet transform |
| title | A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy |
| title_full | A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy |
| title_fullStr | A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy |
| title_full_unstemmed | A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy |
| title_short | A Rapid Detection Method for Freshness of Frozen Crayfish Based on Near-Infrared Spectroscopy |
| title_sort | rapid detection method for freshness of frozen crayfish based on near infrared spectroscopy |
| topic | near-infrared spectroscopy; crayfish; total volatile basic nitrogen; rapid detection; convolutional neural network; wavelet transform |
| url | https://www.spkx.net.cn/fileup/1002-6630/PDF/2024-45-2-037.pdf |
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