Response surface methodology in postharvest and food technology research: A bibliometric assessment
• RSM in postharvest and food research grew at an annual rate of 9.16% over the last decade. • The most cited paper received 364 citations in a study on spray drying. • India led in publications, and USA-China had the strongest collaboration. • Thematic analysis highlighted optimization, storage, and shelf-life as major themes. This bibliometric study revealed research trends in the global usage of response surface methodology (RSM) in postharvest and food technology, focusing on optimizing fruit and vegetable quality, storage, and shelf life. Data were retrieved from the Scopus database covering the years 2015 to 2024. A total of 2157 relevant publications were included. The Bibliometrix R-package and VOSviewer were used to analyze publication patterns, author networks, country collaborations, and thematic analysis. The results indicated a significant increase in publications, with an annual growth rate of 9.16% and a peak of 319 in 2024. Document analysis identified the most impactful studies in this field, with top-cited articles focusing on spray drying, pectin extraction, and phenolic encapsulation. India recorded the most publications, while the highest number of international collaborations was between the United States and China. Thematic analysis revealed the keywords "optimization”, "storage," and "shelf-life" as the major themes driving research in this field. This bibliometric analysis provides an overview of the current state of RSM in these productive research areas and suggests future opportunities for innovation and collaboration to reduce food loss and waste while increasing agriculture and food sustainability.
Authors
- Suchada Sukrong (ORCID: https://orcid.org/0000-0003-4062-2632)
- Pramod V. Mahajan (ORCID: https://orcid.org/0000-0002-6597-9841)
- Di Wu (ORCID: https://orcid.org/0000-0002-4997-5082)
- Sivaji Sathiyaraj
- Kayeen Vadakkan
- Rattapon Saengrayap (ORCID: https://orcid.org/0000-0002-9589-3619)
- Saowapa Chaiwong (ORCID: https://orcid.org/0000-0002-3750-0063)
- Tatiya Trongsatitkul (ORCID: https://orcid.org/0000-0001-7143-0137)
- Suriyakala Gunasekaran
Institutions
- Chulalongkorn University (TH)
- Amala Institute of Medical Sciences (IN)
- Mae Fah Luang University (TH)
- Leibniz Institute for Agricultural Engineering and Bioeconomy (DE)
- Zhejiang University (CN)
- Suranaree University of Technology (TH)
Publication Details
- Journal
- Applied Food Research
- Published
- 2025-10-25
- DOI
- https://doi.org/10.1016/j.afres.2025.101461
- Primary Topic
- Sensory Analysis and Statistical Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00