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Composite Coatings Applied to Fresh and Blanched Chayote ( Sechium edule ) and Modeling of the Drying Kinetics and Sorption Isotherms.

Yokiushirdhilgilmara Estrada-GirónAngelina Martín Del Campo-CamposEmmanuel Gutiérrez-GarcíaVíctor V Fernández-EscamillaLiliana Martínez-ChávezTeresa J Jaime-Ornelas
Published in: Foods (Basel, Switzerland) (2024)
Sustainable methods such as convective drying have regained interest in reducing the loss and waste of food produce. Combined with techniques like blanching and edible coatings, they could serve as useful tools in food processing development. Composite coatings comprising pectin, soy protein isolate, and xanthan gum were optimized using response surface methodology with the Box-Behnken design. This optimization aimed to investigate their effects on the moisture content, water activity, total color, and rehydration ratio of fresh and blanched chayote slices. Additionally, the study explored the modeling of the drying kinetics and sorption isotherms of chayote ( Sechium edule ) slices. Soy protein and xanthan gum were found to primarily influence the moisture content (ranging from 5.44% to 9.93%), and pectin influenced water activity (033 to 0.53) of the fresh-coated chayote, while pectin affected the a w (2.13-8.28) and rehydration of the blanch-coated chayote. The optimized formulations for both fresh and blanched chayote were utilized to assess the drying kinetics behavior and sorption isotherms. The best fit (R 2 : 0.996 to 0.999) was achieved with the parabolic model for thin-layer materials. Furthermore, the sorption isotherms of chayote displayed a Type IV behavior, with the BET model being the most suitable for describing the sorption behavior of materials with low water activity. The predicted values offer valuable data for optimizing processing conditions to enhance the quality and stability of dried chayote.
Keyphrases
  • sewage sludge
  • organic matter
  • protein protein
  • machine learning
  • electronic health record
  • quality improvement
  • big data
  • artificial intelligence
  • municipal solid waste
  • data analysis