Prediction models applied to guava solar drying kinetics

Guava has excellent nutritional characteristics, being considered an important raw material in the food industry. For the efficient use of this fruit, it is necessary to adopt conservation techniques that delay the loss of quality resulting from the ripening process. Drying using solar energy, due t...

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Bibliographic Details
Authors: Lins, Bárbara Valéria Pereira, Farias, Fabiana Pimentel Macêdo, Silva, Débora Rafaelly Soares, Canuto, Morgana Fabílola Cunha Silva, Meira, Ana Clara Sampaio
Format: article
Status:Published version
Publication Date:2021
Country:Brasil
Institution:Universidade Federal de Itajubá (UNIFEI)
Repository:Research, Society and Development
Language:Portuguese
OAI Identifier:oai:ojs.pkp.sfu.ca:article/19761
Online Access:https://rsdjournal.org/index.php/rsd/article/view/19761
Access Level:Open access
Keyword:Psidium guajava L.
Dehydration
Post-harvest.
Deshidración
Poscosecha.
Desidratação
Pós-colheita.
Description
Summary:Guava has excellent nutritional characteristics, being considered an important raw material in the food industry. For the efficient use of this fruit, it is necessary to adopt conservation techniques that delay the loss of quality resulting from the ripening process. Drying using solar energy, due to its potential and low cost, is an economically viable alternative for the conservation of agro-industrial products. Thus, the objective of this study was to analyze the guava dehydration process and describe the drying kinetics using a solar dryer, as well as adjust the experimental data to mathematical modeling. Guavas of the Paluma variety were used at ripening stage 3 (green-yellow), purchased from local stores. The samples were placed in wire baskets and subjected to drying in a single layer in triplicate, using a solar dryer. The guava drying experimental data were fitted to the equations of Page, Henderson and Pabis, Lewis, Cavalcanti Mata and Thompson. The solar dryer provided satisfactory results in the guava drying process, where the best prediction of the drying kinetics process was obtained by the Page model.