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Multivariate statistical analyses applied to NIR spectroscopy and digital image analyses for food products

Grant number: 19/12625-1
Support type:Scholarships in Brazil - Master
Effective date (Start): August 01, 2019
Effective date (End): July 31, 2021
Field of knowledge:Agronomical Sciences - Food Science and Technology - Food Engineering
Principal researcher:Douglas Fernandes Barbin
Grantee:Ingrid Alves de Moraes
Home Institution: Faculdade de Engenharia de Alimentos (FEA). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:15/24351-2 - Applications of image analyses and NIR spectroscopy for quality assessment and authentication of food products, AP.JP


This master's project will investigate the application of near-infrared spectral images (NIR-HSI) for differentiation and determination of the composition of different varieties of cocoa beans. Chemical composition and physical-chemical parameters such as color and pH will be evaluated for characterization of the samples. The images will be acquired and the region of interest to be analyzed will be isolated to obtain the spectra. The most relevant wavelengths in spectral measurements will be identified through variable selection methods to be used in predictive models, in order to reduce the volume of data for processing, enabling applications in the food industry. This work will be developed within a Young Researcher Project, whose proposal is to develop innovative methods of food evaluation with potential for medium-term application in industry. (AU)

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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
MORAES, Ingrid Alves de. The evaluation and classification of carambola using portable near infrared spectrometer (NIR). 2021. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia de Alimentos Campinas, SP.

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