Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy
Monitoring and identifying the freshness levels of meat holds significant importance in the field of food safety as it directly relates to human dietary safety. Traditional packaging methods for lamb meat quality assessment present issues such as cumbersome operations and irreversible damage. This r...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-07-01
|
| Series: | Foods |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2304-8158/12/14/2756 |
| _version_ | 1797589298090868736 |
|---|---|
| author | Peilin Jin Yifan Fu Renzhong Niu Qi Zhang Mingyue Zhang Zhigang Li Xiaoshuan Zhang |
| author_facet | Peilin Jin Yifan Fu Renzhong Niu Qi Zhang Mingyue Zhang Zhigang Li Xiaoshuan Zhang |
| author_sort | Peilin Jin |
| collection | DOAJ |
| description | Monitoring and identifying the freshness levels of meat holds significant importance in the field of food safety as it directly relates to human dietary safety. Traditional packaging methods for lamb meat quality assessment present issues such as cumbersome operations and irreversible damage. This research proposes a quality assessment method for modified atmosphere packaging lamb meat using near-infrared spectroscopy and multi-parameter fusion. Fresh lamb meat quality is taken as the research subject, comparing various physicochemical indicators and near-infrared spectroscopic information under different temperatures (4 °C and 10 °C) and different modified atmosphere packaging combinations. Through precision parameter comparison, rebound and TVB-N values are selected as the modeling parameters. Six spectral preprocessing methods (multi-scatter calibration, MSC; standard normal variate transformation, SNV; normalization; Savitzky–Golay smoothing, SG; Savitzky–Golay 1 derivative, SG-1st; and Savitzky–Golay 2 derivative, SG-2nd), and three feature wavelength selection methods (competitive adaptive reweighted sampling, CARS; successive projections algorithm, SPA; and uninformative variable elimination, UVE) are compared. Partial least squares (PLS) and support vector machine (SVM) are used to construct prediction models for chilled fresh lamb meat quality. The results show that when rebound is used as a parameter, the SG-2nd-SPA-PLSR model has the highest accuracy, with a determination coefficient R<sup>2</sup>p of 0.94 for the prediction set. When TVB-N is used as a parameter, the MSC-UVE-SVM model has the highest accuracy, with an R<sup>2</sup>p of 0.95 for the prediction set. In conclusion, the use of near-infrared spectroscopic analysis enables rapid and non-destructive prediction and evaluation of lamb meat freshness, including its textural characteristics and TVB-N content under different modified atmosphere packaging. This study provides a theoretical basis and technical support for further encapsulating the models into portable devices and developing portable near-infrared spectrometers to rapidly determine lamb meat freshness. |
| first_indexed | 2024-03-11T01:04:30Z |
| format | Article |
| id | doaj.art-4e50e3a04191459fab257eb000f65b12 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-11T01:04:30Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-4e50e3a04191459fab257eb000f65b122023-11-18T19:20:58ZengMDPI AGFoods2304-81582023-07-011214275610.3390/foods12142756Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared SpectroscopyPeilin Jin0Yifan Fu1Renzhong Niu2Qi Zhang3Mingyue Zhang4Zhigang Li5Xiaoshuan Zhang6College of Information Science and Technology, Shihezi University, Shihezi 832000, ChinaBeijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information Science and Technology, Shihezi University, Shihezi 832000, ChinaCollege of Information Science and Technology, Shihezi University, Shihezi 832000, ChinaCollege of Information Science and Technology, Shihezi University, Shihezi 832000, ChinaCollege of Information Science and Technology, Shihezi University, Shihezi 832000, ChinaBeijing Laboratory of Food Quality and Safety, College of Engineering, China Agricultural University, Beijing 100083, ChinaMonitoring and identifying the freshness levels of meat holds significant importance in the field of food safety as it directly relates to human dietary safety. Traditional packaging methods for lamb meat quality assessment present issues such as cumbersome operations and irreversible damage. This research proposes a quality assessment method for modified atmosphere packaging lamb meat using near-infrared spectroscopy and multi-parameter fusion. Fresh lamb meat quality is taken as the research subject, comparing various physicochemical indicators and near-infrared spectroscopic information under different temperatures (4 °C and 10 °C) and different modified atmosphere packaging combinations. Through precision parameter comparison, rebound and TVB-N values are selected as the modeling parameters. Six spectral preprocessing methods (multi-scatter calibration, MSC; standard normal variate transformation, SNV; normalization; Savitzky–Golay smoothing, SG; Savitzky–Golay 1 derivative, SG-1st; and Savitzky–Golay 2 derivative, SG-2nd), and three feature wavelength selection methods (competitive adaptive reweighted sampling, CARS; successive projections algorithm, SPA; and uninformative variable elimination, UVE) are compared. Partial least squares (PLS) and support vector machine (SVM) are used to construct prediction models for chilled fresh lamb meat quality. The results show that when rebound is used as a parameter, the SG-2nd-SPA-PLSR model has the highest accuracy, with a determination coefficient R<sup>2</sup>p of 0.94 for the prediction set. When TVB-N is used as a parameter, the MSC-UVE-SVM model has the highest accuracy, with an R<sup>2</sup>p of 0.95 for the prediction set. In conclusion, the use of near-infrared spectroscopic analysis enables rapid and non-destructive prediction and evaluation of lamb meat freshness, including its textural characteristics and TVB-N content under different modified atmosphere packaging. This study provides a theoretical basis and technical support for further encapsulating the models into portable devices and developing portable near-infrared spectrometers to rapidly determine lamb meat freshness.https://www.mdpi.com/2304-8158/12/14/2756near-infrared spectroscopymutton quality detectiontexture parametersmodified atmosphere packaged |
| spellingShingle | Peilin Jin Yifan Fu Renzhong Niu Qi Zhang Mingyue Zhang Zhigang Li Xiaoshuan Zhang Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy Foods near-infrared spectroscopy mutton quality detection texture parameters modified atmosphere packaged |
| title | Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy |
| title_full | Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy |
| title_fullStr | Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy |
| title_full_unstemmed | Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy |
| title_short | Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy |
| title_sort | non destructive detection of the freshness of air modified mutton based on near infrared spectroscopy |
| topic | near-infrared spectroscopy mutton quality detection texture parameters modified atmosphere packaged |
| url | https://www.mdpi.com/2304-8158/12/14/2756 |
| work_keys_str_mv | AT peilinjin nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT yifanfu nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT renzhongniu nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT qizhang nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT mingyuezhang nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT zhigangli nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy AT xiaoshuanzhang nondestructivedetectionofthefreshnessofairmodifiedmuttonbasedonnearinfraredspectroscopy |