918 resultados para Intensive and extensive margin
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Includes bibliography
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The aim of this study was to estimate the effect of the association between carrot and lettuce crops in several intercropping systems through different yield advantage indexes, as well as to assess which system is better for the environmental resources management with respect to productivity and economic indicators. A 'group balanced block' experimental design was used, with four replications. Cultivars of lettuce crispleaf ('Lucy Brown', 'Tainá', 'Laurel' and 'Verônica') and looseleaf ('Babá de Verão', 'Maravilha das Quatro Estações', 'Elisa' and 'Carolina') groups were evaluated in intercropping systems with 'Alvorada' and 'Brasilia' carrot cultivars. The land equivalent ratio (LER) and yield efficiency index (YEI) were estimated, besides economic indicators such as gross (GI) and net (NI) income, modified monetary advantage (MMA), return rate (RR) and profit margin (PM). The evaluated indexes showed that carrot is the dominant and lettuce the dominated crop. Higher biological/agronomic efficiency indexes and economic indicators were observed in intercropping systems with 'Brasilia' carrot as component crop and that based on the crispleaf lettuce group.
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Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Ciências Biológicas (Botânica) - IBB
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Medicina Veterinária - FMVZ
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)