Development of bio-based adhesive using tannery shaving dust: Process optimization using statistical and artificial intelligence techniques

Gebremariam, Ejigayehu  Chakiso; Malede, Yohanes Chekol; Prabhu, S.; Varadharajan, Venkatramanan; Manivannan, S.; Jayakumar, Mani; Baskar, G.

doi:10.1016/j.biteb.2023.101413

Cited by 4 publications

References 25 publications

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A comparative study on process optimization of betalain pigment extraction from Beta vulgaris subsp. vulgaris: RSM, ANN, and hybrid RSM-GA methods

Prabhu,

Varadharajan,

Mohanasundaram

et al. 2023

Biomass Conv. Bioref.

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Beta vulgaris subsp. vulgaris (red Swiss chard) leaf stalks offer a rich source of betalains, natural pigments with promising applications in the food industry. This study employed response surface methodology (RSM) in conjunction with a 3-level Box-Behnken design to optimize independent extraction variables, including temperature, extraction time, and solid-to-liquid ratio, for maximizing betalains extraction from red Swiss chard. Betacyanins and betaxanthins, the key natural pigments, were targeted as response variables. Statistical analysis revealed the optimal conditions for extraction: 21.14 minutes of extraction time, 52.98°C temperature, and a solid-toliquid ratio of 21.61 mg/mL, resulting in the maximum extraction of betacyanins (15.53 mg/100g) and betaxanthins (9.5 mg/100g). To enhance prediction accuracy, an artificial neural network (ANN) model was employed, outperforming RSM predictions. Moreover, incorporating a genetic algorithm (GA) into the RSM regression equation predicted even higher betalain contents, with betacyanins reaching 16.53 mg/100g and betaxanthins 10.52 mg/100g. Confirmation experiments conducted under RSM-GA predicted optimum conditions demonstrated mean betacyanin and betaxanthin contents of 16.54 mg/100g and 10.49 mg/100g, respectively. The superior predictive capabilities of the ANN model and the synergistic integration of GA with RSM highlight innovative approaches for enhancing extraction efficiency. Furthermore, the characterized extract exhibit attributes such as aggregated morphology, amorphous nature and high thermal stability.

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A comparative study on process optimization of betalain pigment extraction from Beta vulgaris subsp. vulgaris: RSM, ANN, and hybrid RSM-GA methods

Prabhu,

Varadharajan,

Mohanasundaram

et al. 2023

Biomass Conv. Bioref.

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Development on bio-based concrete crack healing in soil exposures: isolation, identification, and characterization of potential bacteria and evaluation of crack healing performance

Anbazhagan,

Arunachalam,

Dharmalingam

et al. 2023

Biomass Conv. Bioref.

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Adsorptive removal of Cu(II) ions from aqueous solution using Teff (Eragrostis tef) hay based magnetized biocarbon: RSM-GA, ANN based optimization and kinetics aspects

Sundramurthy,

Varadharajan,

Wilson

et al. 2024

Zeitschrift Für Physikalische Chemie

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Teff (Eragrostis tef) is known as a staple grain crop which grown as edible seeds, remarkably in Ethiopia. However, after removal of its seeds, the hay obtained from this crop, are considered as agro-waste. Such a lignocellulosic agro-waste can be potentially exploited to prepare activated carbon to treat the harmful industrial effluents for detoxification. In this study, Teff hay (TH) was used as a precursor for preparing the activated carbon. The using H2SO4, chemical activation was carried out followed by carbonaceous process was undertaken to prepared activated carbon (AC) by pyrolysis. The prepared AC was modified as magnetized AC and characterized by various characterization methods. Further, as a bio-absorbent, its potency for adsorptive removal of Cu(II) ions was ascertained. Notably, the most studied and important process factors for adsorption, such as, initial concentration of metal ion, adsorbent dosage, pH, and contact time were subjected to optimization using response surface method (RSM). Further, to ensure the statistical optimization of aforementioned factors, the non-statistical techniques, genetic algorithm (GA) and artificial neural network (ANN) tools have been executed. In addition, the use of prepared Teff-hay based magnetized AC for the removal of Cu(II) by adsorption process was evaluated through different isotherms and kinetic approaches.

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Development of bio-based adhesive using tannery shaving dust: Process optimization using statistical and artificial intelligence techniques

Cited by 4 publications

References 25 publications

A comparative study on process optimization of betalain pigment extraction from Beta vulgaris subsp. vulgaris: RSM, ANN, and hybrid RSM-GA methods

A comparative study on process optimization of betalain pigment extraction from Beta vulgaris subsp. vulgaris: RSM, ANN, and hybrid RSM-GA methods

Development on bio-based concrete crack healing in soil exposures: isolation, identification, and characterization of potential bacteria and evaluation of crack healing performance

Adsorptive removal of Cu(II) ions from aqueous solution using Teff (Eragrostis tef) hay based magnetized biocarbon: RSM-GA, ANN based optimization and kinetics aspects

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