Multi-Objective Optimization Through Machine Learning Modeling for Production of Xylooligosaccharides from Alkali-Pretreated Corn-Cob Xylan Via Enzymatic Hydrolysis

Khangwal, Ishu; Chhabra, Deepak; Shukla, Pratyoosh

doi:10.1007/s12088-021-00970-2

Cited by 8 publications

(2 citation statements)

References 25 publications

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“…Endo-xylanases from many microbial species are highly effective in converting xylan into XOS with different profiles of chain length. Khangwal et al [120] reported that alkali-pretreated xylan by Thermomyces lanuginosus VAPS-24 endoxylanase gave 3.0 mg XOS/mL reaction mixture. Xylanase obtained from Paecilomyces themophila J18 was able to produce XOS (60% DP 2 and 40% DP 3) from hydrothermal-treated corn cob xylan satisfactorily, achieving 29 g XOS/100 g xylan [58].…”

Section: Xylooligosaccharidesmentioning

confidence: 99%

Functional Oligosaccharides Derived from Fruit-and-Vegetable By-Products and Wastes

Chockchaisawasdee

Stathopoulos

2022

Horticulturae

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Industrial-scale food manufacturing generates high quantity of fruit-and-vegetable solid by-product and waste streams (FVSW) which have become a challenge to the environment post-production. Due to this, proposals for a better use of resources to reduce the environmental burden and to promote a circular economy have been introduced. Reintroducing discarded materials back into the production through the recovery of valuable components or through the conversion into value-added ingredients is one approach attracting strong interest in research. FVSW is rich in lignocellulosic materials which can be reused to produce bioactive ingredients. This review highlights the potential use of FVSW as low-cost raw materials and describes the valorisation of FVSW for the production of functional oligosaccharides. The focus is on the production technologies of the main functional oligosaccharides, namely pectic-oligosaccharides, inulin and fructooligosaccharides, xylooligosaccharides, and isomaltooligosaccharides.

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Section: Xylooligosaccharidesmentioning

confidence: 99%

Functional Oligosaccharides Derived from Fruit-and-Vegetable By-Products and Wastes

Chockchaisawasdee

Stathopoulos

2022

Horticulturae

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“…However, the correlations between predicted and actual values were further validated experimentally, and the results were presented as the reduction in ST and percentage reduction in WPE. The potential of various AHML tools is evident in multiple research sectors for data training, validation and optimization; however, the impact of these tools is not adequately utilized in the context of 3D-SA (Deshwal et al, 2020; Khangwal et al, 2021; Pourmostaghimi et al, 2022). The integration of AHML tools with 3D-SA for optimizing various process parameters will enable the collection of highly précised scans in a time-efficient manner and enhance RP’s reliability for the fabrication of customized utility.…”

Section: Introductionmentioning

confidence: 99%

Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN

Kumar,

Chhabra

2024

AIEDAM

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This study aims to develop a multidisciplinary artificial hybrid machine learning (AHML) approach to reduce the scanning time (ST) of the human wrist and improve the accuracy of 3D scanning for anthropometric data collection. A systematic AHML approach was deployed to scan the human wrist distal end optimally using a portable SENSE 2.0 3D scanner. A central composite design (CCD) matrix was developed for three input variables; light intensity (LI = 12–20 W/m2), capture angle (CA = 10°–50°), and scanning distance (SD = 10–20 inches) for executing the experimental runs. For accuracy evaluation, the wrist perimeter on the distal end was checked using CREO Parametric software for wrist perimeter error (WPE). Various AHML tools were developed using: response surface methodology (RSM), multi-objective genetic algorithm RSM, and multi-objective genetic algorithm neural networking (MOGANN). The optimal process parameters recommended by the hybrid tools were experimentally validated for their prediction accuracy. The MOGANN approach combined with the Bayesian regularization algorithm (trainabr) provided the best mutual combination of optimal ST = 20.072 sec and WPE = 0.375 cm corresponding to LI = 12.001 W/m2, CA = 29.428°, and SD = 18.214 inch, with a significant percentage reduction of 55.83% in WPE. Executing 3D scanning of the human wrist over the optimized process parameters predicted by AHML tools will ensure the availability of precise scans for the rapid prototyping of customized orthotic devices in a reliable manner.

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Production, Characterization and Prebiotic Potential of Xylooligosaccharides Produced from Wheat Bran using Enterobacter hormaechei KS1 Xylanase

Kumari,

Nagar,

Goyal

et al. 2023

Indian J Microbiol

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Multi-Objective Optimization Through Machine Learning Modeling for Production of Xylooligosaccharides from Alkali-Pretreated Corn-Cob Xylan Via Enzymatic Hydrolysis

Cited by 8 publications

References 25 publications

Functional Oligosaccharides Derived from Fruit-and-Vegetable By-Products and Wastes

Functional Oligosaccharides Derived from Fruit-and-Vegetable By-Products and Wastes

Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN

Production, Characterization and Prebiotic Potential of Xylooligosaccharides Produced from Wheat Bran using Enterobacter hormaechei KS1 Xylanase

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