Dissolved organic matter evolution and straw decomposition rate characterization under different water and fertilizer conditions based on three-dimensional fluorescence spectrum and deep learning

Yang, Guang; Pan, Hongwei; Liu, Hongjun; Tong, Wenbin; Shi, Lili; Chen, Huiru

doi:10.1016/j.jenvman.2023.118537

Cited by 14 publications

(4 citation statements)

References 75 publications

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“…However, the recent integration of ML models such as CNNs and SVMs for SOM analysis using EEM data marks a significant step forward. , For example, Yang et al applied AlexNet CNN for 3D-EEM (wavelength 280–550 nm) characteristics of DOM, which is the most active organic matter in soil. This CNN, adapted for DOM spectral data (total 1550 spectra), is trained on 80% of the preprocessed data set with the remaining 20% used for testing.…”

Section: Spectroscopy Techniques For Soil Organic Matter Analysismentioning

confidence: 99%

Advancing Soil Health: Challenges and Opportunities in Integrating Digital Imaging, Spectroscopy, and Machine Learning for Bioindicator Analysis

Wang,

Cheng,

Meftaul

et al. 2024

Anal. Chem.

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Section: Spectroscopy Techniques For Soil Organic Matter Analysismentioning

confidence: 99%

Advancing Soil Health: Challenges and Opportunities in Integrating Digital Imaging, Spectroscopy, and Machine Learning for Bioindicator Analysis

Wang,

Cheng,

Meftaul

et al. 2024

Anal. Chem.

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“…The broad hydroxyl (-OH) absorption peak around 3400 cm ¹ indicates a high content of alcohols and phenolic compounds in the humic. The characteristic carboxyl (-COOH) absorption peak around 2300 cm ¹ indicates the presence of carboxylic acid functional groups in the humic 25,26 . The C = C double bond absorption peak around 1600 cm ¹ re ects the presence of aromatic ring structures.…”

Section: Structural Changes Of Humic Before and After Photodegradationmentioning

confidence: 99%

The Synergistic Effect of Clay Minerals on the Photodegradation of Humic

Bao,

Du,

et al. 2024

Preprint

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The study systematically analyzes the photodegradation processes of humic in the plateau lake Erhai Lake and their interactions with clay minerals. The experiments simulate photodegradation reactions under natural conditions, comparing the changes before and after photodegradation reactions. The reduction in total organic carbon (TOC) and changes in the functional groups of organic matter in the photodegradation products of humic are recorded. Aromatic and aliphatic compounds have a key role in humic photodegradation. The photodegradation rate of humic shows a nonlinear change, and The presence of clay minerals accelerates the photodegradation process of humic. The adsorption effects of clay minerals significantly alter the photochemical behavior of humic. Under the influence of clay minerals, the adsorption of humic by clay minerals increases their contact with photons, thereby enhancing the photodegradation efficiency of humic. The continuous photodegradation reaction continuously reduces the particle size of humic adsorbed on the surface of clay minerals, further increasing the adsorption of humic on the surface of clay minerals, accelerating the entire system.

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“…3D-FS technology has been proven to be an important analysis method with the obvious advantages of high manipulation simplicity, little sample damage, and less sample consumption . 3D-FS has been widely applied in the distribution characterization of dissolved organic matter − and toxic tide algae . As typical polycyclic aromatic compounds with large conjugated systems, asphaltenes are anticipated to produce strong fluorescence with characteristics including (1) aromatic or heterocyclic structures, (2) high conjugation degree of π electrons, and (3) rigid planar structures for molecular vibration reduction.…”

Section: Introductionmentioning

confidence: 99%

Insights into Asphaltene Adsorption on Sandstone Surface by Experiment and Simulation: Performance and Mechanism Investigation

Ma,

Huang,

Wan

et al. 2024

Energy Fuels

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Asphaltene adsorption at rock surfaces has important effects on enhanced oil recovery (EOR) in the petroleum industry. In this work, the adsorption interaction of asphaltene with sandstone rock of albite and quartz is investigated to derive experimental and simulation insights. By macroscopic experimental investigation, the interaction performances were evaluated by thermodynamic models of the Langmuir and Freundlich fittings and kinetic models of pseudo-first-order (PFO) and pseudosecond-order (PSO) fittings. The results indicate monolayer molecular asphaltene adsorption for both albite and quartz, but "fast adsorption−slow desorption" is observed for albite and "slow adsorption−fast desorption" for quartz. Meanwhile, albite shows a larger adsorption capacity and stronger adsorption spontaneity with the results of q m(albite 1#) = 2.58 mg g −1 > q m(quartz 1#) = 1.22 mg g −1 and ΔG albite 1 = −2.40 kJ mol −1 < ΔG quartz 1 = −0.97 J mol −1 . By microscopic molecular dynamic simulation (MDS) simulation, the interaction performances were studied for three asphaltene molecules of archipelago-type, island-type, and resin-type. Albite rock shows much higher system stability than quartz, with a more negative final energy of ΔE albite−quartz = −59 kJ mol −1 , and archipelago asphaltene shows the smallest adsorption equilibrium energy, with E ads(archipelago) = −104 < E ads(island) = −71 < E ads(resin) = −58 kJ mol −1 for albite adsorption and E ads(archipelago) = −45 < E ads(island) = −35 ∼ E ads(resin) = −35 kJ mol −1 for quartz adsorption. The interaction mechanism was illustrated by molecular orientation and force dominance for asphaltene adsorption, which "lie sideways" at low concentrations but "stand upright" at high concentrations. This work provided information on the performance and mechanism of asphaltene adsorption at rock surfaces, which is of great significance in reservoir exploitation and enhanced oil recovery.

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Dissolved organic matter evolution and straw decomposition rate characterization under different water and fertilizer conditions based on three-dimensional fluorescence spectrum and deep learning

Cited by 14 publications

References 75 publications

Advancing Soil Health: Challenges and Opportunities in Integrating Digital Imaging, Spectroscopy, and Machine Learning for Bioindicator Analysis

Advancing Soil Health: Challenges and Opportunities in Integrating Digital Imaging, Spectroscopy, and Machine Learning for Bioindicator Analysis

The Synergistic Effect of Clay Minerals on the Photodegradation of Humic

Insights into Asphaltene Adsorption on Sandstone Surface by Experiment and Simulation: Performance and Mechanism Investigation

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