ArticleACS omega2026
Microencapsulation of Beetroot Anthocyanins: Investigation of Degradation Kinetics and Modeling by Using Artificial Neural Networks.
Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A Novel Dairy-Beetroot Powder: Microencapsulation Improves Stability and Sensory Qualities While Preserving Cardioprotective Bioactives.Foods (Basel, Switzerland) · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anthocyanins are widely appreciated as natural pigments, but their use in foods and related industries is still quite limited because they are highly sensitive to heat, pH changes, light, and oxygen. Improving their stability has therefore become a key focus in developing more reliable natural color systems. In this study, beetroot anthocyanins were microencapsulated with different wall materials, maltodextrin (MD), gum arabic (GA), a simple MD/GA blend, and a ternary structure combining MD, GA, and sodium caseinate (MD/GA/SC). These systems were evaluated for their encapsulation efficiencies, antioxidant activity preservation, release behaviors, and degradation responses over a wide range of temperatures (40-100 °C) and pH levels (2.5-6.5). Remarkable findings demonstrated that the MD/GA/SC formulation provided the highest encapsulation efficiency (93.36%), superior radical-scavenging activity (88.43%), and the most controlled release profile. Moreover, this formulation demonstrated the lowest degradation rate constants at pH 2.5, 4.5, and 6.5 (2.886, 2.083, and 1.30 1/min, respectively) together with the highest activation energies at these pH levels (37.460, 52.517, and 62.045 kJ/mol, respectively), indicating a pronounced improvement in thermal stability compared with the other formulations and the free extract. An artificial neural network (ANN) model was developed to predict anthocyanin degradation. The ANN provided highly accurate predictions (
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Registered trials
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