Literature DB >> 22449286

An on-line near-infrared (NIR) transmission method for determining depth profiles of fatty acid composition and iodine value in porcine adipose fat tissue.

Klavs Martin Sørensen1, Henrik Petersen, Søren Balling Engelsen.   

Abstract

The present work describes a measurement method using spatially resolved near-infrared (NIR) spectroscopy to determine porcine carcass fat quality as a function of the distance to the skin by estimating its iodine value (IV). The new method is capable of performing on-line carcass grading at full production speed (approximately 1000 carcasses per hour). The method is demonstrated in an experiment where 35 carcasses were sampled at an abattoir, selected from three feeding groups. The NIR transmission instrument was applied on the loin of each carcass, and a parallel reference sample was removed and processed into 1.8 mm thick disks, representing a depth-of-fat profile from the loin. The disks were analyzed for fatty acid composition using gas chromatography (GC) and for IV. A principal component analysis (PCA) of the obtained GC reference values clearly showed that the feeding regimes can be differentiated. Using interval partial least squares (iPLS) regression, a model was produced that can predict the IV of the fat at a given measured depth with a root mean square error of cross-validation (RMSECV) of 1.44. The results show how the IV varies as a function of feeding regime and as a function of fat depth. The maximum variation found within a single depth profile was 10.1 IV from the skin to the innermost part of the fat layers. In the sample material investigated the average span in IV between the average values of the two porcine backfat layers was 6.4 IV (the maximum difference was 8.6 IV). The new method can provide the abattoir with new chemical information about fat quality and production quality that will open new possibilities of meat/carcass grading and product development.
© 2012 Society for Applied Spectroscopy

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Year:  2012        PMID: 22449286     DOI: 10.1366/11-06396

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


  5 in total

1.  Rapid Prediction of Moisture Content in Intact Green Coffee Beans Using Near Infrared Spectroscopy.

Authors:  Adnan Adnan; Dieter von Hörsten; Elke Pawelzik; And Daniel Mörlein
Journal:  Foods       Date:  2017-05-19

2.  Raman and near Infrared Spectroscopy for Quantification of Fatty Acids in Muscle Tissue-A Salmon Case Study.

Authors:  Nils Kristian Afseth; Katinka Dankel; Petter Vejle Andersen; Gareth Frank Difford; Siri Storteig Horn; Anna Sonesson; Borghild Hillestad; Jens Petter Wold; Erik Tengstrand
Journal:  Foods       Date:  2022-03-26

Review 3.  Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review.

Authors:  Christopher T Kucha; Li Liu; Michael O Ngadi
Journal:  Sensors (Basel)       Date:  2018-01-28       Impact factor: 3.576

4.  Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products.

Authors:  Evgenia D Spyrelli; Agapi I Doulgeraki; Anthoula A Argyri; Chrysoula C Tassou; Efstathios Z Panagou; George-John E Nychas
Journal:  Microorganisms       Date:  2020-04-11

5.  Can In-Line Iodine Value Predictions (NitFomTM) Be Used for Early Classification of Pork Belly Firmness?

Authors:  Stephanie Lam; Bethany Uttaro; Benjamin M Bohrer; Marcio Duarte; Manuel Juárez
Journal:  Foods       Date:  2022-01-06
  5 in total

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