Three dimensional excitation-emission matrix fluorescence spectroscopy of typical Japanese soil powders

Nakaya, Yuki; Nakashima, Satoru; Moriizumi, Mihoko; Oguchi, Masahiro; Kashiwagi, Shinsuke; Naka, N.

doi:10.1016/j.saa.2020.118188

Cited by 19 publications

(5 citation statements)

References 22 publications

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“…The surface chromaticity would induce light absorption and light scattering and thus compromise the fluorescence detection. Kubelka–Munk (K–M) model has been used to correct the absorption and scattering to obtain the true fluorescence spectra, but it is also reported that the K–M correction was insufficient to compensate for the interference above . Nakaya et al developed an empirical calibration method based on K–M correction through which a good calibration curve could be obtained .…”

Section: Methodsmentioning

confidence: 99%

“…Kubelka−Munk (K−M) model has been used to correct the absorption and scattering to obtain the true fluorescence spectra, but it is also reported that the K−M correction was insufficient to compensate for the interference above. 37 Nakaya et al developed an empirical calibration method based on K−M correction through which a good calibration curve could be obtained. 27 The FF-EEM data were corrected with the Nakaya's method in this work, and the correction procedure is detailed in SI.…”

Section: ■ Introductionmentioning

confidence: 99%

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Evaluation of Front-Face Fluorescence for Assessing Cyanobacteria Fouling in Ultrafiltration

Yu,

Huang,

Zhong

et al. 2023

Environ. Sci. Technol.

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Cyanobacteria fouling in ultrafiltration (UF) drinking water treatment poses a significant threat to the stability and sustainability of the process. Both phycocyanin found in cyanobacteria and the polymer membrane exhibit strong fluorescence, which could be readily detected using front-face excitation–emission matrix (FF-EEM) spectroscopy. In this study, FF-EEM was employed for the nondestructive and in situ characterization of algae fouling evolution in UF, while also analyzing fouling mechanisms and reversibility. The results indicated that phycocyanin fluorescence on the membrane surface showed a linear correlation with the specific algal cell count on the membrane surface before reaching saturation. As fouling progressed, membrane fluorescence decreased, which was associated with the extent of the surface coverage on the membrane. The plateau in membrane fluorescence indicated full coverage, coinciding with the cake filtration mechanism, cake compression, and deterioration of fouling reversibility. These findings highlight the promise of FF-EEM as a valuable tool for monitoring and evaluating fouling of cyanobacteria in UF systems.

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Section: Methodsmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

Evaluation of Front-Face Fluorescence for Assessing Cyanobacteria Fouling in Ultrafiltration

Yu,

Huang,

Zhong

et al. 2023

Environ. Sci. Technol.

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“…These differences in the emission spectrum help to rationalize the chlorophyll indices (SFR_G and SFR_R) and anthocyanin indices (ANTH_RG and ANTH_RB) for plants that are generated by the Multiplex3 sensor. The soil fluorescence excitation-emission matrix also demonstrates such differential sensitivities at the FRF and RF emission spectrum [27]. Among soil components, organic matter components such as humic and fulvic acids have fluorescent properties [28,29].…”

Section: Introductionmentioning

confidence: 97%

Assessment of Soil Fertility Using Induced Fluorescence and Machine Learning

Longchamps

Mandal

Khosla

2022

Sensors

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Techniques such as proximal soil sampling are investigated to increase the sampling density and hence the resolution at which nutrient prescription maps are developed. With the advent of a commercial mobile fluorescence sensor, this study assessed the potential of fluorescence to estimate soil chemical properties and fertilizer recommendations. This experiment was conducted over two years at nine sites on 168 soil samples and used random forest regression to estimate soil properties, fertility classes, and recommended N rates for maize production based on induced fluorescence of air-dried soil samples. Results showed that important soil properties such as soil organic matter, pH, and CEC can be estimated with a correlation of 0.74, 0.75, and 0.75, respectively. When attempting to predict fertility classes, this approach yielded an overall accuracy of 0.54, 0.78, and 0.69 for NO3-N, SOM, and Zn, respectively. The N rate recommendation for maize can be directly estimated by fluorescence readings of the soil with an overall accuracy of 0.78. These results suggest that induced fluorescence is a viable approach for assessing soil fertility. More research is required to transpose these laboratory-acquired soil analysis results to in situ readings successfully.

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“…Excitation-emission matrix (EEM) uorescence spectroscopy can provide complete uorescence information of PAHs in complex environment by covering different excitation and emission wavelengths. 29,30 EEM uorescence spectroscopy also has some shortcomings, so it is difficult to extract characteristic uorescence information from the peaks with serious overlap among PAHs. Thus, it is impossible to quantitatively analyze them by a single factor.…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

Tang

et al. 2023

RSC Adv.

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Three dimensional excitation-emission matrix fluorescence spectroscopy of typical Japanese soil powders

Cited by 19 publications

References 22 publications

Evaluation of Front-Face Fluorescence for Assessing Cyanobacteria Fouling in Ultrafiltration

Evaluation of Front-Face Fluorescence for Assessing Cyanobacteria Fouling in Ultrafiltration

Assessment of Soil Fertility Using Induced Fluorescence and Machine Learning

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model

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