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Hyperspectral imaging and artificial intelligence for quality control of protein-based products: isolates, microcapsules and gels

Grant number: 20/09198-1
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): November 01, 2020
Effective date (End): October 31, 2024
Field of knowledge:Agronomical Sciences - Food Science and Technology - Food Engineering
Principal researcher:Douglas Fernandes Barbin
Grantee:Luis Jam Pier Cruz Tirado
Home Institution: Faculdade de Engenharia de Alimentos (FEA). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Protein is one of the fundamental macronutrients for the development and maintenance of the human body. In the last few years, the concern with the population increase and reduced resources, has generated a change in the consumption of animal protein for vegetable protein and emerging sources (e.g. insect). The protein isolated from different sources can be used for the development of new food formulations, as a wall material to encapsulate compounds of interest or as a biopolymer for packaging applications. Obtaining protein products involves several parameters: (1) quality of the protein isolate, (2) control of the production process of the materials, including the efficiency of the process, and (3) quality of the final product. In this approach, it is necessary to develop analysis methodologies that are fast, reliable, free of reagents and easy to execute. Hyperspectral images (HSI) fulfill this criterion, and their application in protein products is, until today, little explored. However, the large amount of information provided by HSI must be analyzed using Artificial Intelligence (AI), such as machine learning methods. In this project, we propose to use HSI in combination with AI to develop new analytical methodologies for the quality control of protein products, which includes protein isolates, oil-filled microcapsules and hydrogels and curcumin-loaded aerogels.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BRASIL, YASMIN LIMA; CRUZ-TIRADO, J. P.; BARBIN, DOUGLAS FERNANDES. Fast online estimation of quail eggs freshness using portable NIR spectrometer and machine learning. FOOD CONTROL, v. 131, JAN 2022. Web of Science Citations: 3.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.