Artificial Intelligence-Powered Algal Biodiesel: The Future of Biofuel Production Through Data-Driven Biotechnology

IF 3.9 2区生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Biotechnology and Bioengineering Pub Date : 2026-10-14 Epub Date: 2026-07-06 DOI:10.1002/bit.70305

Gyanendra Tripathi

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引用次数: 0

Abstract

Microalgae are promising feedstocks for sustainable biodiesel production, although their industrial use is currently limited by their biological complexity and high production costs. Recently, artificial intelligence (AI) technologies have been identified as promising, game-changing tools that could optimize algal biodiesel processes by leveraging data-driven biology. The purpose of this Review is to provide an integrated summary of recent developments in machine learning, deep learning, and hybrid models of microalgal biodiesel, analyzing AI frameworks that integrate biological and physical information with microalgal biodiesel process models to improve productivity, biological stability, and sustainability. It is essential to critically analyze the challenges of data quality and explainability in machine learning models, and to explain their use in techno-economic analysis of microalgal biodiesel. In the final part, directions for developing an independent microalgal biorefinery system using artificial intelligence tools are outlined to accelerate the lab-to-production transition of climate-relevant biofuels.

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人工智能驱动的藻类生物柴油：通过数据驱动的生物技术生产生物燃料的未来。

微藻是可持续生物柴油生产的有前途的原料，尽管它们的工业用途目前受到其生物复杂性和高生产成本的限制。最近，人工智能（AI）技术被认为是一种有前途的、改变游戏规则的工具，可以通过利用数据驱动的生物学来优化藻类生物柴油的生产过程。本综述的目的是对机器学习、深度学习和微藻生物柴油混合模型的最新发展进行综合总结，分析将生物和物理信息与微藻生物柴油过程模型相结合的人工智能框架，以提高生产力、生物稳定性和可持续性。批判性地分析机器学习模型中数据质量和可解释性的挑战，并解释它们在微藻生物柴油的技术经济分析中的应用是至关重要的。最后，概述了使用人工智能工具开发独立微藻生物精炼系统的方向，以加速气候相关生物燃料从实验室到生产的过渡。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biotechnology and Bioengineering 工程技术-生物工程与应用微生物

CiteScore

7.90

自引率

5.30%

发文量

280

审稿时长

2.1 months

期刊介绍： Biotechnology & Bioengineering publishes Perspectives, Articles, Reviews, Mini-Reviews, and Communications to the Editor that embrace all aspects of biotechnology. These include: -Enzyme systems and their applications, including enzyme reactors, purification, and applied aspects of protein engineering -Animal-cell biotechnology, including media development -Applied aspects of cellular physiology, metabolism, and energetics -Biocatalysis and applied enzymology, including enzyme reactors, protein engineering, and nanobiotechnology -Biothermodynamics -Biofuels, including biomass and renewable resource engineering -Biomaterials, including delivery systems and materials for tissue engineering -Bioprocess engineering, including kinetics and modeling of biological systems, transport phenomena in bioreactors, bioreactor design, monitoring, and control -Biosensors and instrumentation -Computational and systems biology, including bioinformatics and genomic/proteomic studies -Environmental biotechnology, including biofilms, algal systems, and bioremediation -Metabolic and cellular engineering -Plant-cell biotechnology -Spectroscopic and other analytical techniques for biotechnological applications -Synthetic biology -Tissue engineering, stem-cell bioengineering, regenerative medicine, gene therapy and delivery systems The editors will consider papers for publication based on novelty, their immediate or future impact on biotechnological processes, and their contribution to the advancement of biochemical engineering science. Submission of papers dealing with routine aspects of bioprocessing, description of established equipment, and routine applications of established methodologies (e.g., control strategies, modeling, experimental methods) is discouraged. Theoretical papers will be judged based on the novelty of the approach and their potential impact, or on their novel capability to predict and elucidate experimental observations.