Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae DOI Open Access
Jun Wei Roy Chong, Doris Ying Ying Tang, Hui Yi Leong

et al.

Bioengineered, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 14, 2023

Fucoxanthin is a carotenoid that possesses various beneficial medicinal properties for human well-being. However, the current extraction technologies and quantification techniques are still lacking in terms of cost validation, high energy consumption, long time, low yield production. To date, artificial intelligence (AI) models can assist improvise bottleneck fucoxanthin process by establishing new processes which involve big data, digitalization, automation efficiency This review highlights application AI such as neural network (ANN) adaptive neuro fuzzy inference system (ANFIS), capable learning patterns relationships from large datasets, capturing non-linearity, predicting optimal conditions significantly impact yield. On top that, combining metaheuristic algorithm genetic (GA) further improve parameter space discovery ANN ANFIS models, results R2 accuracy ranging 98.28% to 99.60% after optimization. Besides, support vector machine (SVM), convolutional networks (CNNs), have been leveraged fucoxanthin, either computer vision based on color images or regression analysis statistical data. The findings reliable when modeling concentration pigments with 66.0% − 99.2%. paper has reviewed feasibility potential purposes, reduce cost, accelerate yields, development fucoxanthin-based products.

Language: Английский

Revolutionizing Agro-Food Waste Management: Real-Time Solutions through IoT and Big Data Integration DOI Open Access
Kallol Das, Tanvir Ahmed,

Suborna Rani

et al.

Voice of the Publisher, Journal Year: 2025, Volume and Issue: 11(01), P. 17 - 36

Published: Jan. 1, 2025

Language: Английский

Citations

1
Advances in Chlorella Microalgae for Sustainable Wastewater Treatment and Bioproduction DOI Creative Commons
Yazan Abuhasheesh, Aya Ghazal, Doris Ying Ying Tang

et al.

Chemical Engineering Journal Advances, Journal Year: 2025, Volume and Issue: unknown, P. 100715 - 100715

Published: Feb. 1, 2025

Language: Английский

Citations

1
Prediction of microalgae harvesting efficiency and identification of important parameters for ballasted flotation using an optimized machine learning model DOI
Kaiwei Xu, Zihan Zhu, Haining Yu

et al.

Algal Research, Journal Year: 2025, Volume and Issue: unknown, P. 103985 - 103985

Published: Feb. 1, 2025

Language: Английский

Citations

1
How could Artificial Intelligence be used to increase the potential of biorefineries in the near future? A review DOI Creative Commons
Ana Arias, Gumersindo Feijóo, Marı́a Teresa Moreira

et al.

Environmental Technology & Innovation, Journal Year: 2023, Volume and Issue: 32, P. 103277 - 103277

Published: July 13, 2023

Innovation in digitalization and low-carbon technologies are leading the way for production sector. In context of bioeconomy, a path is opening up integration bio-based processes into value chain as alternative schemes to fossil fuel-based models, although process modeling optimization needed this approach at an early stage design development. The large number variables biorefinery cascade scheme presents inherent difficulty strategy, considering conditions that allow higher productivity revenues parallel with lower environmental burdens. implementation artificial intelligence (AI) through techniques such machine learning predictive could be considered efficient tool optimization. Such require amounts historical data identify effects, synergies clusters parameters; detect anomalies; develop models predictive, prescriptive or root cause analysis; provide autonomous control. sense, critical review report aims overview available reports have AI evaluation identifying its potentialities enable better strategies under principles sustainability circular economy. This useful development further research on processes. work forefront innovations meet efficiency criteria order information interest policy makers, stakeholders industry professionals.

Language: Английский

Citations

21
Bridging artificial intelligence and fucoxanthin for the recovery and quantification from microalgae DOI Open Access
Jun Wei Roy Chong, Doris Ying Ying Tang, Hui Yi Leong

et al.

Bioengineered, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 14, 2023

Fucoxanthin is a carotenoid that possesses various beneficial medicinal properties for human well-being. However, the current extraction technologies and quantification techniques are still lacking in terms of cost validation, high energy consumption, long time, low yield production. To date, artificial intelligence (AI) models can assist improvise bottleneck fucoxanthin process by establishing new processes which involve big data, digitalization, automation efficiency This review highlights application AI such as neural network (ANN) adaptive neuro fuzzy inference system (ANFIS), capable learning patterns relationships from large datasets, capturing non-linearity, predicting optimal conditions significantly impact yield. On top that, combining metaheuristic algorithm genetic (GA) further improve parameter space discovery ANN ANFIS models, results R2 accuracy ranging 98.28% to 99.60% after optimization. Besides, support vector machine (SVM), convolutional networks (CNNs), have been leveraged fucoxanthin, either computer vision based on color images or regression analysis statistical data. The findings reliable when modeling concentration pigments with 66.0% − 99.2%. paper has reviewed feasibility potential purposes, reduce cost, accelerate yields, development fucoxanthin-based products.

Language: Английский

Citations

20