Non-destructive Near Infrared Spectroscopy for the labelling of frozen Iberian pork loins

被引:36
作者
Caceres-Nevado, J. M. [1 ]
Garrido-Varo, A. [1 ]
De Pedro-Sanz, E. [1 ]
Tejerina-Barrado, D. [2 ]
Perez-Marin, D. C. [1 ]
机构
[1] Univ Cordoba, Fac Agr & Forestry Engn, Campus Rabanales N-4,Km 396, Cordoba 14014, Spain
[2] Junta Extremadura, Ctr Invest Cient & Tecnol Extremadura CICYTEX La, Meat Qual Area, Badajoz, Spain
关键词
Iberian pig loin; Fresh meat authentication; Mislabelling; In situ Near Infrared analysis; PLS-DA discriminant analysis; VARIABLE SELECTION; REFLECTANCE SPECTROSCOPY; BREAST MEAT; THAWED MEAT; FRESH; DIFFERENTIATION; QUALITY; DISCRIMINATION; IDENTIFICATION; WATER;
D O I
10.1016/j.meatsci.2021.108440
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Iberian pigs fed on acorns and pasture were slaughtered from January until March of 2018 and 2019. The meat from those Iberian pigs is a seasonal food that only can be found fresh, at the marketplace, during a limit period of the year. Selling frozen-thawed meat is a legal practice, but consumers must be informed about it on the product label. However, to declare as fresh meat, meat previously frozen, is one of the most frequent meat frauds. The present study compares the performance of two rather different Near Infrared Spectroscopy instruments, based on Fourier Transform and Linear Variable Filter technologies, for the in-situ detection of fresh and frozen-thawed acorns-fed Iberian pig loins using Partial Least Discriminant Analysis (PLS-DA). The performance of the models developed for both instruments offered a very high discriminant ability. Furthermore, the models showed consistent results and interpretation when were evaluated with several scalars and graphical methods.
引用
收藏
页数:11
相关论文
共 50 条
[41]   Qualitative classification of Dendrobium huoshanense (Feng dou) using fast non-destructive hand-held near infrared spectroscopy [J].
Wang, Fang ;
Jia, Bin ;
Dai, Jun ;
Song, Xiangwen ;
Li, Xiaoli ;
Gao, Haidi ;
Yan, Hui ;
Han, Bangxing .
JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2022, 30 (03) :147-153
[42]   Rapid and non-destructive prediction of mango quality attributes using Fourier transform near infrared spectroscopy and chemometrics [J].
Munawar A.A. ;
von Hörsten D. ;
Wegener J.K. ;
Pawelzik E. ;
Mörlein D. .
Engineering in Agriculture, Environment and Food, 2016, 9 (03) :208-215
[43]   Non-destructive Identification of the geographical origin of red jujube by near-infrared spectroscopy and fuzzy clustering methods [J].
Hu, Caiping ;
Xu, Hongjia ;
Fu, Zhaoming ;
Wu, Bin ;
Zhang, Rui ;
Zhi, Chenhong .
INTERNATIONAL JOURNAL OF FOOD PROPERTIES, 2023, 26 (02) :3275-3290
[44]   Non-destructive prediction of soluble solids and dry matter concentrations in apples using near-infrared spectroscopy [J].
Zhang, Y. ;
Nock, J. F. ;
Al Shoffe, Y. ;
Watkins, C. B. .
XXX INTERNATIONAL HORTICULTURAL CONGRESS, IHC 2018-INTERNATIONAL SYMPOSIUM ON STRATEGIES AND TECHNOLOGIES TO MAINTAIN QUALITY AND REDUCE POSTHARVEST LOSSES, 2020, 1275 :341-347
[45]   Non-destructive Detection of the Freshness of Garlic Powder Using Near-infrared (NIR) Spectroscopy and Chemometrics Techniques [J].
Mohammadigol, Reza ;
Shahhoseini, Reza .
JOURNAL OF MEDICINAL PLANTS AND BY-PRODUCTS-JMPB, 2025, 14 (01) :87-92
[46]   Robustness of near infrared spectroscopy based spectral features for non-destructive bitter pit detection in honeycrisp apples [J].
Kafle, Gopi Krishna ;
Khot, Lav R. ;
Jarolmasjed, Sanaz ;
Si Yongsheng ;
Lewis, Karen .
POSTHARVEST BIOLOGY AND TECHNOLOGY, 2016, 120 :188-192
[47]   Study on non-destructive evaluation methods for defect pods for green soybean processing by near-infrared spectroscopy [J].
Sirisomboon, Panmanas ;
Hashimoto, Yuki ;
Tanaka, Munehiro .
JOURNAL OF FOOD ENGINEERING, 2009, 93 (04) :502-512
[48]   A Rapid, Non-Destructive Method for Screening Prochloraz-Containing Water Using Near-Infrared Spectroscopy [J].
Zhang, Yan ;
Xiang, Bingren ;
Xu, Jianping .
ASIAN JOURNAL OF CHEMISTRY, 2014, 26 (10) :3085-3088
[49]   Non-Destructive Detection of Internal Mold Infection in Sweet Tamarind Using Short Wavelength Near Infrared Spectroscopy [J].
Teerachaichayut, S. ;
Suktanarak, S. ;
Kasemsumram, S. .
II INTERNATIONAL SYMPOSIUM ON DISCOVERY AND DEVELOPMENT OF INNOVATIVE STRATEGIES FOR POSTHARVEST DISEASE MANAGEMENT, 2014, 1053 :113-115
[50]   Comparative Analysis of Non-Destructive Prediction Model of Soluble Solids Content for Malus micromalus Makino Based on Near-Infrared Spectroscopy [J].
Gao, Qiang ;
Wang, Meili ;
Guo, Yangyang ;
Zhao, Xiaoqiang ;
He, Dongjian .
IEEE ACCESS, 2019, 7 :128064-128075