Testing two NIRs instruments to predict chicken breast meat quality and exploiting machine learning approaches to discriminate among genotypes and presence of myopathies-Reference-Cited by-同舟云学术

Testing two NIRs instruments to predict chicken breast meat quality and exploiting machine learning approaches to discriminate among genotypes and presence of myopathies

Published:2023-02 Issue: Volume:144 Page:109391
ISSN:0956-7135
Container-title:Food Control
language:en
Short-container-title:Food Control

Author:

Serva Lorenzo^ORCID,Marchesini Giorgio,Cullere Marco^ORCID,Ricci Rebecca,Dalle Zotte Antonella

Publisher

Elsevier BV

Subject

Food Science,Biotechnology

Reference54 articles.

1. Characterization of different strains of broiler chicken by carcass measurements, chemical and physical parameters and NIRS on breast muscle;Abeni;Meat Science,2001

2. Non-destructive estimation of Mandarin maturity status through portable VIS-NIR spectrophotometer;Antonucci;Food and Bioprocess Technology,2011

3. Prediction of chicken quality attributes by near infrared spectroscopy;Barbin;Food Chemistry,2015

4. Standard normal variate transformation and de-trending of near-infrared diffuse reflectance spectra;Barnes;Applied Spectroscopy,1989

5. Near-infrared reflectance spectroscopy as a method to predict chemical composition of breast meat and discriminate between different n-3 feeding sources;Berzaghi;Poultry Science,2005

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