Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models

Dinesha, B.L.; Hiregoudar, Sharanagouda; Nidoni, Udaykumar; Ramappa, K. T.; Dandekar, A.T.; Ravi, M. V.

doi:10.2166/wst.2021.035

Cited by 14 publications

(7 citation statements)

References 35 publications

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“…6b) depicted the average height and width of the nanoparticles. This study revealed that (Dinesha et al, 2021) [17] . Topography and profile image obtained by AFM for CZnO nano-adsorbent was indicated by the height (Y-axis) and width (X-axis) of the particles.…”

Section: Fig 5: Morphology Analysis Of Silver Nanoparticles Using Sca...mentioning

confidence: 68%

Characterization and antibacterial efficacy of silver nanoparticles extracted from neem (Azadirachta indica) leaf extract

Vijayakumar¹,

Manjunath²,

Hiregoudar³

et al. 2021

Int. J. Chem. Stud.

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Use of silver and silver salts is as old as human civilization but the green synthesis of silver nanoparticles (Ag NPs) has only recently been recognized. AgNPs were synthesized using aqueous extract of neem leaves and silver salt. The synthesized AgNPs were characterized using particle size analyser, UV-visible spectroscopy, XRD, SEM and AFM. The size of AgNPs was found to be within the range of 20-60 nm. The absorbance peak was in the range of 420-450 nm. SEM and AFM analysis showed that, the synthesized AgNPs are spherical in shape and surface roughness is 20.40 nm. Further the XRD analysis confirms the nano crystalline phase of silver with cubic crystal structure nature. The EDS analysis confirmed the presence of silver nanoparticles. AgNPs were specifically used in agriculture and medicine as antibacterial, antifungal and antioxidants. Antibacterial activity of synthesized AgNPs was carried out for both gram positive and gram negative bacteria and compared with standard silver nanoparticles. Hence, AgNPs could be use in the food and agricultural filed for commercial usage.

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Section: Fig 5: Morphology Analysis Of Silver Nanoparticles Using Sca...mentioning

confidence: 68%

Characterization and antibacterial efficacy of silver nanoparticles extracted from neem (Azadirachta indica) leaf extract

Vijayakumar¹,

Manjunath²,

Hiregoudar³

et al. 2021

Int. J. Chem. Stud.

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“…Among the analysed physical parameters of MPIW, TSS, TDS, and turbidity were decreased by 73.38%, 88.36%, and 98.97%, respectively. In addition, the EC of treated samples exhibited a lesser reduction e ciency Thus, the reduction could be attributed to the detachment of coated CZnO nano-adsorbent from the sand surface during the regeneration process (Dinesha et al 2021b). The results may guide the regenerated CSZOCS lter bed to nd a higher potential ability to adsorb BOD and COD in collective regeneration cycles for organic pollutant recovery.…”

Section: Realistic Treatment Of Mpiwmentioning

confidence: 99%

“…Among these methods, chemical coagulation is a widely used method for the treatment of industrial e uent (Ali et al 2018). Nevertheless, this method has some disadvantages, such as large chemical addition, huge sludge generation, not being economically viable, and the development of secondary pollution (Dinesha et al 2021b).…”

Section: Introductionmentioning

confidence: 99%

Characterization and efficiency of chitosan zinc-oxide nano-adsorbent coated sand filter bed for milk processing industry wastewater treatment

Dinesha

Hiregoudar

Nidoni

et al. 2022

Preprint

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Sustainable wastewater management in an industry is required to avoid widespread water scarcity problems. In this study, chitosan zinc oxide nano-adsorbent was synthesised and obtained a particle size of 88.35 ± 2.89 d.nm. Chitosan zinc-oxide nano-adsorbent coated sand filter bed was developed by coating CZnO with sand, and characterised by considering its adsorption properties as well as its surface morphology, crystallinity, and functional groups. Batch adsorption experiments were conducted to optimise the process parameters such as CZnO coating dosage, contact time, pH, and initial concentration of biological oxygen demand and chemical oxygen demand. Adsorbent efficiency was studied in treating simulated and real milk processing industry wastewater. The percent reduction efficiency of organic pollutants was found to increase with the increase in contact time and coating dosage of chitosan-zinc oxide nano-adsorbent. Adsorption was rapid and occurred within 140 min with different coating dosages. The percent reduction of biological oxygen demand and chemical oxygen demand increased with an increase in pH. The optimum solution pH for adsorption of both the pollutants from synthetic solution was 6.0. The equilibrium concentration of synthetic solution reached 200 mg/L and 250 mg/L for both pollutants. Four regeneration cycles could be applied without compromising the adsorption efficiency of the filter bed. The performance of the filter bed was compared with previous studies, and it was found to have excellent adsorption efficiency. Hence, chitosan zinc-oxide nano-adsorbent coated sand could be used as a promising filter bed for the removal of organic load from milk processing industry wastewater.

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“…By building a calibration model between the UV-Vis spectrum data of water and the COD standard values, the corresponding COD concentration in water can be predicted based on water's spectrum. Therefore, the prediction accuracy of the model depends on the pros and cons of the calibration modeling method [6]. In recent years, with the development and breakthrough of statistics, applied mathematics, chemometrics, artificial intelligence and other fields, some new modeling methods have been applied to UV-Vis spectroscopy to measure COD, providing a new idea to measure COD concentrations in water with a complex composition [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy

Pan

Bian

et al. 2021

IEEE Access

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The ultraviolet-visible (UV-Vis) spectroscopy measurement method of Chemical Oxygen Demand (COD) in water is a simple physical method that can measure water without secondary pollution from chemical reagents. To solve the problems of low accuracy and insufficient generalization capability of the COD prediction model, an improved Bagging algorithm is proposed and evaluated in this study. The Improved-Bagging algorithm can reduce model variance and bias concurrently, and improves the accuracy and stability of the traditional Bagging algorithm. Results show that the Improved-Bagging algorithm achieves a better prediction ability on different preprocessed data than the traditional Bagging algorithm. After ensemble empirical mode decomposition based (EEMD-Based) algorithm denoising and stability competitive adaptive reweighted sampling (SCARS) algorithm dimension reduction, Improved-Bagging model achieves the best prediction performance. Its coefficient of determination (R 2 ) on the prediction set reached 0.9317, its root mean square error of prediction (RMSEP) reached 5.39 mg/L, and its variance reached 5.53 mg 2 . Results also show that the Improved-Bagging algorithm can accurately measure the COD concentration in water, which lays the foundation for the wide application of spectroscopy to measure water quality parameters.

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Comparison of chitosan based nano-adsorbents for dairy industry wastewater treatment through response surface methodology and artificial neural network models

Cited by 14 publications

References 35 publications

Characterization and antibacterial efficacy of silver nanoparticles extracted from neem (Azadirachta indica) leaf extract

Characterization and antibacterial efficacy of silver nanoparticles extracted from neem (Azadirachta indica) leaf extract

Characterization and efficiency of chitosan zinc-oxide nano-adsorbent coated sand filter bed for milk processing industry wastewater treatment

An Improved-Bagging Model for Water Chemical Oxygen Demand Measurements Using UV-Vis Spectroscopy

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