Developments and Challenges in Online NIR Spectroscopy for Meat Processing. Issue 6 (11th September 2017)

• Record Type: Journal Article
• Authors: Dixit, Y.; Casado‐Gavalda, Maria P.; Cama‐Moncunill, R.; Cama‐Moncunill, X.; Markiewicz‐Keszycka, Maria; Cullen, P. J.; Sullivan, Carl
• Is Part Of: Comprehensive reviews in food science and food safety. Volume 16:Issue 6(2017)
• Page Start: 1172
• Page End: 1187
• Publication Date: 2017-09-11
• Subjects: chemometrics -- meat -- near‐infrared spectroscopy -- on/inline -- probe; Food -- Research -- Periodicals; Food -- Safety measures -- Periodicals; 664.0072
• DOI: 10.1111/1541-4337.12295
• Languages: English
• ISSNs: 1541-4337

Abstract

Abstract: Meat and meat products are popular foods due to their balanced nutritional nature and their availability in a variety of forms. In recent years, due to an increase in the consumer awareness regarding product quality and authenticity of food, rapid and effective quality control systems have been sought by meat industries. Near‐Infrared (NIR) spectroscopy has been identified as a fast and cost‐effective tool for estimating various meat quality parameters as well as detecting adulteration. This review focusses on the on/inline application of single and multiprobe NIR spectroscopy for the analysis of meat and meat products starting from the year 1996 to 2017. The article gives a brief description about the theory of NIR spectroscopy followed by its application for meat and meat products analysis. A detailed discussion is provided on the various studies regarding applications of NIR spectroscopy and specifically for on/inline monitoring along with their advantages and disadvantages. Additionally, a brief description has been given about the various chemometric techniques utilized in the mentioned studies. Finally, it discusses challenges encountered and future prospects of the technology. It is concluded that, advancements in the fields of NIR spectroscopy and chemometrics have immensely increased the potential of the technology as a reliable on/inline monitoring tool for the meat industry.