992 resultados para leaf area index (LAI)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Microclima e características agronômicas em diferentes espaçamentos e populações na cultura do milho
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
ELPA (European Leaf Physiognomic Approach): Grid data set of environmental and ecological parameters
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Macrophytes growing in shallow coastal zones characterised by intense metabolic activity have the capacity to modify pH within their canopy and beyond. We observed diel pH changes in shallow (5-12 m) seagrass (Posidonia oceanica) meadows spanning 0.06 pH units in September to 0.24 units in June. The carbonate system (pH, DIC, and aragonite saturation state (omega Ar)) and O2 within the meadows displayed strong diel variability driven by primary productivity, and changes in chemistry were related to structural parameters of the meadow, in particular, the leaf surface area available for photosynthesis (LAI). LAI was positively correlated to mean, max and range pHNBS and max and range omega Ar. In June, vertical mixing (as Turbulent Kinetic Energy) influenced max and min omega Ar, while in September there was no effect of hydrodynamics on the carbonate system within the canopy. Max and range omega Ar within the meadow showed a positive trend with the calcium carbonate load of the leaves, pointing to a possible link between structural parameters, omega Ar and carbonate deposition.
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The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine’s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.
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Agronomic management in Ciudad Real, a province in central Spain, is characteristic of semi-arid cropped areas whose water supplies have high nitrate (NO3?) content due to environmental degradation. This situation is aggravated by the existence of a restrictive subsurface layer of ?caliche? or hardpan at a depth of 0.60 m. Under these circumstances, fertirrigation rates, including nitrogen (N) fertilizer schedules, must be carefully calibrated to optimize melon yields while minimizing the N pollution and water supply. Such optimization was sought by fertilizing with different doses of N and irrigating at 100% of the ETc (crop evapotranspiration), adjusted for this crop and area. The N content in the four fertilizer doses used was: 0, 55, 82 and 109 kg N ha?1. Due to the NO3? content in the irrigation water, however, the actual N content was 30 kg ha?1 higher in all four treatments repeated in two different years. The results showed correlation between melon plant N uptake and drainage (Dr), which in turn affects the amount of N leached, as well as correlation between Dr and LAI (leaf area index) for each treatment. A fertilizer factor (?) was estimated through two methods, from difference in Dr and in LAI ratio with respect to the maximum N dose, to correct ETc based on N doses. The difference was found in the adjusted evapotranspiration in both years using the corresponding ? achieved 42?49 mm at vegetative period, depending on the method, and it was not significant at senescent period. Finally, a growth curve between N uptake and plant dry weight (DW) for each treatment was defined to confirm that the observed higher plant vigour, showing higher LAI and reduced Dr, was due mainly to higher N doses.
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A field study in three vineyards in southern Queensland (Australia) was carried out to develop predictive models for individual leaf area and shoot leaf area of two cultivars (Cabernet Sauvignon and Shiraz) of grapevines (Vitis Vinifera L.). Digital image analysis was used to measure leaf vein length and leaf area. Stepwise regressions of untransformed and transformed models consisting of up to six predictor variables for leaf area and three predictor variables for shoot leaf area were carried out to obtain the most efficient models. High correlation coefficients were found for log10 transformed individual leaf and shoot leaf area models. The significance of predictor variables in the models varied across vineyards and cultivars, demonstrating the discontinuous and heterogeneous nature of vineyards. The application of this work in a grapevine modeling environment and in a dynamic vineyard management context are discussed. Sample sizes for quantification of individual leaf areas and areas of leaves on shoots are proposed based on target margins of errors of sampled data.
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Vegetation changes, such as shrub encroachment and wetland expansion, have been observed in many Arctic tundra regions. These changes feed back to permafrost and climate. Permafrost can be protected by soil shading through vegetation as it reduces the amount of solar energy available for thawing. Regional climate can be affected by a reduction in surface albedo as more energy is available for atmospheric and soil heating. Here, we compared the shortwave radiation budget of two common Arctic tundra vegetation types dominated by dwarf shrubs (Betula nana) and wet sedges (Eriophorum angustifolium) in North-East Siberia. We measured time series of the shortwave and longwave radiation budget above the canopy and transmitted radiation below the canopy. Additionally, we quantified soil temperature and heat flux as well as active layer thickness. The mean growing season albedo of dwarf shrubs was 0.15 ± 0.01, for sedges it was higher (0.17 ± 0.02). Dwarf shrub transmittance was 0.36 ± 0.07 on average, and sedge transmittance was 0.28 ± 0.08. The standing dead leaves contributed strongly to the soil shading of wet sedges. Despite a lower albedo and less soil shading, the soil below dwarf shrubs conducted less heat resulting in a 17 cm shallower active layer as compared to sedges. This result was supported by additional, spatially distributed measurements of both vegetation types. Clouds were a major influencing factor for albedo and transmittance, particularly in sedge vegetation. Cloud cover reduced the albedo by 0.01 in dwarf shrubs and by 0.03 in sedges, while transmittance was increased by 0.08 and 0.10 in dwarf shrubs and sedges, respectively. Our results suggest that the observed deeper active layer below wet sedges is not primarily a result of the summer canopy radiation budget. Soil properties, such as soil albedo, moisture, and thermal conductivity, may be more influential, at least in our comparison between dwarf shrub vegetation on relatively dry patches and sedge vegetation with higher soil moisture.
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Aiming to obtain empirical models for the estimation of Syrah leaf area a set of 210 fruiting shoots was randomly collected during the 2013 growing season in an adult experimental vineyard, located in Lisbon, Portugal. Samples of 30 fruiting shoots were taken periodically from the stage of inflorescences visible to veraison (7 sampling dates). At the lab, from each shoot, primary and lateral leaves were separated and numbered according to node insertion. For each leaf, the length of the central and lateral veins was recorded and then the leaf area was measured by a leaf area meter. For single leaf area estimation the best statistical models uses as explanatory variable the sum of the lengths of the two lateral leaf veins. For the estimation of leaf area per shoot it was followed the approach of Lopes & Pinto (2005), based on 3 explanatory variables: number of primary leaves and area of the largest and smallest leaves. The best statistical model for estimation of primary leaf area per shoot uses a calculated variable obtained from the average of the largest and smallest primary leaf area multiplied by the number of primary leaves. For lateral leaf area estimation another model using the same type of calculated variable is also presented. All models explain a very high proportion of variability in leaf area. Our results confirm the already reported strong importance of the three measured variables (number of leaves and area of the largest and smallest leaf) as predictors of the shoot leaf area. The proposed models can be used to accurately predict Syrah primary and secondary leaf area per shoot in any phase of the growing cycle. They are inexpensive, practical, non-destructive methods which do not require specialized staff or expensive equipment.
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Andean montane forests are one of the most diverse ecosystems on Earth, but are also highly vulnerable to climate change. Therefore, the link between plant distribution and ecosystem productivity is a critical point to investigate in these ecosystems. Are the patterns in productivity observed in montane forest due to species turnover along the elevational gradients? Methodological constraints keep this question unanswered. Also, despite their importance, belowground biomass remains poorly quantified and understood. I measured two plant functional traits in seedlings, root:shoot ratio and specific leaf area, to identify different strategies in growth and biomass allocation across elevations. A tradeoff in specific leaf area with elevation was found in only one species, and no generalized directional change was detected with elevations for root:shoot ratio. Lack of information for the ontogeny of the measured plant traits could confounding the analysis.
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The covering of the soil is an agricultural practice that intends to control the harmful herbs, to reduce the losses of water by evaporation of the soil, and to facilitate the harvest and the commercialization, once the product is cleaner and healthier. However, when the soil is covered important microclimatic parameters are also altered, and consequently the germination of seeds, the growth of roots, the absorption of water and nutrients, the metabolic activity of the plants and the carbohydrates storage. The current trial intended to evaluate the effect of soil covering with blue colored film on consumptive water-use in a lettuce crop (Lactuca sativa, L.). The experiment was carried out in a plastic greenhouse in Araras - São Paulo State, Brazil from March 3rd, 2001 to May 5th, 2001. The consumptive water-use was measured through two weighing lysimeter installed inside the greenhouse. Crop spacing was 0.25 m x 0.25 m and the color of the film above soil was blue. Leaf area index (IAF), was measured six times (7; 14; 21; 28; 35; 40 days after transplant) and the water-use efficiency (EU) was measured at the end. The experimental design was subdivided portions with two treatments, bare soil and covered soil. The average consumptive water-use was 4.17 mm day-1 to the bare soil treatment and 3.11 mm day-1 to the covered soil treatment. The final leaf area index was 25.23 to the bare soil treatment and 24.39 to the covered soil treatment, and there was no statistical difference between then.