AVOCADO FOR POST-HARVEST CONSERVATION: USE OF ALGINATE COATING AND MATHEMATICAL MODELING VIA ARTIFICIAL NEURAL NETWORKS FOR PREDICTING THE QUALITY AND STABILITY OF BIOACTIVE COMPOUNDS

• Grant number: 25/12405-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2025
• End date: September 30, 2026
• Field of knowledge: Agronomical Sciences - Food Science and Technology - Food Technology
• Principal Investigator: Angela Vacaro de Souza
• Grantee: Gabrielli de Paula Affonso Borges
• Host Institution: Faculdade de Ciências e Engenharia. Universidade Estadual Paulista (UNESP). Campus de Tupã. Tupã , SP, Brazil

Abstract

The aim of this study is to evaluate the effect of an edible coating based on sodium alginate, in different concentrations, on the post-harvest conservation of 'Hass' avocado. Physical-chemical parameters (moisture, pH, titratable acidity, soluble solids, ratio), biochemical parameters (phenolic compounds, flavonoids, vitamin C, antioxidant activity by DPPH and FRAP), instrumental color, firmness, mass loss and bioactive compounds in the pulp and peel will be analyzed. Essential minerals and fat-soluble vitamins will also be quantified using reference methods. The treated fruits will be stored under refrigeration and periodically evaluated during the storage period at 5ºC and 90% RH. The experimental data will feed artificial neural network models to predict the best concentration of alginate and the ideal time for consumption, aiming to optimize the quality and shelf life of the fruit. The results will contribute to the development of sustainable conservation strategies, adding value to Brazilian avocados and promoting innovation in the production chain. (AU)