Tren, Inovasi, dan Keberlanjutan dalam Mathematical Modelling untuk Food Science: Analisis Bibliometrik 2014–2024
DOI:
10.29303/jm.v6i2.8078Published:
2024-11-29Downloads
Abstract
Mathematical Modelling is an essential tool in various aspects of Food Science, particularly in addressing complex challenges such as production process optimization, shelf-life prediction, food waste management, and food safety assurance. This article aims to provide an in-depth analysis of research trends in Mathematical Modelling within Food Science during the 2014–2024 period, based on 350 documents indexed in Scopus. A bibliometric approach was employed using VOSviewer to map keyword relations, collaboration patterns among researchers, and geographical distribution of studies. The results revealed four main clusters of research topics: food safety and disease (Blue Cluster), sustainability and environmental issues (Red Cluster), prediction and process optimization (Yellow Cluster), and technology and innovation in food processing (Green Cluster). These findings underline the critical role of Mathematical Modelling in tackling global food challenges. This article provides recommendations to expand international collaborations and explore artificial intelligence integration in Mathematical Modelling research for food in the future.
Keywords: Bibliometrix, Food Science, Mathematical Modelling
Keywords:
Bibliometrix Food Science Mathematical ModellingReferences
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