992 resultados para leaf surface


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Plant surface areas were measured from samples of two common submersed aquatics with widely diverging morphologies: Eurasian watermilfoil ( Myriophyllum spicatum L.) and water stargrass ( Heteranthera dubia (Jacq.) MacM.). Measures for the highly dissected leaves of Eurasian watermilfoil involved development of a regression equation relating leaf length to direct measures of a subsample of leaf parts. Measures for the simple leaves of the stargrass were sums of measured triangles. Stem surfaces for both species were calculated as measured cylinders. Though the means of the stem length and leaf length were larger for stargrass samples, their mean surface area was 95 cm 2 which was less than the 108 cm 2 recorded for Eurasian watermilfoil samples. Relating surface area to dry weight for the stargrass was straightforward, with 1 mg of dry weight yielding an average 0.678 cm 2 of surface area. Biomass measures for the water milfoil were confounded by the additional weight of epiphytic algae persisting on cleaned samples. The results suggest that a lesstime consuming method for surface area measures of plants with highly dissected leaves and a caveat for using biomass measures to estimate surface area in such plants.

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We have made a comparison of (a) different surface chemistries of surface plasmon resonance (SPR) sensor chips (such as carboxymethylated dextran and carboxymethylated C1) and (b) of different assay formats (direct, sandwich and subtractive immunoassay) in order to improve the sensitivity of the determination of the model bacteria Acidovorax avenae subsp. citrulli (Aac). The use of the carboxymethylated sensor chip C1 resulted in a better sensitivity than that of carboxymethylated dextran CM5 in all the assay formats. The direct assay format, in turn, exhibits the best sensitivity. Thus, the combination of a carboxymethylated sensor chip C1 with the direct assay format resulted in the highest sensitivity for Aac, with a limit of detection of 1.6x106 CFU mL-1. This SPR immunosensor was applied to the detection of Aac in watermelon leaf extracts spiked with the bacteria, and the lower LOD is 2.2x107 CFU mL-1.

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This study was undertaken to isolate ligninase-producing white-rot fungi for use in the extraction of fibre from pineapple leaf agriwaste. Fifteen fungal strains were isolated from dead tree trunks and leaf litter. Ligninolytic enzymes (lignin peroxidase (LiP), manganese peroxidase (MnP), and laccase (Lac)), were produced by solid-state fermentation (SSF) using pineapple leaves as the substrate. Of the isolated strains, the one showing maximum production of ligninolytic enzymes was identified to be Ganoderma lucidum by 18S ribotyping. Single parameter optimization and response surface methodology of different process variables were carried out for enzyme production. Incubation period, agitation, and Tween-80 were identified to be the most significant variables through Plackett-Burman design. These variables were further optimized by Box-Behnken design. The overall maximum yield of ligninolytic enzymes was achieved by experimental analysis under these optimal conditions. Quantitative lignin analysis of pineapple leaves by Klason lignin method showed significant degradation of lignin by Ganoderma lucidum under SSF

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This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

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Canopy leaf area index (LAI), defined as the single-sided leaf area per unit ground area, is a quantitative measure of canopy foliar area. LAI is a controlling biophysical property of vegetation function, and quantifying LAI is thus vital for understanding energy, carbon and water fluxes between the land surface and the atmosphere. LAI is routinely available from Earth Observation (EO) instruments such as MODIS. However EO-derived estimates of LAI require validation before they are utilised by the ecosystem modelling community. Previous validation work on the MODIS collection 4 (c4) product suggested considerable error especially in forested biomes, and as a result significant modification of the MODIS LAI algorithm has been made for the most recent collection 5 (c5). As a result of these changes the current MODIS LAI product has not been widely validated. We present a validation of the MODIS c5 LAI product over a 121 km2 area of mixed coniferous forest in Oregon, USA, based on detailed ground measurements which we have upscaled using high resolution EO data. Our analysis suggests that c5 shows a much more realistic temporal LAI dynamic over c4 values for the site we examined. We find improved spatial consistency between the MODIS c5 LAI product and upscaled in situ measurements. However results also suggest that the c5 LAI product underestimates the upper range of upscaled in situ LAI measurements.

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 In the last decade, a vast number of land surface schemes has been designed for use in global climate models, atmospheric weather prediction, mesoscale numerical models, ecological models, and models of global changes. Since land surface schemes are designed for different purposes they have various levels of complexity in the treatment of bare soil processes, vegetation, and soil water movement. This paper is a contribution to a little group of papers dealing with intercomparison of differently designed and oriented land surface schemes. For that purpose we have chosen three schemes for classification: i) global climate models, BATS (Dickinson et al., 1986; Dickinson et al., 1992); ii) mesoscale and ecological models, LEAF (Lee, 1992) and iii) mesoscale models, LAPS (Mihailović, 1996; Mihailović and Kallos, 1997; Mihailović et al., 1999) according to the Shao et al. (1995) classification. These schemes were compared using surface fluxes and leaf temperature outputs obtained by time integrations of data sets derived from the micrometeorological measurements above a maize field at an experimental site in De Sinderhoeve (The Netherlands) for 18 August, 8 September, and 4 October 1988. Finally, comparison of the schemes was supported applying a simple statistical analysis on the surface flux outputs.

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 In the last decade, a vast number of land surface schemes has been designed for use in global climate models, atmospheric weather prediction, mesoscale numerical models, ecological models, and models of global changes. Since land surface schemes are designed for different purposes they have various levels of complexity in the treatment of bare soil processes, vegetation, and soil water movement. This paper is a contribution to a little group of papers dealing with intercomparison of differently designed and oriented land surface schemes. For that purpose we have chosen three schemes for classification: i) global climate models, BATS (Dickinson et al., 1986; Dickinson et al., 1992); ii) mesoscale and ecological models, LEAF (Lee, 1992) and iii) mesoscale models, LAPS (Mihailović, 1996; Mihailović and Kallos, 1997; Mihailović et al., 1999) according to the Shao et al. (1995) classification. These schemes were compared using surface fluxes and leaf temperature outputs obtained by time integrations of data sets derived from the micrometeorological measurements above a maize field at an experimental site in De Sinderhoeve (The Netherlands) for 18 August, 8 September, and 4 October 1988. Finally, comparison of the schemes was supported applying a simple statistical analysis on the surface flux outputs.

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The likelihood that continuing greenhouse-gas emissions will lead to an unmanageable degree of climate change [1] has stimulated the search for planetary-scale technological solutions for reducing global warming [2] (“geoengineering”), typically characterized by the necessity for costly new infrastructures and industries [3]. We suggest that the existing global infrastructure associated with arable agriculture can help, given that crop plants exert an important influence over the climatic energy budget 4 and 5 because of differences in their albedo (solar reflectivity) compared to soils and to natural vegetation [6]. Specifically, we propose a “bio-geoengineering” approach to mitigate surface warming, in which crop varieties having specific leaf glossiness and/or canopy morphological traits are specifically chosen to maximize solar reflectivity. We quantify this by modifying the canopy albedo of vegetation in prescribed cropland areas in a global-climate model, and thereby estimate the near-term potential for bio-geoengineering to be a summertime cooling of more than 1°C throughout much of central North America and midlatitude Eurasia, equivalent to seasonally offsetting approximately one-fifth of regional warming due to doubling of atmospheric CO2[7]. Ultimately, genetic modification of plant leaf waxes or canopy structure could achieve greater temperature reductions, although better characterization of existing intraspecies variability is needed first.

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Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976-1981). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was similar to 6%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage. (C) 2008 Elsevier B.V. All rights reserved.

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Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

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This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236-243, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20201

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Objetivou-se avaliar os efeitos de nitrogênio (0, 100, 200, 300 e 400 kg/ha.ano), com ou sem aplicação de calcário dolomítico em cobertura, sobre o teor de potássio (K) do solo nas profundidades de 0 a 5; 5 a 10; e 10 a 20 cm e a concentração de potássio na planta. O experimento foi realizado em Latossolo Vermelho distroférrico de relevo suavemente ondulado, disposto em esquema fatorial 5 × 2, em blocos casualizados, com quatro repetições. A adubação nitrogenada promoveu aumento linear na concentração de potássio na planta e no teor desse mineral na camada de 0 a 5 cm do solo. Ocorreu efeito de inibição competitiva entre a absorção de potássio e cálcio e entre potássio e magnésio. Embora uma fração significativa de potássio retorne à camada superficial do solo pelo resíduo de forragem, em decorrência da maior produção de massa, o aumento da concentração de potássio na planta nas mais altas doses de nitrogênio comprova a importância do suprimento de potássio para a planta, por intensificar a massa de forragem.

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O gênero Gochnatia é comumente encontrado em diferentes fitofisionomias do Cerrado do Estado de São Paulo, crescendo desde ambientes mais abertos até áreas florestais mais fechadas. Aqui foram comparadas a anatomia foliar e alguns parâmetros ecofisiológicos de duas espécies do gênero Gochnatia, uma arbustiva (Gochnatia barrosii Cabrera) e a outra arbórea (Gochnatia polymorpha (Less.) Cabrera), ambas ocorrendo em área de cerradão na Estação Ecológica de Assis, SP. Encontraram-se diferenças estruturais qualitativas entre as espécies, com G. barrosii apresentando folhas anfiestomáticas, com epiderme unisseriada e G. polymorpha apresentando folhas hipoestomáticas, com epiderme múltipla ou hipoderme, na face adaxial. Além disso, as folhas de G. barrosii apresentaram menores valores para a espessura dos tecidos (com exceção da epiderme na face abaxial) e da folha em relação a G. polymorpha. Foram observadas diferenças na assimilação de CO2 tanto em base de área quanto de massa seca foliar, além de diferenças na área foliar específica, sendo esta maior em G. barrosii. Apesar das folhas de G. barrosii possuírem estrutura bem menos escleromorfa do que as folhas de G. polymorpha, não foram encontradas diferenças na eficiência do uso de água. Os resultados sugerem que espécies de formas distintas de crescimento de um mesmo gênero possuem características foliares diferenciadas para lidar com as variações ambientais a que são submetidas.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)