R
Roberto Gonçalves Junqueira
Researcher at Universidade Federal de Minas Gerais
Publications - 68
Citations - 1359
Roberto Gonçalves Junqueira is an academic researcher from Universidade Federal de Minas Gerais. The author has contributed to research in topics: Detection limit & Casein. The author has an hindex of 18, co-authored 68 publications receiving 1198 citations.
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A procedure to assess linearity by ordinary least squares method
TL;DR: In this article, a detailed procedure for testing linearity of calibration curves in method validation by the OLS method, including experimental design, estimation of the parameters, outlier treatment and evaluation of the assumptions, was proposed.
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Flour mixture of rice flour, corn and cassava starch in the production of gluten-free white bread
TL;DR: In this article, the use of rice flour corn and cassava starch was evaluated in several formulations aiming to find a flour mixture to replace wheat flour in the production of free-gluten white bread.
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Effects of high hydrostatic pressure (HHP) on sensory characteristics of yellow passion fruit juice
L. H. E. S. Laboissiere,Rosires Deliza,A.M. Barros-Marcellini,Amauri Rosenthal,L. M. A. Q. Camargo,Roberto Gonçalves Junqueira +5 more
TL;DR: In this article, the effects of high hydrostatic pressure on the sensory properties of passion fruit juice by quantitative descriptive analysis (QDA) were investigated, which revealed high similarity among juice sensory attributes from in natura and pressurized samples both differing from commercial ones.
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Isolation and screening of alkaline lipase-producing fungi from Brazilian savanna soil
TL;DR: The most productive strain, identified as Colletotrichum gloesporioides, produced 27,700 U/l of lipase under optimized conditions and the crude lipase preparation was capable of hydrolysing a broad range of substrates including lard, natural oils and tributyrin.
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Detection of several common adulterants in raw milk by MID-infrared spectroscopy and one-class and multi-class multivariate strategies.
Carina de Souza Gondim,Roberto Gonçalves Junqueira,Scheilla Vitorino Carvalho de Souza,Itziar Ruisánchez,M. Pilar Callao +4 more
TL;DR: A sequential strategy was proposed to detect adulterants in milk using a mid-infrared spectroscopy and soft independent modelling of class analogy technique, providing 82% correct classifications, 17% inconclusive classifications and 1% misclassifications.