Impact of sustainable polysaccharide coatings on shelf-life and quality parameters of bananas
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Carolina L. Recio-Colmenares
, Carlos Molina-Ramírez
und Hasbleidy Palacios-Hinestroza
Abstract
This study addresses the urgent need for sustainable alternatives to conventional plastic food packaging by developing and evaluating novel starch-based coatings enriched with chitosan and bacterial nanocellulose (BNC) derived from food waste. These coatings were applied to unripe bananas and their effectiveness in extending shelf-life was assessed over 21 days under controlled conditions. The results demonstrate that the coatings, particularly those containing chitosan, significantly reduced weight loss (up to 35 %), preserved firmness (maintaining 35 % higher firmness), and delayed the increase in reducing sugars (up to 63 % reduction at day 14), effectively doubling the shelf-life of bananas. The superior performance of chitosan-containing coatings is attributed to their film-forming properties, creating a modified atmosphere that retards ripening. This research highlights the potential of valorizing food waste into sustainable, high-performance polymeric coatings for food preservation, contributing to a circular economy in the food industry. Further research is needed to optimize the coatings for long-term effectiveness beyond 14 days.
Funding source: MINISTERIO DE CIENCIA, TECNOLOGÍA E INNOVACIÓN DE COLOMBIA (MINCIENCIAS)
Award Identifier / Grant number: 848
Funding source: Universidad de Guadalajara
Acknowledgments
In this study, generative artificial intelligence, particularly the Gemini language model, was used to review and improve the writing of the manuscript, ensuring the clarity and coherence of the text. Gemini’s assistance was useful in expediting the presentation of the re-search results and conclusions.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: Conceptualization, CM, HP and CR; methodology, CM; formal analysis, HP and CR; investigation, CM; resources, HP, BS; writing – original draft preparation, CM; writing – review and editing, HP and CR. All authors have read and agreed to the published version of the manuscript.
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Use of Large Language Models, AI and Machine Learning Tools: In this study, generative artificial intelligence, particularly the Gemini language model, was used to review and improve the writing of the manuscript, ensuring the clarity and coherence of the text. Gemini’s assistance was useful in expediting the presentation of the re-search results and conclusions.
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Conflict of interest: The authors declare no conflict of interest.
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Research funding: This research was funded by MINISTERIO DE CIENCIA, TECNOLOGÍA E INNOVACIÓN DE COLOMBIA (MINCIENCIAS), grant number 848 and The APC was funded by Universidad de Guadalajara.
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Data availability: Data is available upon request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/pac-2024-0295).
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