International Journal of Food Science & Technology· 2026Q1
Phenolic Profile of Kitaibelia balansae Leaf Extract and Machine-Learning Modelling of Effects on Pathogenic and Lactic Acid Bacteria
- 0citations
- Q1SCImago
- 2026year
Short summary
Kitaibelia balansae leaf extract, optimized via ultrasound-assisted extraction (UAE), inhibited pathogenic bacteria while promoting lactic acid bacteria growth over 24h, with Gaussian Process Regression (GPR) models accurately predicting these effects.
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Key points
- Ultrasound-assisted extraction (UAE) optimized for Kitaibelia balansae leaves yielded an extract with a targeted phenolic profile, including high syringic acid concentration.
- The extract inhibited growth of two pathogenic bacterial species but promoted growth of two lactic acid bacterial strains over 24 hours.
- Machine learning models, with GPR achieving the best performance, outperformed MLR in predicting the bacterial responses to the extract.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract This study followed a three-stage approach. First, phenolic compounds were extracted from Kitaibelia balansae leaves using ultrasound-assisted extraction (UAE), and the extraction parameters were optimised. The targeted phenolic profile of the optimised extract was analysed, and its effects on two pathogenic bacterial species and two lactic acid bacterial strains were monitored over 24 h. Syringic acid showed the highest measured concentration among the targeted compounds. Relative to the solvent-matched controls, extract-treated cultures showed lower growth measurements for the pathogenic bacteria and higher growth measurements for the selected lactic acid bacteria under the tested conditions. These findings represent microorganism-dependent responses to the whole extract and do not establish that individual phenolic compounds caused the observed effects. In the present evaluation, machine-learning models outperformed MLR, with GPR showing the best performance. Independent biological validation is needed to confirm broader generalizability.
The authors' abstract, as published at the source. International Journal of Food Science & Technology, 2026 · DOI ↗
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Field: Biochemistry (Medicine)
BiochemistryMedicine