Multiobjective decision making strategy for selective albumin extraction from a rapeseed cold-pressed meal based on Rough Set approach

Beaubier, Sophie; Defaix, Claire; Albe-Slabi, Sara; Aymes, Arnaud; Galet, Olivier; Fournier, Frantz; Kapel, Romain

doi:10.1016/j.fbp.2022.02.005

Cited by 5 publications

(3 citation statements)

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“…Regarding the valorization of RSM and the assessment of several alternatives, only one peer reviewed publication has been identified so far as relevant to the results presented herein. This publication by Beaubier et al [27] describes how Multiobjective Decision Making strategies built upon the Rough Set approach can be used for selective albumin extraction from RSM. On three process performance indicators (albumin extraction yield, albumin content in the extract, and phytic acid content in the residual solid residue), the effects of pH and NaCl concentration during the extraction step were examined.…”

Section: Discussionmentioning

confidence: 99%

Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects

Aragonés

Ondrejíčková²,

Lodeiro³

et al. 2022

Energies

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A framework for assessing, from a sustainability and circular bioeconomy point of view, the best valorization approach for biorefineries side-streams has been developed and validated. Two biorefinery side streams are considered as case-studies for validation: rapeseed meal from biodiesel and corn oil from bioethanol production. Firstly, a methodology to evaluate different valorization scenarios has been developed following a holistic approach that addresses technical aspects, environmental impact, and economic analysis. This way, a framework (inspired by the Battelle Method and using insights from Multicriteria Decision Analysis) has been produced where the sustainability potential of each scenario can be assessed. Such framework has been validated for five valorization scenarios for rapeseed meal and seven scenarios for corn oil. It can be concluded that protein extraction through alkaline (NaOH) hydrolysis is the best approach for rapeseed meal valorization while carotenoids recovery through ion exchange extraction is the most suitable strategy for corn oil. Secondly, for the selected scenarios, an estimation of the maximum recoverable amount of valuable compounds is conducted at the European and country-level. The use of this framework substantially aids in the best choice of the cutting-edge conversion technologies, supporting industry practitioners in the selection of processes to be further scaled-up.

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Section: Discussionmentioning

confidence: 99%

Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects

Aragonés

Ondrejíčková²,

Lodeiro³

et al. 2022

Energies

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“…Nevertheless, these processes degrade the cruciferins, making them difficult to valorize in foods. Recently, it has been shown that napins could be selectively extracted upon acidic conditions [ 16 , 17 ]. This process also allows for the co-production of a high-quality solid residue rich in cruciferins and low in phytic acid, but only applicable for feed utilization.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Selective Hydrolysis of Cruciferins for Production of Potent Mineral Chelating Peptides and Napins Purification to Valorize Total Rapeseed Meal Proteins

Kaugarenia

Beaubier

Durand

et al. 2022

Foods

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Preventing oxidation and microbial spoilage are both major concerns in food industries. In this context, this study aimed to valorize the total rapeseed meal proteins with controlled enzymatic proteolysis to generate potent mineral-chelating peptides from cruciferins while keeping intact the antimicrobial napins. Implementation of proteolysis of total rapeseed protein isolate with the Prolyve® enzyme highlighted an interesting selective hydrolysis of the cruciferins. Hence, the mechanism of this particular hydrolysis was investigated through a Design of Experiments method to obtain a model for the prediction of kinetics (cruciferin degradation and napin purity) according to the operating conditions applied. Then, multicriteria optimization was implemented to maximize the napin purity and yield while minimizing both enzymatic cost and reaction time. Antioxidant assays of the peptide fraction obtained under the optimal conditions proved the high metal-chelating activity preservation (EC50 = 247 ± 27 µg) for more than three times faster production. This fraction might counteract lipid oxidation or serve as preventing agents for micronutrient deficiencies, and the resulting purified napins may have applications in food safety against microbial contamination. These results can greatly help the development of rapeseed meal applications in food industries.

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“…From the different views, GrC models mainly cover four types: fuzzy sets [5], rough sets [6], quotient spaces [7], and cloud models [8]. As representative models of GrC, rough sets describe uncertain concepts by upper and lower approximation boundaries, which have been applied to data mining [9,10], medical systems [11], attribute reductions [12,13], decision systems [14,15], and machine learning [16].…”

Section: Introductionmentioning

confidence: 99%

Cost-Sensitive Multigranulation Approximation in Decision-Making Applications

Yang

Kuang

et al. 2022

Electronics

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A multigranulation rough set (MGRS) model is an expansion of the Pawlak rough set, in which the uncertain concept is characterized by optimistic and pessimistic upper/lower approximate boundaries, respectively. However, there is a lack of approximate descriptions of uncertain concepts by existing information granules in MGRS. The approximation sets of rough sets presented by Zhang provide a way to approximately describe knowledge by using existing information granules. Based on the approximation set theory, this paper proposes the cost-sensitive multigranulation approximation of rough sets, i.e., optimistic approximation and pessimistic approximation. Their related properties were further analyzed. Furthermore, a cost-sensitive selection algorithm to optimize the multigranulation approximation was performed. The experimental results show that when multigranulation approximation sets and upper/lower approximation sets are applied to decision-making environments, multigranulation approximation produces the least misclassification costs on each dataset. In particular, misclassification costs are reduced by more than 50% at each granularity on some datasets.

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Multiobjective decision making strategy for selective albumin extraction from a rapeseed cold-pressed meal based on Rough Set approach

Cited by 5 publications

References 44 publications

Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects

Valorizing Biodiesel and Bioethanol Side-Streams: Sustainability Potential Assessment through a Multicriteria Decision Analysis Framework and Appraisal of Valuable Compound Recovery Prospects

Optimization of Selective Hydrolysis of Cruciferins for Production of Potent Mineral Chelating Peptides and Napins Purification to Valorize Total Rapeseed Meal Proteins

Cost-Sensitive Multigranulation Approximation in Decision-Making Applications

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