Dataset Information

On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.

ABSTRACT: Biosurfactants are a series of organic compounds that are composed of two parts, hydrophobic and hydrophilic, and since they have properties such as less toxicity and biodegradation, they are widely used in the food industry. Important applications include healthy products, oil recycling, and biological refining. In this research, to calculate the curves of rhamnolipid adsorption compared to Amberlite XAD-2, the least-squares vector machine algorithm has been used. Then, the obtained model is formed by 204 adsorption data points. Various graphical and statistical approaches are applied to ensure the correctness of the model output. The findings of this study are compared with studies that have used artificial neural network (ANN) and data group management method (GMDH) models. The model used in this study has a lower percentage of absolute mean deviation than ANN and GMDH models, which is estimated to be 1.71%.The least-squares support vector machine (LSSVM) is very valuable for investigating the breakthrough curve of rhamnolipid, and it can also be used to help chemists working on biosurfactants. Moreover, our graphical interface program can assist everyone to determine easily the curves of rhamnolipid adsorption on Amberlite XAD-2.

SUBMITTER: Chen F

PROVIDER: S-EPMC8096566 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.

Chen Fengqin F Huang Jinbo J Wu Xianjun X Wu Xiaoli X Arabmarkadeh Arash A

BioMed research international 20210426

Biosurfactants are a series of organic compounds that are composed of two parts, hydrophobic and hydrophilic, and since they have properties such as less toxicity and biodegradation, they are widely used in the food industry. Important applications include healthy products, oil recycling, and biological refining. In this research, to calculate the curves of rhamnolipid adsorption compared to Amberlite XAD-2, the least-squares vector machine algorithm has been used. Then, the obtained model is fo ...[more]

PMID: 33996999

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Project description:Phytopathogens pose severe implications in the quantity and quality of food production by instigating several diseases. Biocontrol strategies comprising the application of biomaterials have offered endless opportunities for sustainable agriculture. We explored multifarious potentials of rhamnolipid-BS (RH-BS: commercial), fungal chitosan (FCH), and FCH-derived nanoparticles (FCHNPs). The high-quality FCH was extracted from Cunninghamella echinulata NCIM 691 followed by the synthesis of FCHNPs. Both, FCH and FCHNPs were characterized by UV-visible spectroscopy, DLS, zeta potential, FTIR, SEM, and Nanoparticle Tracking Analysis (NTA). The commercial chitosan (CH) and synthesized chitosan nanoparticles (CHNPs) were used along with test compounds (FCH and FCHNPs). SEM analysis revealed the spherical shape of the nanomaterials (CHNPs and FCHNPs). NTA provided high-resolution visual validation of particle size distribution for CHNPs (256.33 ± 18.80 nm) and FCHNPs (144.33 ± 10.20 nm). The antibacterial and antifungal assays conducted for RH-BS, FCH, and FCHNPs were supportive to propose their efficacies against phytopathogens. The lower MIC of RH-BS (256 μg/ml) was observed than that of FCH and FCHNPs (>1,024 μg/ml) against Xanthomonas campestris NCIM 5028, whereas a combination study of RH-BS with FCHNPs showed a reduction in MIC up to 128 and 4 μg/ml, respectively, indicating their synergistic activity. The other combination of RH-BS with FCH resulted in an additive effect reducing MIC up to 128 and 256 μg/ml, respectively. Microdilution plate assay conducted for three test compounds demonstrated inhibition of fungi, FI: Fusarium moniliforme ITCC 191, FII: Fusarium moniliforme ITCC 4432, and FIII: Fusarium graminearum ITCC 5334 (at 0.015% and 0.020% concentration). Furthermore, potency of test compounds performed through the in vitro model (poisoned food technique) displayed dose-dependent (0.005%, 0.010%, 0.015%, and 0.020% w/v) antifungal activity. Moreover, RH-BS and FCHNPs inhibited spore germination (61-90%) of the same fungi. Our efforts toward utilizing the combination of RH-BS with FCHNPs are significant to develop eco-friendly, low cytotoxic formulations in future.

Dataset Information

On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.

Publications

On the Evaluation of Rhamnolipid Biosurfactant Adsorption Performance on Amberlite XAD-2 Using Machine Learning Techniques.

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