Influence of natural and synthetic carotenoids on the color of egg yolk

Carotenoids are incorporated into the diet of laying hens in order to modify the yolk color. A natural source of carotenoids in tropical countries is annatto, which could be used in the diets of hens. This study aimed to evaluate the addition of natural (annatto) and synthetic carotenoids to the diet of laying hens (commercial and alternative) and their effects on yolk color and consumer sensory perception of fresh and stored eggs obtained from two different preparations (boiled and fried). Physicochemical analysis of proximate composition, thiobarbituric acid reactive substances (TBARS), emulsion activity and instrumental color were performed. Cooking caused significant alterations to the moisture in the preparations and this may have directly affected the color intensity, influencing factors related to egg appearance. In this study, 85 % of the panelists indicated that yolk color is an important attribute of the product’s quality. There was no antioxidant effect of the carotenoids in raw eggs. Synthetic additives should be better dosed to obtain the desired effect. Storage did not alter the proximate composition of the eggs

Viscosidade da clara de ovo proveniente de poedeiras de diferentes espécies com aditivos comerciais e naturais

Yolk color and egg white (albumen) cleanliness and viscosity are important parameters by which consumers judge the quality of eggs. This study aimed to investigate changes in albumen viscosity during storage of eggs for up to 36 days from two different commercial laying hen strains (Carijo Barbada and Isa Brown) fed a diet containing annatto (1.5 and 2.0%) or a synthetic additive without synthetic colorants (control). Analyses of humidity, albumen height, pH, viscosity, foam formation, and stability were carried out on eggs. Carijo Barbada strain had smaller albumen, lower humidity and higher egg white viscosity than Isa Brown strain; however, with storage, viscosity lowered significantly on both strains. Initially, the addition of 2.0% of annatto or a synthetic additive increased viscosity in both strains, but with storage only the control maintained longer viscosity. Lower viscosity did not change foam density and stability

Influence of natural and synthetic carotenoids on the color of egg yolk

ABSTRACT Carotenoids are incorporated into the diet of laying hens in order to modify the yolk color. A natural source of carotenoids in tropical countries is annatto, which could be used in the diets of hens. This study aimed to evaluate the addition of natural (annatto) and synthetic carotenoids to the diet of laying hens (commercial and alternative) and their effects on yolk color and consumer sensory perception of fresh and stored eggs obtained from two different preparations (boiled and fried). Physicochemical analysis of proximate composition, thiobarbituric acid reactive substances (TBARS), emulsion activity and instrumental color were performed. Cooking caused significant alterations to the moisture in the preparations and this may have directly affected the color intensity, influencing factors related to egg appearance. In this study, 85 % of the panelists indicated that yolk color is an important attribute of the product’s quality. There was no antioxidant effect of the carotenoids in raw eggs. Synthetic additives should be better dosed to obtain the desired effect. Storage did not alter the proximate composition of the eggs

Planejamento familiar e o impacto da laqueadura na taxa de natalidade no Brasil: uma revisão sistemática : Family planning and the impact of tubal sterilization in Brazil: a systematic review

Ao se buscar compreender o desenvolvimento social brasileiro, uma variável a ser considerada são os níveis de natalidade da nossa população e os métodos de organização e planejamento das famílias brasileiras, desta maneira este tem como objetivo fazer uma análise sistemática da relação entre as taxas de natalidade e o desenvolvimento de intervenções como a laqueadura, para tal este se embasou no método de pesquisa qualitativo com ênfase no levantamento bibliográfico. Concluindo que há uma relação muito íntima entre os métodos de contracepção e a queda de natalidade média brasileira

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

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