92 resultados para leaf display index

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Understanding resource capture can help design appropriate species combinations, planting designs and management. Leaf area index (LAI) and its longevity are the most important factors defining dry matter production and thus growth and productivity. The ecophysiological modifications and yield of rubber (Hevea spp.) in an agroforestry system (AFS) with beans (Phaseolus vulgaris L.) were studied. The experiment was established in Southeast-Brazil, with three rubber cultivars: IAN 3087, RRIM 600 and RRIM 527. The AFS comprised double rows of rubber trees along with beans sown in autumn and winter seasons in 1999. There was about 50% higher rubber yield per tree in the AFS than the rubber monoculture. Trees within the AFS responded to higher solar radiation availability with higher LAI and total foliage area, allowing its greater interception. All three cultivars had higher LAI in the AFS than monoculture, reaching maximum values in the AFS between April and May of 3.17 for RRIM 527; 2.83 for RRIM 600 and 2.28 for IAN 3087. The maximum LAI values for monocrop rubber trees were: 2.65, 2.62 and 1.99, respectively, for each cultivar. Rubber production and LAI were positively correlated in both the AFS and monoculture but leaf fall of rubber trees in the AFS was delayed and total phytomass was larger. It is suggested that trees in the AFS were under exploited and could yield more without compromising their life cycle if the tapping system was intensified. This shows how knowledge of LAI can be used to manage tapping intensity in the field, leading to higher rubber yield.

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The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

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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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By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

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The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

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Only 7% of the once extensive forest along the eastern coast of Brazil remains, and much of that is degraded and threatened by agricultural expansion and urbanization. We wondered if methods similar to those developed to establish fast-growing Eucalyptus plantations might also work to enhance survival and growth of rainforest species on degraded pastures composed of highly competitive C(4) grasses. An 8-factor experiment was laid out to contrast the value of different intensities of cultivation, application of fertilizer and weed control on the growth and survival of a mixture of 20 rainforest species planted at two densities: 3 m x 1 m, and 3 m x 2 m. Intensive management increased seedling survival from 90% to 98%, stemwood production and leaf area index (LAI) by similar to 4-fold, and stemwood production per unit of light absorbed by 30%. Annual growth in stem biomass was closely related to LAI alone (r(2) = 0.93, p < 0.0001), and the regression improved further in combination with canopy nitrogen content (r(2) =0.99, p < 0.0001). Intensive management resulted in a nearly closed forest canopy in less than 4 years, and offers a practical means to establish functional forests on abandoned agricultural land. (C) 2009 Elsevier B.V. All rights reserved.

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The climatic water balance is one of the most used tools to assess, indirectly the amount of water present in the soil is capable of meeting the water needs of the plant. This study analyzed the climatologic hydric balance, the effective soil water storage and coffee plant transpiration in dry regimen cultivation. Daily climatologic hydric balance was calculated for coffee from January 2003 to May 2006. It was concluded that even in the most rainy months of the year, there is a hydric deficit in coffee plants grown in a dry regimen; effective soil water storage varied greatly through the years evaluated, and September was the most critical month, when this value remained below 30%; relative transpiration can not be taken as the single evaluation method for yield losses of coffee, grown in a dry regimen.

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The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

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The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

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Eddy-covariance measurements of net ecosystem exchange of CO(2) (NEE) and estimates of gross ecosystem productivity (GEP) and ecosystem respiration (R(E)) were obtained in a 2-4 year old Eucalyptus plantation during two years with very different winter rainfall In the first (drier) year the annual NEE GEP and RE were lower than the sums in the second (normal) year and conversely the total respiratory costs of assimilated carbon were higher in the dry year than in the normal year Although the net primary production (NPP) in the first year was 23% lower than that of the second year the decrease in the carbon use efficiency (CUE = NPP/GEP) was 11% and autotrophic respiration utilized more resources in the first dry year than in the second normal year The time variations in NEE were followed by NPP because in these young Eucalyptus plantations NEE is very largely dominated by NPP and heterotrophic respiration plays only a relatively minor role During the dry season a pronounced hysteresis was observed in the relationship between NEE and photosynthetically active radiation and NEE fluxes were inversely proportional to humidity saturation deficit values greater than 0 8 kPa Nighttime fluxes of CO(2) during calm conditions when the friction velocity (u) was below the threshold (0 25 ms(-1)) were estimated based on a Q(10) temperature-dependence relationship adjusted separately for different classes of soil moisture content which regulated the temperature sensitivity of ecosystem respiration (C) 2010 Elsevier B V All rights reserved

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Tibouchina pulchra saplings were exposed to carbon filtered air (CF), ambient non-filtered air (NF) and ambient non-filtered air + 40 ppb ozone (NF + O-3) 8 h per day during two months. The AOT40 values at the end of the experiment were 48, 910 and 12,895 ppb h(-1), respectively, for the three treatments. After 25 days of exposure (AOT40=3871 ppb h(-1)), interveinal red stippling appeared in plants in the NF + O-3 chamber. In the NF chamber, symptoms were observed only after 60 days of exposure (AOT40 = 910 ppb h(-1)). After 60 days, injured leaves per plant corresponded to 19% in NF + O-3 and 1% in the NF treatment; and the average leaf area injured was 7% within the NF + O-3 and 0.2% within the NF treatment. The extent of leaf area injured (leaf injury index) was mostly explained by the accumulated exposure of ozone (r(2) = 0.89; p < 0.05). (C) 2007 Elsevier Ltd. All rights reserved.

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Psidium guajava ""Paluma"", a tropical tree species, is known to be an efficient ozone indicator in tropical countries. When exposed to ozone, this species displays a characteristic leaf injury identified by inter-veinal red stippling on adaxial leaf surfaces. Following 30 days of three ozone treatments consisting of carbon filtered air (CF - AOT40 = 17 ppb h), ambient non-filtered air (NF - AOT40 = 542 ppb h) and ambient non-filtered air + 40 ppb ozone (NF + O(3) - AOT40 - 7802 ppb h), the amounts of residual anthocyanins and tannins present in 10 P. guajava (""Paluma"") saplings were quantified. Higher amounts of anthocyanins were found in the NF + O(3) treatment (1.6%) when compared to the CF (0.97%) and NF (1.30%) (p < 0.05), and of total tannins in the NF + O(3) treatment (0.16%) compared to the CIF (0.14%). Condensed tannins showed the same tendency as enhanced amounts. Regression analyses using amounts of tannins and anthocyanins, AOT40 and the leaf injury index (LII), showed a correlation between the leaf injury index and quantities of anthocyanins and total tannins. These results are in accordance with the association between the incidence of red-stippled leaves and ozone polluted environments. (C) 2009 Elsevier Ltd. All rights reserved.

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Shot peening is a cold-working mechanical process in which a shot stream is propelled against a component surface. Its purpose is to introduce compressive residual stresses on component surfaces for increasing the fatigue resistance. This process is widely applied in springs due to the cyclical loads requirements. This paper presents a numerical modelling of shot peening process using the finite element method. The results are compared with experimental measurements of the residual stresses, obtained by the X-rays diffraction technique, in leaf springs submitted to this process. Furthermore, the results are compared with empirical and numerical correlations developed by other authors.

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The characterization of a coffee gene encoding a protein similar to miraculin-like proteins, which are members of the plant Kunitz serine trypsin inhibitor (STI) family of proteinase inhibitors (PIs), is described. PIs are important proteins in plant defence against insects and in the regulation of proteolysis during plant development. This gene has high identity with the Richadella dulcifica taste-modifying protein miraculin and with the tomato protein LeMir; and was named as CoMir (Coffea miraculin). Structural protein modelling indicated that CoMir had structural similarities with the Kunitz STI proteins, but suggested specific folding structures. CoMir was up-regulated after coffee leaf miner (Leucoptera coffella) oviposition in resistant plants of a progeny derived from crosses between C. racemosa (resistant) and C. arabica (susceptible). Interestingly, this gene was down-regulated during coffee leaf miner herbivory in susceptible plants. CoMir expression was up-regulated after abscisic acid application and wounding stress and was prominent during the early stages of flower and fruit development. In situ hybridization revealed that CoMir transcripts accumulated in the anther tissues that display programmed cell death (tapetum, endothecium and stomium) and in the metaxylem vessels of the petals, stigma and leaves. In addition, the recombinant protein CoMir shows inhibitory activity against trypsin. According to the present results CoMir may act in proteolytic regulation during coffee development and in the defence against L. coffeella. The similarity of CoMir with other Kunitz STI proteins and the role of CoMir in plant development and plant stress are discussed.

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Leaf wetness duration (LWD) is related to plant disease occurrence and is therefore a key parameter in agrometeorology. As LWD is seldom measured at standard weather stations, it must be estimated in order to ensure the effectiveness of warning systems and the scheduling of chemical disease control. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results for operational use. However, the requirement of net radiation (Rn) is a disadvantage foroperational physical models, since this variable is usually not measured over crops or even at standard weather stations. With the objective of proposing a solution for this problem, this study has evaluated the ability of four models to estimate hourly Rn and their impact on LWD estimates using a Penman-Monteith approach. A field experiment was carried out in Elora, Ontario, Canada, with measurements of LWD, Rn and other meteorological variables over mowed turfgrass for a 58 day period during the growing season of 2003. Four models for estimating hourly Rn based on different combinations of incoming solar radiation (Rg), airtemperature (T), relative humidity (RH), cloud cover (CC) and cloud height (CH), were evaluated. Measured and estimated hourly Rn values were applied in a Penman-Monteith model to estimate LWD. Correlating measured and estimated Rn, we observed that all models performed well in terms of estimating hourly Rn. However, when cloud data were used the models overestimated positive Rn and underestimated negative Rn. When only Rg and T were used to estimate hourly Rn, the model underestimated positive Rn and no tendency was observed for negative Rn. The best performance was obtained with Model I, which presented, in general, the smallest mean absolute error (MAE) and the highest C-index. When measured LWD was compared to the Penman-Monteith LWD, calculated with measured and estimated Rn, few differences were observed. Both precision and accuracy were high, with the slopes of the relationships ranging from 0.96 to 1.02 and R-2 from 0.85 to 0.92, resulting in C-indices between 0.87 and 0.93. The LWD mean absolute errors associated with Rn estimates were between 1.0 and 1.5h, which is sufficient for use in plant disease management schemes.