Cultivares de batata para sistemas orgânicos de produção.

Informações a respeito de cultivares adaptadas ao sistema de cultivo orgânico são escassas. O objetivo deste estudo foi avaliar, sob sistema de cultivo orgânico, genótipos nacionais e estrangeiros desenvolvidos para o cultivo convencional, quanto ao potencial produtivo, em condições de campo. O experimento foi conduzido em 2008, no Pólo APTA Leste Paulista, em Monte Alegre do Sul-SP. O delineamento experimental foi em blocos ao acaso, com 18 tratamentos e quatro repetições. Cada parcela foi constituída por 80 batatas-semente, dispostas em quatro linhas de 5 m de comprimento, espaçadas de 80 cm, com 25 cm entre tubérculos. Os genótipos avaliados foram Agata, Asterix, Caesar, Cupido, Éden, Melody, Novella e Vivaldi, de origem estrangeira; e Apuã, Aracy, Catucha, IAC Aracy Ruiva, Itararé, Monte Alegre 172, IAC 6090, APTA 16.5, APTA 15.20 e APTA 21.54, nacionais. Foram avaliadas as características de produtividade total e comercial de tubérculos, massa média total e comercial de tubérculos, teor de matéria seca e severidade da pinta-preta (Alternaria solani). Os clones APTA 16.5, APTA 21.54 e IAC 6090, e as cultivares Cupido, Apuã, Itararé e Monte Alegre 172 foram os mais produtivos. ‘APTA 21.54’ superou os demais em relação a produtividade comercial (18,07 t ha-1), sendo que ‘APTA 16.5’, ‘Cupido’, ‘IAC 6090’ e ‘Itararé’ formaram o segundo grupo. As maiores massas médias de tubérculos foram apresentadas pelas cultivares Itararé e Cupido. O clone IAC 6090 e as cultivares Aracy e Aracy Ruiva foram as que apresentaram maiores teores de matéria seca, com valor médio de 22,91%. ‘APTA 16.5’, ‘Apuã’, ‘Aracy’, ‘Aracy Ruiva’, ‘Éden’, ‘Ibituaçú’ e ‘Monte Alegre 172’ apresentaram alto nível de resistência à pinta-preta. As cultivares Itararé, Apuã e Cupido são adaptadas ao cultivo orgânico, e os clones avançados APTA 16.5, APTA 21.54 e IAC 6090 apresentam potencial de cultivo no sistema orgânico

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

Agricultural Trade Liberalization: Policies and Implications for Latin America

This book investigates key issues in regard to liberalization of agricultural trade in the Western Hemisphere, including potential scenarios for liberalization at the regional and multilateral levels, the effects of U.S. and European Union agricultural policies on trade, and how a Free Trade Area of the Americas and a European Union-MERCOSUR trade agreement might affect agricultural trade flows. It also examines agricultural liberalization in the U.S.-Central America Free Trade Agreement and suggests a food security typology for use by the World Trade Organization.

Comparação das informações sobre as prevalências de doenças crônicas obtidas pelo suplemento saúde da PNAD/98 e as estimadas pelo estudo Carga de Doença no Brasil Comparison of the information on prevalences of chronic diseases obtained by the health suplement of PNAD/98 and the estimated ones by the study Burden of Disease in Brazil

Neste estudo, estimativas de prevalência de cinco doenças crônicas &shy; cirrose, depressão, diabetes, insuficiência renal crônica e tuberculose &shy; obtidas pelo Suplemento Saúde da PNAD/98 foram comparadas com as obtidas no Projeto Carga Global de Doença no Brasil. Essas estimativas foram baseadas em análise sistemática de literatura e banco de dados de morbidade disponíveis. Os resultados mostram que a PNAD apresentou número de casos mais elevados para depressão e insuficiência renal crônica, enquanto as estimativas do Projeto Carga de Doença no Brasil apresentou maiores prevalências para cirrose, diabetes e tuberculose.<br>In this study, prevalence estimates of five chronic disease cirrhosis, depression, diabetes, chronic rhenal insufficiency and tuberculosis based on the 1998 PNAD Health Supplement were compared to those obtained by the Brazilian Global Burden of Disease Project. These estimates were based on systematic literature review as well as on available data set of morbidities. The results show that PNAD presented higher number of cases for depression and Chronic rhenal insufficiency while the prevalence rates estimated by Brazilian Global Burden of Disease Project were higher for cirrhosis, diabetes and tuberculosis