Bacterial Pattern Identification in Near-Infrared Spectrum

Krepelka, Pavel; Pérez‐Rodríguez, Fernando; Bartušek, K.

doi:10.5604/20830157.1121369

Cited by 3 publications

(3 citation statements)

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“…These bands in the NIR spectrum displayed functional group oscillations corresponding to the lipids and proteins contained in the cell membranes of bacteria. It was found that different bacteria exhibited NIR absorption bands at the same location [38]. Accordingly, the A. aceti bacteria used in this study could have a similar NIR spectrum pattern to that found in their report.…”

Section: Comparison Of Pls and Scars-pls Modelssupporting

confidence: 81%

“…The error in the prediction of the TSS and tannic acid contents in the fermented vinegar samples might have occurred due to A. aceti bacteria under fermentation conditions. Krepelka et al [38] investigated the bacteria pattern in the NIR spectrum and reported the NIR spectra of bacteria cells on a glass filter without water absorption effects. According to their results, the NIR spectrum of pure bacteria revealed the vibration of NH (1st overtone) at 7150-6250 cm −1 , vibrations of the CH and CONH groups (1st overtone) at 5910-5500 cm −1 , and the vibration of the functional groups related to lipids and proteins at 5250-4000 cm −1 [28,38].…”

Section: Comparison Of Pls and Scars-pls Modelsmentioning

confidence: 99%

“…Krepelka et al [38] investigated the bacteria pattern in the NIR spectrum and reported the NIR spectra of bacteria cells on a glass filter without water absorption effects. According to their results, the NIR spectrum of pure bacteria revealed the vibration of NH (1st overtone) at 7150-6250 cm −1 , vibrations of the CH and CONH groups (1st overtone) at 5910-5500 cm −1 , and the vibration of the functional groups related to lipids and proteins at 5250-4000 cm −1 [28,38]. These bands in the NIR spectrum displayed functional group oscillations corresponding to the lipids and proteins contained in the cell membranes of bacteria.…”

Section: Comparison Of Pls and Scars-pls Modelsmentioning

confidence: 99%

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Assessing Fermentation Broth Quality of Pineapple Vinegar Production with a Near-Infrared Fiber-Optic Probe Coupled with Stability Competitive Adaptive Reweighted Sampling

Kasemsumran,

Boondaeng,

Jungtheerapanich

et al. 2023

Molecules

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In this study, the performance of a near-infrared (NIR) fiber-optic probe coupled with stability competitive adaptive reweighted sampling (SCARS) was investigated for the analysis of acetic acid, ethanol, total soluble solids, caffeic acid, gallic acid, and tannic acid in the broth of pineapple vinegar during fermentation. The NIR spectra of the broth samples in the region of 11,536–3956 cm−1 were collected during vinegar fermentation promoted by Acetobacter aceti. This continuous biological process led to changes in the concentrations of all analytes studied. SCARS provided optimized and stabilized NIR spectral variables for the construction of a partial least squares (PLS) model for each analyte using a small number of optimal variables (under 88 variables). The SCARS-PLS model outperformed the conventional PLS model, and achieved excellent accuracy in accordance with ISO 12099:2017 for the four prediction models of acetic acid, ethanol, caffeic acid, and gallic acid, with root-mean-square error of prediction values of 0.137%, 0.178%, 0.637 μg/mL and 0.640 μg/mL, respectively. In contrast, only an acetic acid content prediction model constructed via the conventional PLS method and using the whole spectral region (949 variables) could pass with acceptable accuracy. These results indicate that the NIR optical probe coupled with SCARS is an appropriate method for the continuous monitoring of multianalytes during vinegar fermentation, particularly acetic acid and ethanol contents, which are indicators of the finished fermentation of pineapple vinegar.

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Section: Comparison Of Pls and Scars-pls Modelssupporting

confidence: 81%