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Doctoral Thesis
DOI
10.11606/T.89.1999.tde-19032008-102256
Document
Author
Full name
Inar Alves de Castro
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 1999
Supervisor
Committee
Toledo, Júlio Orlando Tirapegui (President)
Areas, José Alfredo Gomes
Colli, Célia
Correa, Ana Maria Segall
Silva, Rui Sérgio dos Santos Ferreira da
Title in Portuguese
Modelagem e otimização de propriedades nutricionais e sensoriais de misturas protéicas através da metodologia estatística de superfície de resposta
Keywords in Portuguese
Gelatina
Gluten
Misturas protéicas
NPR
PDCAAS
Proteina do leite
Soja
Abstract in Portuguese
Gelatina Hidrolisada (GH), Glúten de Trigo (GT) e Isolado Protéico de Soja (IPS) foram misturados em diferentes proporções com o objetivo de substituir proteínas lácteas em uma formulação alimentícia utilizada em programas institucionais de alimentação escolar, buscando-se uma redução de custos sem alterações significativas das propriedades nutricionais e sensoriais do produto final. A qualidade nutricional das misturas foi avaliada de acordo com os métodos "Escore Químico corrigido pela Digestibilidade PDCAAS" e "Razão de Eficiência Protéica - NPR". As misturas, aplicadas àformulação de uma bebida láctea, foram avaliadas sensorialmente através do método de "Diferença Escalar do Controle". Os resultados obtidos experimentalmente pelo delineamento simplex-centróide foram utilizados para modelar equações canônicas de Scheffé que pudessem descrever o efeito da proporção de cada componente na qualidade final. Todos os resultados foram correlacionados através de análise multivariada e representados na forma de Análise de Componente Principal (ACP). Uma "solução de compromisso" contendo 25% de GH, 15% GT e 60% de IPS foi selecionada na otimização conjunta das respostas nutricional, sensorial e econômica, resultando na redução média de 6% do custo do produto final sem alteração significativa de qualidade (p < 0,01). Estes resultados revelaram a eficiência da utilização de técnicas estatísticas multivariadas na otimização simultânea e na visualização das interações que ocorrem em processos complexos como sistemas biológicos.
Title in English
Protein mixtures and their nutritional properties optimized by response surface methodology
Keywords in English
Gelatin
Gluten
NPR
PDCAAS
Protein mixtures
Soybean
Abstract in English
Hidrolizated Gelatin (HG), Wheat Gluten (WG) and Soybean Protein Isolate (SPI) were mixed at different proportions in order to partially replace milk proteins in food formulation utilized in Food Programs to reduce its cost without significant decrease in its nutritional and sensorial properties. The nutritional quality of the mixtures was evaluated by the "Protein DigestibilityCorrected Amino Acid Score (PDCAAS)" and "Net Protein Ratio (NPR)"methods. The sensorial quality of the mixtures was evaluated by the "Scale Difference of Control". The results obtained experimentally by simplex design were used to elaborate Scheffé's canonical equations that would describe the effect of the proportion of each component on the final nutritional quality of the product. Ali the results were correlationed by Multivariate Analysis and represented by Principal Component Analysis (PCA). A "compromise solution" containing 25% HG, 15% WG and 60% SPI was selected as multiresponse optimization. This mixture was applicated in food formulation and submitted to the evaluations of nutrition and sensorial quality. The final product showed about 6% of cost reduction without any significant change in its quality (p< 0,01). These results demonstrated the statistics multivariate methods efficiency in simultaneous optimization and visualization of interactions which are present in complex process like biological systems.
 
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InarACastro_Tese.pdf (39.12 Mbytes)
Publishing Date
2008-03-20
 
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