Translating near-infrared spectroscopy from laboratory to commercial slaughterhouse: Existing challenges and solutions

Puneet Mishra*, Ronald Klont, Theo Verkleij, Sjaak Wisse

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)


In recent decades, applications of near-infrared (NIR) spectroscopy for fresh meat and meat products analysis have increased exponentially in the scientific literature. The practical applications of NIR spectroscopy in slaughterhouse conditions are, however, still limited. Reasons for that are several challenges associated with the translation of NIR technology. The challenges range from reaching the best NIR calibration models for predictive analysis for predictive carcass composition analysis to combining NIR information with background information of cattle to support decision making for purposes such as pricing. This study supplies a comprehensive highlight of several existing challenges related to the translation of NIR technology from the research lab to commercial slaughterhouse conditions. The challenges covered were both related to the NIR data analysis of meat measurements, as well as the key challenges in technology transfer. Furthermore, some existing solutions are highlighted concerning each challenge. The major challenges were related to both the data analysis and proper sensor implementation in the slaughterhouse lines. Although several challenges exist, the recent innovations in data analysis techniques and innovations in sensing probe technology would defiantly ease the implementation of NIR technology in practical slaughterhouse conditions. However, all slaughterhouse lines are different and the implementation of NIR technology (from the sensor implementation point of view) for a particular slaughterhouse will be unique. However, data and models between different slaughter lines should play a complementary role.

Original languageEnglish
Article number103918
JournalInfrared Physics and Technology
Publication statusPublished - Dec 2021


  • In-line
  • Meat analysis
  • Model maintenance
  • Non-destructive
  • Quality analysis


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