A review of recent trends, advancements, and future directions in near-infrared spectroscopy applications in biofuel production and analysis

• Published in: Infrared physics & technology Vol. 145; p. 105692
• Main Authors: Odoi-Yorke, Flavio, Kaburi, Sandra Ama, Sanful, Rita Elsie, Otoo, Gifty Serwaa, Lamptey, Francis Padi, Abbey, Agnes Abeley, Agyekum, Ephraim Bonah, Darko, Ransford Opoku
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2025
• Subjects: Bibliometric analysis; Biofuels; Near-infrared spectroscopy; Oxidative stability; Biofuels; Bibliometric analysis; Oxidative stability; Near-infrared spectroscopy
• ISSN: 1350-4495
• DOI: 10.1016/j.infrared.2024.105692

•This study reviewed NIRS applications in biofuel production and analysis.•A total of 345 relevant documents from 1996 to 2023 were reviewed.•Current trends, advancements, and future directions in the subject were analysed.•The USA, China, and Brazil are the top publishing countries in this research area.•The Journal of Near Infrared Spectroscopy is one of the top publishing journals. The growing demand for sustainable energy solutions has intensified research into biofuel production and analysis techniques. Near-infrared spectroscopy (NIRS) has emerged as a promising tool in this field, yet a comprehensive understanding of its applications and impact remains lacking. This study aims to systematically review and analyse the applications of NIRS in biofuel production and analysis, providing insights into research trends, key contributors, and future directions. A bibliometric analysis was conducted using the Scopus database, covering publications from 1996 to 2023. The methodology included quantitative analysis, thematic mapping, factorial analysis, and citation analysis using the Bibliometrix package in R. The findings reveal a significant growth in NIRS biofuel applications, with an 11.85% annual increase in publications. The USA, China, and Brazil emerged as leading contributors, with strong international collaborations. Key applications include real-time monitoring of biodiesel production, biomass characterisation, and biogas production analysis. The integration of machine learning with NIRS data analysis represents a notable trend, enhancing prediction accuracy and model robustness. Thematic analysis identifies emerging research clusters in process monitoring, quality control, and feedstock analysis. These findings have important implications for both research and industry. The versatility of NIRS across various biofuel types and production stages suggests its potential for improving process efficiency and product quality. The identified research trends provide direction for future studies, particularly in standardising methodologies and developing more sophisticated data analysis techniques. This review highlights NIRS as a key technology that is enabling the advancement of sustainable biofuel production.