Literature DB >> 28534672

A Review of the Principles and Applications of Near-Infrared Spectroscopy to Characterize Meat, Fat, and Meat Products.

Nuria Prieto1, Olga Pawluczyk2, Michael Edward Russell Dugan1, Jennifer Lynn Aalhus1.   

Abstract

Consumer demand for quality and healthfulness has led to a higher need for quality assurance in meat production. This requirement has increased interest in near-infrared (NIR) spectroscopy due to the ability for rapid, environmentally friendly, and noninvasive prediction of meat quality or authentication of added-value meat products. This review includes the principles of NIR spectroscopy, pre-processing methods, and multivariate analyses used for quantitative and qualitative purposes in the meat sector. Recent advances in portable NIR spectrometers that enable new online applications in the meat industry are shown and their performance evaluated. Discrepancies between published studies and potential sources of variability are discussed, and further research is encouraged to face the challenges of using NIRS technology in commercial applications, so that its full potential can be achieved.

Entities:  

Keywords:  Near-infrared spectroscopy; fat; meat; online; portable instruments; quality

Mesh:

Substances:

Year:  2017        PMID: 28534672     DOI: 10.1177/0003702817709299

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  18 in total

1.  Rapid Nondestructive Prediction of Multiple Quality Attributes for Different Commercial Meat Cut Types Using Optical System.

Authors:  Jiangying An; Yanlei Li; Chunzhi Zhang; Dequan Zhang
Journal:  Food Sci Anim Resour       Date:  2022-07-01

2.  Using near-infrared spectroscopy to determine intramuscular fat and fatty acids of beef applying different prediction approaches.

Authors:  Wilson Barragán-Hernández; Liliana Mahecha-Ledesma; William Burgos-Paz; Martha Olivera-Angel; Joaquín Angulo-Arizala
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

3.  Near-Infrared Spectroscopy as a Beef Quality Tool to Predict Consumer Acceptance.

Authors:  Wilson Barragán-Hernández; Liliana Mahecha-Ledesma; Joaquín Angulo-Arizala; Martha Olivera-Angel
Journal:  Foods       Date:  2020-07-24

Review 4.  Critical Review on the Utilization of Handheld and Portable Raman Spectrometry in Meat Science.

Authors:  Anel Beganović; Luzia Maria Hawthorne; Katrin Bach; Christian W Huck
Journal:  Foods       Date:  2019-02-01

5.  Lattice Rayleigh Anomaly Associated Enhancement of NH and CH Stretching Modes on Gold Metasurfaces for Overtone Detection.

Authors:  Daler R Dadadzhanov; Tigran A Vartanyan; Alina Karabchevsky
Journal:  Nanomaterials (Basel)       Date:  2020-06-29       Impact factor: 5.076

6.  Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits.

Authors:  Simone Savoia; Andrea Albera; Alberto Brugiapaglia; Liliana Di Stasio; Alessio Cecchinato; Giovanni Bittante
Journal:  J Anim Sci Biotechnol       Date:  2021-03-12

7.  Phenotypic and genetic variation of ultraviolet-visible-infrared spectral wavelengths of bovine meat.

Authors:  Giovanni Bittante; Simone Savoia; Alessio Cecchinato; Sara Pegolo; Andrea Albera
Journal:  Sci Rep       Date:  2021-07-06       Impact factor: 4.379

8.  Investigations into the Performance of a Novel Pocket-Sized Near-Infrared Spectrometer for Cheese Analysis.

Authors:  Verena Wiedemair; Dominik Langore; Roman Garsleitner; Klaus Dillinger; Christian Huck
Journal:  Molecules       Date:  2019-01-24       Impact factor: 4.411

9.  Food Safety Gaps between Consumers' Expectations and Perceptions: Development and Verification of a Gap-Assessment Tool.

Authors:  Paohui Lin; Hsientang Tsai; Tzuya Ho
Journal:  Int J Environ Res Public Health       Date:  2020-08-31       Impact factor: 3.390

Review 10.  Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems.

Authors:  Tiago Bresolin; João R R Dórea
Journal:  Front Genet       Date:  2020-08-20       Impact factor: 4.599

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.