Near infrared spectroscopy integrated with chemometrics for rapid detection of E. coli ATCC 25922 and E. coli K12

2010 ◽  
Vol 148 (2) ◽  
pp. 366-370 ◽  
Author(s):  
U. Siripatrawan ◽  
Y. Makino ◽  
Y. Kawagoe ◽  
S. Oshita
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Rapid Detection ◽  
Near Infrared ◽  
E Coli

scholarly journals Near-Infrared Spectroscopy Evaluations for the Differentiation of Carbapenem-Resistant from Susceptible Enterobacteriaceae Strains

Diagnostics ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 736
Author(s):  
Bushra Alharbi ◽  
Maggy Sikulu-Lord ◽  
Anton Lord ◽  
Hosam M. Zowawi ◽  
Ella Trembizki
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Accuracy ◽  
Bacterial Species ◽  
Carbapenem Resistance ◽  
Accurate Identification ◽  
E Coli ◽  
Carbapenem Resistant ◽  
Global Threat

Antimicrobial Resistance (AMR) caused by Carbapenem-Resistant Enterobacteriaceae (CRE) is a global threat. Accurate identification of these bacterial species with associated AMR is critical for their management. While highly accurate methods to detect CRE are available, they are costly, timely and require expert skills, making their application infeasible in low-resource settings. Here, we investigated the potential of Near-Infrared Spectroscopy (NIRS) for a range of applications: (i) the detection and differentiation of isolates of two pathogenic Enterobacteriaceae species, Klebsiella pneumoniae and Escherichia coli, and (ii) the differentiation of carbapenem resistant and susceptible K. pneumoniae. NIRS has successfully differentiated between K. pneumoniae and E. coli isolates with a predictive accuracy of 89.04% (95% CI; 88.7–89.4%). K. pneumoniae isolates harbouring carbapenem-resistance determinants were differentiated from susceptible K. pneumoniae strains with an accuracy of 85% (95% CI; 84.2–86.1%). To our knowledge, this is the largest proof of concept demonstration for the utility and feasibility of NIRS to rapidly differentiate between K. pneumoniae and E. coli as well as carbapenem-resistant K. pneumoniae from susceptible strains.

Shortwave Near-Infrared Spectroscopy for Rapid Detection of Aflatoxin B1 Contamination in Polished Rice

2019 ◽  
Vol 82 (5) ◽  
pp. 796-803
Author(s):  
R. PUTTHANG ◽  
P. SIRISOMBOON ◽  
C. DACHOUPAKAN SIRISOMBOON
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Aflatoxin B1 ◽  
Rapid Detection ◽  
Near Infrared ◽  
Cross Validation ◽  
Polished Rice ◽  
Standard Normal Variate ◽  
Standard Normal ◽  
Rice Samples

ABSTRACT The objective of this research was to apply near-infrared spectroscopy, with a short-wavelength range of 950 to 1,650 nm, for the rapid detection of aflatoxin B1 (AFB1) contamination in polished rice samples. Spectra were obtained by reflection mode for 105 rice samples: 90 samples naturally contaminated with AFB1 and 15 samples artificially contaminated with AFB1. Quantitative calibration models to detect AFB1 were developed using the original and pretreated absorbance spectra in conjunction with partial least squares regression with prediction testing and full cross-validation. The statistical model from the external validation process developed from the treated spectra (standard normal variate and detrending) was most accurate for prediction, with a correlation coefficient (r) of 0.952, a standard error of prediction of 3.362 μg/kg, and a bias of −0.778 μg/kg. The most predictive models according to full cross-validation were developed from the multiplicative scatter correction pretreated spectra (r = 0.967, root mean square error in cross-validation [RMSECV] = 2.689 μg/kg, bias = 0.015 μg/kg) and standard normal variate pretreated spectra (r = 0.966, RMSECV = 2.691 μg/kg, bias = 0.008 μg/kg). A classification-based partial least squares discriminant analysis model of AFB1 contamination classified the samples with 90% accuracy. The results indicate that the near-infrared spectroscopy technique is potentially useful for screening polished rice samples for AFB1 contamination.

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