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For: Khan M, Chuenchart W, Surendra KC, Kumar Khanal S. Applications of artificial intelligence in anaerobic co-digestion: Recent advances and prospects. Bioresour Technol 2023;370:128501. [PMID: 36538958 DOI: 10.1016/j.biortech.2022.128501] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 06/17/2023]
Number Cited by Other Article(s)
1
Chandekar B, M V R, Patel SKS. Efficient dark-fermentation biohydrogen production by Shigella flexneri SPD1 from biowaste-derived sugars through green solvents approach. BIORESOURCE TECHNOLOGY 2024;410:131276. [PMID: 39151564 DOI: 10.1016/j.biortech.2024.131276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 08/08/2024] [Accepted: 08/13/2024] [Indexed: 08/19/2024]
2
Gupta RK, Patel SKS, Lee JK. Novel cofactor regeneration-based magnetic metal-organic framework for cascade enzymatic conversion of biomass-derived bioethanol to acetoin. BIORESOURCE TECHNOLOGY 2024;408:131175. [PMID: 39084533 DOI: 10.1016/j.biortech.2024.131175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/10/2024] [Accepted: 07/28/2024] [Indexed: 08/02/2024]
3
Zhang K, Wang N. Machine learning modeling of thermally assisted biodrying process for municipal sludge. WASTE MANAGEMENT (NEW YORK, N.Y.) 2024;188:95-106. [PMID: 39128323 DOI: 10.1016/j.wasman.2024.07.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 07/12/2024] [Accepted: 07/29/2024] [Indexed: 08/13/2024]
4
Saha R, Chauhan A, Rastogi Verma S. Machine learning: an advancement in biochemical engineering. Biotechnol Lett 2024;46:497-519. [PMID: 38902585 DOI: 10.1007/s10529-024-03499-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/24/2024] [Accepted: 05/18/2024] [Indexed: 06/22/2024]
5
Kovačić Đ, Radočaj D, Jurišić M. Ensemble machine learning prediction of anaerobic co-digestion of manure and thermally pretreated harvest residues. BIORESOURCE TECHNOLOGY 2024;402:130793. [PMID: 38703965 DOI: 10.1016/j.biortech.2024.130793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 04/30/2024] [Accepted: 05/01/2024] [Indexed: 05/06/2024]
6
Sun J, Rao Y, He Z. Machine learning-aided inverse design for biogas upgrading through biological CO2 conversion. BIORESOURCE TECHNOLOGY 2024;399:130549. [PMID: 38461869 DOI: 10.1016/j.biortech.2024.130549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 02/24/2024] [Accepted: 03/06/2024] [Indexed: 03/12/2024]
7
Zhai S, Chen K, Yang L, Li Z, Yu T, Chen L, Zhu H. Applying machine learning to anaerobic fermentation of waste sludge using two targeted modeling strategies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024;916:170232. [PMID: 38278257 DOI: 10.1016/j.scitotenv.2024.170232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/28/2024]
8
Song C, Cai F, Yang S, Wang L, Liu G, Chen C. Machine learning-based prediction of methane production from lignocellulosic wastes. BIORESOURCE TECHNOLOGY 2024;393:129953. [PMID: 37914053 DOI: 10.1016/j.biortech.2023.129953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/29/2023] [Accepted: 10/29/2023] [Indexed: 11/03/2023]
9
Piadeh F, Offie I, Behzadian K, Bywater A, Campos LC. Real-time operation of municipal anaerobic digestion using an ensemble data mining framework. BIORESOURCE TECHNOLOGY 2024;392:130017. [PMID: 37967795 DOI: 10.1016/j.biortech.2023.130017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/05/2023] [Accepted: 11/10/2023] [Indexed: 11/17/2023]
10
Li L, Guan W, Fan Y, He Q, Guo D, Yuan A, Xing Q, Wang Y, Ma Z, Ni J, Chen J, Zhou Q, Zhong Y, Li J, Zhang H. Zinc/carbon nanomaterials inhibit antibiotic resistance genes by affecting quorum sensing and microbial community in cattle manure production. BIORESOURCE TECHNOLOGY 2023;387:129648. [PMID: 37572887 DOI: 10.1016/j.biortech.2023.129648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/02/2023] [Accepted: 08/05/2023] [Indexed: 08/14/2023]
11
Sukphun P, Wongarmat W, Imai T, Sittijunda S, Chaiprapat S, Reungsang A. Two-stage biohydrogen and methane production from sugarcane-based sugar and ethanol industrial wastes: A comprehensive review. BIORESOURCE TECHNOLOGY 2023;386:129519. [PMID: 37468010 DOI: 10.1016/j.biortech.2023.129519] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/14/2023] [Accepted: 07/16/2023] [Indexed: 07/21/2023]
12
Li Y, Xue Z, Li S, Sun X, Hao D. Prediction of composting maturity and identification of critical parameters for green waste compost using machine learning. BIORESOURCE TECHNOLOGY 2023;385:129444. [PMID: 37399955 DOI: 10.1016/j.biortech.2023.129444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 06/28/2023] [Accepted: 06/30/2023] [Indexed: 07/05/2023]
13
Nie E, He P, Peng W, Zhang H, Lü F. Microbial volatile organic compounds as novel indicators of anaerobic digestion instability: Potential and challenges. Biotechnol Adv 2023;67:108204. [PMID: 37356597 DOI: 10.1016/j.biotechadv.2023.108204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 06/07/2023] [Accepted: 06/19/2023] [Indexed: 06/27/2023]
14
Sonwai A, Pholchan P, Tippayawong N. Machine Learning Approach for Determining and Optimizing Influential Factors of Biogas Production from Lignocellulosic Biomass. BIORESOURCE TECHNOLOGY 2023;383:129235. [PMID: 37244314 DOI: 10.1016/j.biortech.2023.129235] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 05/19/2023] [Accepted: 05/21/2023] [Indexed: 05/29/2023]
15
Khanal SK, Tarafdar A, You S. Artificial intelligence and machine learning for smart bioprocesses. BIORESOURCE TECHNOLOGY 2023;375:128826. [PMID: 36871700 DOI: 10.1016/j.biortech.2023.128826] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
16
Zhang Y, Feng Y, Ren Z, Zuo R, Zhang T, Li Y, Wang Y, Liu Z, Sun Z, Han Y, Feng L, Aghbashlo M, Tabatabaei M, Pan J. Tree-based machine learning model for visualizing complex relationships between biochar properties and anaerobic digestion. BIORESOURCE TECHNOLOGY 2023;374:128746. [PMID: 36813050 DOI: 10.1016/j.biortech.2023.128746] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 02/09/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
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