Detection and quantification ofEscherichia coliandPseudomonas aeruginosain cow milk by near-infrared spectroscopy-Reference-Cited by-同舟云学术

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Detection and quantification ofEscherichia coliandPseudomonas aeruginosain cow milk by near-infrared spectroscopy

Published:2015-01-26 Issue:3 Volume:68 Page:357-365
ISSN:1364-727X
Container-title:International Journal of Dairy Technology
language:en
Short-container-title:Int J Dairy Technol

Author:

Cámara-Martos Fernando¹,Lopes Joao Almeida²,Moreno-Rojas Rafael¹,Pérez-Rodríguez Fernando¹³

Affiliation:

1. Departamento de Bromatología y Tecnología de los Alimentos; Universidad de Córdoba; Campus Rabanales, Edif. Darwin-Anexo 14014 Córdoba Spain

2. REQUIMTE; Serviço de Química-Física; Faculdade de Farmacia; Universidade do Porto; Rua Anibal Cunha 164 4099 - 030 Porto Portugal

3. Optimum Quality. Pol. Tecnocordoba; C/Estonia; 1 Nave 79 14014 Córdoba Spain

Publisher

Wiley

Subject

Process Chemistry and Technology,Bioengineering,Food Science

Reference34 articles.

1. Rapid non-destructive detection of spoilage of intact chicken breast muscle using near-infrared and Fourier transform mid-infrared spectroscopy and multivariate statistics;Alesandrakis;Food Bioprocess and Technology,2012

2. Detection and identification of bacteria in an isolated system with near-infrared spectroscopy and multivariate analysis;Alexandrakis;Journal of Agricultural and Food Chemistry,2008

3. Monitoring quality loss of pasteurized skim milk using visible and short wavelength near-infrared spectroscopy and multivariate analysis;Al-Qadiri;Journal of Dairy Science,2008

4. Potentiality of Fourier transform infrared spectroscopy (FTIR) for discrimination and identification of dairy lactic acid bacteria;Amiel;Le Lait,2000

5. Spoilage potentials and antimicrobial resistance of Pseudomonas spp. isolated from cheeses;Arslan;Journal of Dairy Science,2011

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3. Advances in Detection of Microorganisms Using Near-Infrared Spectroscopy;SPECTROSC SPECT ANAL;2022

4. Application of Optical Quality Control Technologies in the Dairy Industry: An Overview;Photonics;2021-12-03

5. Achieving a robust Vis/NIR model for microbial contamination detection of Persian leek by spectral analysis based on genetic, iPLS algorithms and VIP scores;Postharvest Biology and Technology;2021-05

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