The process of partial hydrogenation produces trans fats and the fats that undergo this process are called partially hydrogenated fats (PHF). Clinical studies have shown a strong association between PHF and coronary heart diseases. In 2015 The U.S. Food and Drug Administration removed the Generally recognized as safe or "GRAS" status of PHF. These fats were used in confectionary, margarines, shortenings, doughnuts, cookies, cakes, etc. The PHF serve a function in food by providing a higher shelf life and a desired harder structure due to their higher melting point. Hence, the food industry is currently looking for PHF alternatives which serve the function but have no harmful health effects. One of the alternatives to replace PHF is to use interesterified fats that have a low level of saturation that makes them healthier. However, these new fats are too soft with restricted use in many food applications. In this study, we explored the use of high intensity ultrasound (HIU) to improve the functional properties of interesterified fats and make them harder. Our study showed that HIU formed small crystals in these fats and increased their viscosity. The results from this study on the flavor release from the interesterified fats showed that the physical structure and hence the amount of solid fat in the sample affected its flavor perception. The solid fats had higher flavor perception than the liquid fat samples. The goal of this study is to improve the functionality of the interesterified fats using HIU and understand the flavor release from these fats to make substitution in food products easier.

Oxidation in oils and muscle foods has been studied for many years to understand its mechanism and furthermore to control and manage it. A series of different processing steps or different packaging techniques can alter oxidative stability. The objective of the current study was to examine oxidative stability of processed oil and to evaluate the effect of carbon dioxide generating mineral on quality of beef and chicken under different storage conditions. In Study 1 (Chapter 3), the effect of ultrasound on oxidative stability of interesterified soybean oil and soybean oil was examined. Sonication did not affect oxidation rate until the oils were highly oxidized. Sonicated interesterified soybean oil exhibited a slightly but significantly lower oxidation rate than non-sonicated oil during long-term storage, while sonication of non-interesterified soybean oil led to a significantly higher oxidation rate than in non-sonicated soybean oil after induction period. In Study 2 (Chapter 4), the feasibility of trona as a CO2 producing product in a model system and in modified atmosphere packaging of beef steaks was investigated. Trona was able to generate more carbon dioxide than sodium bicarbonate with salicylic acid in model systems. Steaks stored with trona/acid mixture had similar color stability and delayed lipid oxidation compared to those stored in high oxygen packaging. In Study 3 (Chapter 5), the effect of packets containing trona and acid placed in a simulated self serve retail case and closed butcher case on the quality of ground beef was studied. Mineral packets did not affect color, lipid oxidation, or microbial growth of ground beef since there was not a sufficient amount of moisture to generate CO2 effectively. In Study 4 (Chapter 6), the quality of chicken breast/thigh portions stored with mineral packets was compared to those without mineral packets during extended storage, and mineral packets had an antimicrobial effect of CO2 only on day 15. In conclusion, high intensity ultrasound did not affect the rate of oxidation of oil until the oil had already become noticeably rancid, and mineral packets containing trona and an acid with low water solubility can be used as CO2 generating sachet if sufficient moisture is given.

Orientador: Daniel Barrera Arellano / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-17T11:56:59Z (GMT). No. of bitstreams: 1 Gandra_KellyMoreira_D.pdf: 1962114 bytes, checksum: b863c0d311a5f84450122b2a375cd93e (MD5) Previous issue date: 2011 / Resumo: O desafio das indústrias de alimentos na substituição da gordura trans em diversos produtos consiste no desenvolvimento de formulações que apresentem funcionalidade equivalente e viabilidade econômica. A interesterificação química tem-se mostrado a principal alternativa para a obtenção de gorduras plásticas zero ou low trans. Apesar da evolução tecnológica dos processos de produção das matérias-primas, os métodos convencionais utilizados pelas indústrias alimentícias na formulação de gorduras especiais são demorados e trabalhosos e, além de cálculos, muitos procedimentos de tentativa e erro são necessários. As redes neurais constituem um campo da ciência da computação ligado à inteligência artificial, que tem sido utilizado com sucesso na área de óleos e gorduras. Mediante a dificuldade enfrentada pelas indústrias na etapa de formulação de gorduras, o objetivo deste trabalho foi aplicar a técnica de redes neurais artificiais na formulação de blends zero trans para recheios de biscoito. Foram construídas e treinadas redes neurais do tipo perceptron multicamadas, utilizando três matérias-primas: óleo de soja e duas bases interesterificadas. O treinamento das redes neurais foi realizado utilizando-se como variáveis de saída o conteúdo de gordura sólida e o ponto de fusão de 62 exemplos de blends elaborados com as três matérias-primas e, como variáveis de entrada, a proporção de cada matéria-prima utilizada nos diferentes blends. A verificação da aprendizagem e da eficiência das redes neurais em generalizar dados foi realizada solicitando-se formulações de 16 blends utilizados e 16 não utilizados no treinamento, respectivamente. Desta forma, observou-se o alto desempenho das redes neurais na predição do conteúdo de gordura sólida e ponto de fusão de blends formulados com as matérias-primas do treinamento. Para averiguar a amplitude de aplicação, formulações de gorduras para recheio de biscoito foram requisitadas à rede. Foram selecionadas três formulações para cada gordura comercial usada como padrão, sendo que todas apresentaram maior desvio do conteúdo de gordura sólida, em relação ao solicitado, nas temperaturas de 10°C e 20°C. Já o conteúdo de gordura sólida e ponto de fusão determinados experimentalmente para cada formulação foram muito semelhantes aos preditos. Os recheios produzidos com as formulações propostas pela rede e com as gorduras comerciais apresentaram excelente estabilidade térmica. As formulações propostas pela rede, apesar de se apresentarem mais macias que as gorduras comerciais, foram capazes de manter a estrutura dos recheios e os biscoitos unidos sem a expulsão do recheio. A rede neural pode ser considerada uma ferramenta de grande valor na indústria, como alternativa aos procedimentos convencionais de formulação, assim como na produção de alimentos com zero ou baixo teor de isômeros trans / Abstract: The challenge for food industries to replace trans fats in various products lies in the development of formulations that yield fats with equivalent functionality and economic feasibility. Chemical interesterification has been used as the main alternative for obtaining zero trans plastic fats. Despite the technological evolution of raw material production processes, conventional methods used by food industries to formulate specialty fats are time-consuming and laborious and, in addition to calculations, many trial and error procedures are necessary. Neural networks are a field of computer science related to artificial intelligence, which has been used successfully in the area of oils and fats. Considering the difficulties faced by industries in the formulation stage of fats, the objective of this study was to apply the technique of artificial neural networks in the formulation of blends for zero trans biscuit fillings. Multilayer perceptron neural networks were constructed and trained using three raw materials: soybean oil and two interesterified fat bases. The neural network training phase was performed using as input variables the solid fat content and melting point of 62 examples of blends prepared with the three raw materials and, as output variables, the proportion of each raw material used in the different blends. The assessment of the learning capacity and efficiency of the neural networks in generalizing data was performed by requesting formulations of 16 blends used in training and 16 not used in training, respectively. The high performance of the neural networks to predict the solid fat content and melting point of blends formulated with the raw materials used for training was observed. To determine the range of application, formulations of fats for biscuit filling were requested to the network. Three formulations for each commercial fat used as standard were selected, all of which presented deviations greater than the solid fat content requested at temperatures of 10°C and 20°C. However, the solid fat content and the melting point determined experimentally for each formulation were very similar to those predicted. The fillings made with the formulations proposed by the network and commercial fats showed excellent thermal stability. The formulations proposed by the network, even though softer than the commercial fats, were able to maintain the structure of both filling and biscuit together without the expulsion of the filling. Neural networks can be considered a very valuable resource for the industry, as an alternative to conventional formulation procedures, as well as for the design and production of foods with low or zero trans isomer contents / Doutorado / Engenharia de Alimentos / Doutor em Tecnologia de Alimentos

Orientador: Caroline Joy Steel / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-19T12:10:54Z (GMT). No. of bitstreams: 1 Penteado_AlessandraAfonsoTeixeira_M.pdf: 973579 bytes, checksum: 53ad98f08de44e474e99931a80129f8b (MD5) Previous issue date: 2012 / Resumo: Após as crescentes divulgações na mídia dos malefícios à saúde causados pela ingestão de gorduras trans e a Resolução RDC 360, de 23 de dezembro de 2003, que estabelece a obrigatoriedade de declaração dos níveis de gordura trans nos rótulos dos alimentos industrializados, nota-se uma crescente demanda por produtos sem ácidos graxos trans (¿low trans¿). O objetivo principal deste projeto foi aplicar a tecnologia de Redes Neurais Artificiais (RNAs) para a obtenção de blends de gorduras ¿low trans¿ derivadas de soja e avaliar seu desempenho quando aplicados no processamento de biscoitos laminados tipo Maria. Para tal, foram utilizadas duas bases de gorduras interesterificadas de soja (B1 e B2) e óleo de soja e, como características para definição do blend final foram utilizados os parâmetros de ponto de fusão e curva de sólidos das gorduras comerciais low trans e hidrogenada. Para a produção dos biscoitos, foram selecionados quatro blends de acordo com o menor erro apresentado pela RNA. Óleo de soja, gorduras comerciais low trans e hidrogenada de soja, foram utilizadas para comparação, bem como uma formulação sem adição de gordura. Todas as gorduras foram caracterizadas quanto aos índices de acidez, peróxido e iodo, composição em ácidos graxos e triacilgliceróis, ponto de fusão e curva de sólidos. Os blends foram caracterizados quanto ao ponto de fusão e curva de sólidos. Os biscoitos tiveram condições de processamento idênticas e diferenças de maquinabilidade da massa foram avaliadas. Após a produção dos biscoitos em escala laboratorial, os mesmos foram analisados quanto às suas características tecnológicas e físico-químicas (massa, dimensões, expansão, crescimento horizontal e vertical, cor instrumental, textura instrumental, atividade de água, gradiente de umidade, teor de umidade, teor de lipídios). Também foi realizado um acompanhamento mensal dos biscoitos por um período de quatro meses, analisando cor instrumental, textura instrumental, atividade de água, umidade e porcentagem de quebra/fissura. Os resultados mostraram que a gordura é fundamental para boa maquinabilidade, textura e umidade final dos biscoitos e ao longo do shelf- life estudado. Os biscoitos produzidos com os blends elaborados através da RNA, quando comparados com biscoitos produzidos com gorduras comerciais low trans e hidrogenada, não apresentaram alterações significativas nos parâmetros de processo/maquinabilidade e análises físico-químicas do produto final e ao longo de quatro meses de estocagem, sendo que o blend composto por 46% da base interesterificada de soja (B2) e 54% de óleo de soja, apresentou melhor performance. Assim, este estudo permite afirmar que através da RNA foi possível desenvolver gorduras para aplicação em biscoitos laminados que sejam low trans, derivadas de soja e com menor teor de saturados que as atuais gorduras comerciais. Portanto, representando uma vantagem para saúde do consumidor, otimizando tempo de formulação de gorduras, e possibilitando a obtenção de uma matéria prima para produção de biscoitos com maior disponibilidade no mercado brasileiro e a custos mais acessíveis / Abstract: After growing media disclosures of the health hazards caused by trans fats intake, and the RDC 360, 23 December 2003, establishing the mandatory declaration of trans fat levels on the labels of processed foods, a growing demand for products without trans fatty acids (¿low trans¿) has been noted. But the big challenge is getting ¿low trans¿ with the same functional and sensory properties of hydrogenated fats. The main objective of this project was to applied the technology of Artificial Neural Networks (ANN) to obtain fat blends derived from soy (low trans) and evaluate this performance when applied in the processing of rolled biscuits. To this end, was used two sets of soy interesterified fats (B1 e B2) and soybean oil and, as characteristics to define the blend, the parameters used were the melting point and the solid fat curve of the commercial fats low trans and hydrogenated. For the production of biscuits, four blends were selected according to the smallest ANN error. Soybean oil, commercial fats low trans and hydrogenated, were used for comparison as well as a fat-free formulation. All fats were characterized by acid value, peroxide and iodine index, fatty acid and triacylglycerols composition, melting point and solid fat curve. The biscuits had identical processing conditions and differences in machinability of the dough were evaluated. After biscuits production on a laboratory scale, they were analyzed in their technological and physicochemical characteristics (mass, size, expansion, horizontal and vertical growth, instrumental color, instrumental texture, water activity, moisture gradient, moisture and lipids value). Also, was carried out a monthly monitoring on the biscuits in a period of four months analyzing instrumental color, instrumental texture, water activity, moisture value and percentage of breakage/cracking biscuits. The results showed that fat is essential for a machinability, texture and moisture content in final biscuits and along the storage studied. The biscuits produced with the low trans blends prepared by the ANN, compared with the biscuits made with the commercial fatty low trans and hydrogenated, showed no significant changes in process/machinabilility parameters and physicalchemical analysis of the final products and over the four moth storage, and that the blend composed of 46% of the interesterified soybean (B2) and 54% soybean oil, had a better performance. Thus this study do suggest that through Artificial Neural Network was possible to develop low trans fats derived from soybean and less saturated fat than current commercial fats, for use in biscuits, representing a benefit for the consumer health, an operational and financial advantage, optimizing time of fats formulation, while enabling the obtains a raw material for biscuits production with Brasilian greater market availability and so, more affordable costs / Mestrado / Tecnologia de Alimentos / Mestre em Tecnologia de Alimentos