Non-Destructive Detection of the Freshness of Air-Modified Mutton Based on Near-Infrared Spectroscopy

被引:25
|
作者
Jin, Peilin [1 ]
Fu, Yifan [2 ]
Niu, Renzhong [1 ]
Zhang, Qi [1 ]
Zhang, Mingyue [1 ]
Li, Zhigang [1 ]
Zhang, Xiaoshuan [2 ]
机构
[1] Shihezi Univ, Coll Informat Sci & Technol, Shihezi 832000, Peoples R China
[2] China Agr Univ, Coll Engn, Beijing Lab Food Qual & Safety, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
near-infrared spectroscopy; mutton quality detection; texture parameters; modified atmosphere packaged; TVB-N CONTENT; PORK MEAT; CALIBRATION; PREDICTION; SELECTION; QUALITY; BEEF; ATMOSPHERES;
D O I
10.3390/foods12142756
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
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 & DEG;C and 10 & DEG;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(2)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(2)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.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Research on the Factors Influencing the Non-Destructive Detection of Potatoes by Near-Infrared Spectroscopy
    Han Min-jie
    Wang Xiang-you
    Xu Ying-chao
    Cui Ying-jun
    Lu Dan-yang
    [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43 (01) : 37 - 42
  • [2] Progress in Non-destructive Citrus Quality Detection Using Near-infrared Spectroscopy
    Zhang, Xinxin
    Li, Pao
    Yu, Mei
    Jiang, Liwen
    Liu, Xia
    Shan, Yang
    [J]. Shipin Kexue/Food Science, 2022, 43 (01): : 260 - 268
  • [3] Non-destructive test for geomembranes by visible near-infrared spectroscopy
    Komiya, T.
    Nakayama, H.
    Shimaoka, T.
    Inoue, K.
    [J]. GEOSYNTHETICS, VOLS 1-4, 2006, : 373 - +
  • [4] Study on Non-Destructive Detection Method for Egg Freshness Based on LLE-SVR and Visible/Near-Infrared Spectrum
    Duan Yu-fei
    Wang Qiao-hua
    Ma Mei-hu
    Lu Xi
    Wang Cai-yun
    [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36 (04) : 981 - 985
  • [5] Non-destructive detection of pesticide residues in cucumber using visible/near-infrared spectroscopy
    Jamshidi, Bahareh
    Mohajerani, Ezeddin
    Jamshidi, Jamshid
    Minaei, Saeid
    Sharifi, Ahmad
    [J]. FOOD ADDITIVES AND CONTAMINANTS PART A-CHEMISTRY ANALYSIS CONTROL EXPOSURE & RISK ASSESSMENT, 2015, 32 (06): : 857 - 863
  • [6] Rapid Non-Destructive Detection Method for Black Tea With Exogenous Sucrose Based on Near-Infrared Spectroscopy
    Luo Zheng-fei
    Gong Zheng-li
    Yang Jian
    Yang Chong-shan
    Dong Chun-wang
    [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43 (08) : 2649 - 2656
  • [7] Evaluation of Different Models for Non-Destructive Detection of Tomato Pesticide Residues Based on Near-Infrared Spectroscopy
    Nazarloo, Araz Soltani
    Sharabiani, Vali Rasooli
    Gilandeh, Yousef Abbaspour
    Taghinezhad, Ebrahim
    Szymanek, Mariusz
    [J]. SENSORS, 2021, 21 (09)
  • [8] Non-destructive detection of seed cotton moisture content based on Fourier transform near-infrared spectroscopy
    Guo, Junxian
    Zhang, Zhenzhen
    Han, Jing
    Zhou, Jun
    Shi, Yong
    Jiang, Yanwu
    Yang, Xiao
    [J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2023, 39 (21): : 152 - 160
  • [9] Non-destructive detection of mutton freshness using anthocyanin nanofiber smart label
    Sun, Wuliang
    Li, Wenbo
    Jin, Zhimin
    Jin, Ye
    Sun, Wenxiu
    [J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2021, 37 (04): : 24 - 30
  • [10] Non-Destructive Measurement of the Egg Freshness by Near Infrared Spectrometry
    Kim, Sang Ho
    Lee, Sang Jin
    Lee, Duk Su
    Cho, Won Bo
    Lee, Seong Hun
    Borden, Stuart
    Woo, Young A.
    Kim, Hyo Jin
    [J]. JOURNAL OF THE KOREAN CHEMICAL SOCIETY-DAEHAN HWAHAK HOE JEE, 2005, 49 (06): : 531 - 536