Exploring the perception and sensory acceptance of a Peruvian purple maize breakfast cereal by Brazilian consumers

This study aimed to explore the perception and sensory acceptance of Purple Maize (PM) breakfast cereals by a Brazilian panel. The extrudates were elaborated using 25%, 50%, 75%, and 100% PM in a commercial yellow corn base. A total of 117 consumers evaluated samples through an acceptability test (nine-point hedonic scale) followed by CATA questions (35 descriptive terms) and a market research questionnaire. The cereals formulated with 50% and 75% PM had the best scores (6) in color, aroma, texture, and overall liking during the acceptability test. Based on the penalty-lift analysis, Brazilian consumers' most important drivers of preference were the attractive color, crispy texture, and the natural and innovative purple color. In contrast, hard texture and brown color drivers negatively impacted the scores. In the market research, consumers indicated that they could eat the product both as a breakfast cereal and as a snack during the day; Likewise, they highlighted the possible health benefits, the innovative color, and the use of exotic raw materials as the best characteristics of the product. Therefore, using 50% PM or more allows for obtaining sustainable and nutritious breakfast cereals with characteristics of color, flavor, and texture well accepted by Brazilian consumers.Campus Lima Su

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Effects of thermoplastic extrusion on "blends" of brewing by-products

Orientador: Caroline Joy SteelDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: A reutilização de resíduos agroindustriais está atraindo cada vez mais a atenção de pesquisadores, pois subprodutos são uma fonte barata de fibras, proteínas e compostos bioativos, apesar de sua composição heterogênea e instabilidade microbiológica. A indústria cervejeira gera bilhões de toneladas de subprodutos anualmente, entre os quais, em maior quantidade, o resíduo úmido de cervejaria (RUC), composto principalmente por bagaço de malte, apresentando, em base seca, em torno de 58% de fibras dietéticas insolúveis (FDI), 18% de proteínas e 14% de lipídeos; e o excesso de levedura (LEV), contendo 53% de proteínas, 20% de fibras dietéticas totais (FDT) e 7% de minerais. Entretanto, ambos apresentam alta umidade, 78% e 86%, respectivamente, implicando em difícil manipulação e transporte, além de rápida deterioração. Gerado em menor quantidade, porém com baixa umidade, o pó de malte (PDM) é formado por, aproximadamente, 65% de carboidratos, 15% de proteínas e 14% de FDI, mas sua alta carga microbiana provocou restrição no uso. Entre as técnicas exploradas para reutilização de resíduos agroindustriais, a extrusão termoplástica mostra grandes vantagens, pois permite a utilização do subproduto como um todo, aliando calor, pressão e cisalhamento, sem gerar resíduos. Entre suas limitações estão umidade e tamanho de partículas da matéria-prima. Decidiu-se utilizar um Delineamento de Misturas para compor blends dos subprodutos, com uma umidade máxima de 30% para o ponto centroide, explorando-se duas alternativas: Delineamento A ¿ secagem do RUC e composição de blends com RUCseco, LEV e grits de milho; Delineamento B ¿ blends com RUC, LEV e PDM, aliados a 55% de pó de arroz (PDA), subproduto do processamento de saquê, contendo 65% de carboidratos e 18% de proteína. Os parâmetros de processo foram fixados em: velocidade de alimentação 250 rpm; velocidade da rosca 390 rpm; temperatura das zonas, da alimentação à matriz, 45-60-80-110ºC. Os extrusados do Delineamento A apresentaram altas umidades, durezas e densidades, baixos índices de expansão (IE), solubilidade em água (ISA) e absorção de água (IAA), fenômenos atribuídos à alta quantidade de fibras insolúveis do RUCseco. Os extrusados do Delineamento B, apresentaram maiores IE e ISA, menores durezas e densidades, porém teor proteico similar ao do Delineamento As características atribuídas à alta proporção de PDA. A otimização dos produtos visou menor umidade e melhores propriedades tecnológicas. Restauração de peças da extrusora levou ao aumento da energia mecânica (EME) do sistema, influenciando as propriedades tecnológicas dos produtos otimizados. Estes foram analisados quanto à sua composição centesimal, incluindo FDT e FDI; à digestibilidade in vitro de proteínas (DIVP); aos parâmetros tecnológicos: atividade de água, IE, densidade aparente, dureza instrumental, cor instrumental (CIELab), ISA e IAA, e propriedades de pasta (RVA); e à qualidade microbiológica. Os otimizados A revelaram alto conteúdo de FDI e lipídeos, o que regeu suas propriedades tecnológicas, produzindo extrusados com estrutura frágil e oca. Os otimizados B exibiram alto IE e baixa dureza, porém resultados com alto coeficiente de variação, associados à heterogeneidade do PDM. Conclui-se que é possível utilizar extrusão termoplástica para transformação de subprodutos agroindustriais em novos produtos ou ingredientes, com diferentes propriedades tecnológicas e nutricionais, para alimentação humana ou animalAbstract: The recovery of agroindustrial wastes is increasingly attracting the attention of researchers, since by-products are an inexpensive source of fibres, proteins and various bioactive compounds, despite their heterogeneous composition and microbiological instability. The brewery industry produces billions of tons of by-products each year, including, in greater quantity, brewer's spent grain (BSG), mainly composed of malt bagasse, providing, on a dry basis, about 58% insoluble dietary fibres (IDF), 18% proteins and 14% lipids; and brewer¿s spent yeast (BSY), containing 53% proteins, 20% total dietary fibres (TDF) and 7% of minerals. However, both have a high moisture content, 78% and 86%, respectively, implying difficult handling and transportation, and rapid deterioration. Generated in smaller quantities but with low moisture content, malt powder (MP) is comprised of approximately 65% carbohydrates, 15% proteins and 14% IDF, however, its high microbial load implied usage restrictions. Among the techniques used to recycle agroindustrial waste, thermoplastic extrusion shows great advantages, as it allows the use of the by-products as a whole, combining heat, pressure and shear, without generating residues. Among its limitations are feed moisture and particle size. It was decided to use a Mixture Design to compose blends of by-products, with a maximum moisture of 30% for the centroid point, exploring two alternatives: Design A ¿ drying of BSG and blends composition with dryBSG, BSY and corn grits; Design B ¿ blends with BSG, BSY and MP, allied to 55% rice powder (RP), a by-product from sake processing, with 65% carbohydrates and 18% proteins. The process parameters were set at: feed rate 250 rpm; screw speed 390 rpm; temperature of the zones, from the feed hopper to the die, 45-60-80-110ºC. The extruded products from Design A presented high moisture content, hardness and density, low indices of expansion (EI), water solubility (WSI) and water absorption (WAI), phenomena attributed to the high amount of insoluble dryBSG fibres. The extruded products of Design B, presented higher EI and WSI, lower hardness and densities, but a similar protein content to that of Design A, characteristics attributed to a high proportion of RP. The optimization of the products aimed at lower moisture and better technological properties. Restoration of extruder parts led to the increase in mechanical energy (SME) of the system, influencing the technological properties of the optimized products. They were analysed regarding their proximate composition, including TDF and IDF; their protein in vitro digestibility (PIVD); their technological parameters: water activity, EI, apparent density, instrumental hardness, instrumental colour (CIELab), WSI and WAI, and pasting properties (RVA); and their microbiological quality. The optimized A extrudates revealed high content of insoluble fibres and lipids, which governed its technological properties, producing brittle, hollow extruded products. The optimized B extrudates showed high EI and low hardness, but a high coefficient of variation for the results, associated to the heterogeneity of the MP. In conclusion, it is possible to apply thermoplastic extrusion for transformation of agroindustrial by-products into new products or ingredients with different technological and nutritional properties, for human or animal feedingMestradoTecnologia de AlimentosMestra em Tecnologia de Alimentos131799/2016-9CNP