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EXTERNAL VALIDATION AND TRANSFERABILITY OF NIRS MODELS DEVELOPED FOR DETECTING AND QUANTIFYING MBM IN INTACT COMPOUND FEEDING STUFFS
Author(s) -
PÉREZ MARÍN D.C.,
GARRIDOVARO A.,
GUERRERO J.E.,
GÓMEZ A.,
SOLDADO A.,
DE LA ROZA B.
Publication year - 2008
Publication title -
journal of food quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.568
H-Index - 43
eISSN - 1745-4557
pISSN - 0146-9428
DOI - 10.1111/j.1745-4557.2007.00186.x
Subject(s) - meat and bone meal , transferability , european union , computer science , food science , biochemical engineering , biology , business , machine learning , fish meal , engineering , logit , fishery , fish <actinopterygii> , economic policy
The ban on the use of animal‐origin by‐products such as meat and bone meal (MBM) in compound feeds was one of the measures implemented in the European Union to stop the spread of bovine spongiform encephalopathy (BSE) and to prevent its reoccurrence. It is now clear that the blanket ban will only be lifted if reliable analytical methods are available that ensure the detection of animal by‐products. Near‐infrared spectroscopy (NIRS) is likely to be the most rapid method for testing feedingstuffs, enabling a substantial increase in the number of samples tested and providing instant detection of adulteration, especially when samples are analyzed in intact form. This study aimed to demonstrate the feasibility of NIRS predictive models for detecting and quantifying MBM in intact compound feedingstuffs, and to demonstrate the transferability of calibration models between two NIRS instruments.PRACTICAL APPLICATIONS This study shows the potential of near infrared spectroscopy (NIRS) as a fast screening method for detecting the adulteration of compound feedingstuffs with animal‐origin meals, useful for the feed industry and the inspection bodies. NIRS could provide the first line of defense of the food chain, allowing a large‐scale analysis and making more costly methods to be used more productively on suspect specimens.

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