Upland and lowland rice cultivar agronomic traits, cooking and processing characteristics

Diversas cultivares e progênies-elite de arroz de sequeiro e irrigado foram testadas quanto a várias características agronômicas e parâmetros de qualidade do produto, durante os anos agrícolas de 1982/83 e 1983/84. A cultivar IAC-165 e as progênies IAC-233 e IAC-150 sobressaíram-se quanto ao potencial e estabilidade de produção de grãos, dentre os materiais genéticos de arroz de sequeiro em estudo. A progênie IAC-150 mostrou-se especialmente adequada para o processamento industrial, em virtude dos bons níveis alcançados para várias características de qualidade de produto (razões de aumento de peso e de volume, gelatinização, viscosidade a quente e “set-back”). A cultivar de arroz irrigado IAC-4440 apresentou excelente potencial e estabilidade produtiva, aliados à elevada resistência à brusone e alto rendimento de grãos inteiros, revelando também ser de cocção muito rápida e com boa soltura de grifos após o cozimento e resfriamento, o que a recomenda para o consumo in natura. Outros materiais, tanto de arroz de sequeiro como irrigado, mostraram bons níveis para alguns parâmetros de qualidade, podendo servir como fontes de genes para a melhoria daquelas características em futuros programas de melhoramento genético.Upland and lowland rice cultivars and selected progenies have been evaluated as to their yielding stability and potential, several agronomic traits as well as to cooking and processing characteristics in agronomic years 1982/83 and 1983/84. Among the upland rice materials under testing, the cultivar IAC-165 and the progenies IAC-233 and IAC-150 have shown reasonable yielding potentials. The latter has also revealed good proportional increases in volume and weight, low gelatinization, high values for peak hot-paste viscosity and an excellent “set back”. Those features make IAC-150 quite adequate for processing purposes, e.g., parboiled or canned rice. The lowland cultivar IAC-4440 has significantly outyielded the other lowland rice materials in grain production, showing a marked yielding stability and leaf blast resistance. It has also attained high levels for peak hot-paste and cold viscosities, which make it proper for in natura consumption. Other upland and lowland rice materials have also presented good levels for certain cooking and processing characteristics and can be used in future breeding programs as gene sources for those specific attributes

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

Influência da secagem à alta temperatura nas características das massas com ovos

Dois processos de alta temperatura foram empregados na secagem de macarrão com ovos e comparados com o processo convencional. Em um dos processos, a temperatura elevada foi aplicada na fase inicial da secagem e no outro, na fase final. Os resultados obtidos mostraram que os produtos secos à alta temperatura apresentaram cor mais clara, maior resistência à mastigação e menor gomosidade que o seco pelo processo convencional. Os processos de alta temperatura proporcionaram ainda menor perda de sólidos solúveis durante o cozimento. O teor de lisina disponível de cada massa foi avaliado antes e após secagem. A alta temperatura, principalmente quando aplicada na fase inicial da secagem, propiciou perdas de lisina disponível bem superiores às encontradas para o processo convencional. Quanto às análises microbiológicas, os três processos estudados apresentaram resultados semelhantes

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved