10 resultados para Climate Leaf Analysis Multivariate Program (CLAMP)


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This paper presents the evaluation of qualitative and quantitative characteristics of 63 accessions of the sapodilla collection held in CATTE, Costa Rica. Cluster analysis of data indicated six distinct groups with 15, 14, 8, 8, 15 and 3 trees, respectively. Canonic discriminant analysis and F and X2 tests detected the variables most affecting group differentiation. These were reducing sugars, fruit acidity, fruit and seed length, sucrose, pH, fruit diameter, fruit weight, Brix degrees, total sugar content, total solid content, proteins, carbohydrates, leaf length and width, branch architecture, fructification distribution, fruit production, flowering and fruiting season, The origin of the materiais is related to the classifications obtained.

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The seasonal climate drivers of the carbon cy- cle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combina- tion of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measure- ments and 35 litter productivity measurements), their asso- ciated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonal- ity in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rain- fall is < 2000 mm yr-1 (water-limited forests) and to radia- tion otherwise (light-limited forests). On the other hand, in- dependent of climate limitations, wood productivity and lit- terfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosyn- thetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest pro- ductivity in a drier climate in water-limited forest, and in cur- rent light-limited forest with future rainfall < 2000 mm yr-1.

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A cultura da banana tem baixa diversidade genética, tornando a espécie susceptível a doenças dizimadoras como a Sigatoka negra. No entanto, a adoção de novas variedades necessita de avaliações agronômicas e físico-químicas. Neste estudo, as variedades de banana, resistentes à Sigatoka negra, foram caracterizadas e comparadas com a variedade tradicional (Grand Naine). Cada variedade foi avaliada considerando-se critérios relevantes para a agroindústria, como pH, sólidos solúveis totais, acidez total titulável, relação SST/ATT, açúcares totais, açúcares redutores e não redutores, umidade, sólidos totais e rendimento no processamento. A variedade Thap Maeo apresentou-se como a variedade mais potencial para substituição da Gran Naine na indústria, com altos teores de sólidos solúveis totais, açúcares redutores, açúcares totais e umidade. As variedades Caipira e FHIA 2 também podem substituir a Grand Naine. Na análise de agrupamentos, verificou-se que a variedade Grand Naine esteve muito próxima das variedades do subgrupo Gros Michel (Bucaneiro, Ambroisa e Calipso) e também da variedade Caipira, apresentando no seu genoma o grupo AAA. Conclui-se que há opções de variedades resistentes para substituição da variedade tradicional, nas regiões afetadas pela Sigatoka-negra.

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Clustering data streams is an important task in data mining research. Recently, some algorithms have been proposed to cluster data streams as a whole, but just few of them deal with multivariate data streams. Even so, these algorithms merely aggregate the attributes without touching upon the correlation among them. In order to overcome this issue, we propose a new framework to cluster multivariate data streams based on their evolving behavior over time, exploring the correlations among their attributes by computing the fractal dimension. Experimental results with climate data streams show that the clusters' quality and compactness can be improved compared to the competing method, leading to the thoughtfulness that attributes correlations cannot be put aside. In fact, the clusters' compactness are 7 to 25 times better using our method. Our framework also proves to be an useful tool to assist meteorologists in understanding the climate behavior along a period of time.

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In a study of the vanadyl (VO2þ)-humic acids system, the residual vanadyl ion suppressed fluorescence and specific electron paramagnetic resonance (EPR) and NMR signals. In the case of NMR, the proton rotating frame relaxation times (T1qH) indicate that this suppression is due to an inefficient H-C cross polarization, which is a consequence of a shortening of T1qH. Principal components analysis (PCA) facilitated the isolation of the effect of the VO2þ ion and indicated that the organic free radical signal was due to at least two paramagnetic centres and that the VO2þ ion preferentially suppressed the species whose electronic density is delocalized over O atoms (greater g-factor). additionally, the newly obtained variables (principal components ? PC) indicated that, as the result of the more intense tillage a relative increase occurred in the accumulation of: (i) recalcitrant structures; (ii) lignin and long-chain alkyl structures; and (iii) organic free radicals with smaller g-factors.