Efficiency of nitrogen sources and rates on growth and dry matter yield of tifton 85

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Manejo de minimelancia cultivada em fibra da casca de coco, sob ambiente protegido

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

Regeneração natural sob talhões puros de espécies nativas com diferentes atributos funcionais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Manejo de minimelancia cultivada em fibra da casca de coco, sob ambiente protegido

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

Regeneração natural sob talhões puros de espécies nativas com diferentes atributos funcionais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effects of irrigation on water use and water use efficiency in two fast growing Eucalyptus plantations

Eucalyptus plantations occupy almost 20 million ha worldwide and exceed 3.7 million ha in Brazil alone. Improved genetics and silviculture have led to as much as a three-fold increase in productivity in Eucalyptus plantations in Brazil and the large land area occupied by these highly productive ecosystems raises concern over their effect on local water supplies. As part of the Brazil Potential Productivity Project, we measured water use of Eucalyptus grandis x urophylla clones in rainfed and irrigated stands in two plantations differing in productivity. The Aracruz (lower productivity) site is located in the state of Espirito Santo and the Veracel (higher productivity) site in Bahia state. At each plantation, we measured stand water use using homemade sap flow sensors and a calibration curve using the clones and probes we utilized in the study. We also quantified changes in growth, leaf area and water use efficiency (the amount of wood produced per unit of water transpired). Measurements were conducted for 1 year during 2005 at Aracruz and from August through December 2005 at Veracel. Transpiration at both sites was high compared to other studies but annual estimates at Aracruz for the rainfed treatment compared well with a process model calibrated for the Aracruz site (within 10%). Annual water use at Aracruz was 1394 mm in rainfed treatments versus 1779 mm in irrigated treatments and accounted for approximately 67% and 58% of annual precipitation and irrigation inputs respectively. Increased water use in the irrigated stands at Aracruz was associated with higher sapwood area, leaf area index and transpiration per unit leaf area but there was no difference in the response of canopy conductance with air saturation deficit between treatments. Water use efficiency at the Aracruz site was also not influenced by irrigation and was similar to the rainfed treatment. During the period of overlapping measurements, the response to irrigation treatments at the more productive Veracel site was similar to Aracruz. Stand water use at the Veracel site totaled 975 mm and 1102 mm in rainfed and irrigated treatments during the 5-month measurement period respectively. Irrigated stands at Veracel also had higher leaf area with no difference in the response of canopy conductance with air saturation deficit between treatments. Water use efficiency was also unaffected by irrigation at Veracel. Results from this and other studies suggest that improved resource availability does not negatively impact water use efficiency but increased productivity of these plantations is associated with higher water use and should be given consideration during plantation management decision making processes aimed at increasing productivity. Published by Elsevier B.V.

Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil

Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

STRUCTURAL CHARACTERIZATION OF CANOPIES OF Eucalyptus spp. USING RADIOMETRIC DATA FROM TM/Landsat 5

Empirical approaches and, more recently, physical approaches, have grounded the establishment of logical connections between radiometric variables derived from remote data and biophysical variables derived from vegetation cover. This study was aimed at evaluating correlations of dendrometric and density data from canopies of Eucalyptus spp., as collected in Capao Bonito forest unit, with radiometric data from imagery acquired by the TM/Landsat-5 sensor on two orbital passages over the study site (dates close to field data collection). Results indicate that stronger correlations were identified between crown dimensions and canopy height with near-infrared spectral band data (rho(s)4), irrespective of the satellite passage date. Estimates of spatial distribution of dendrometric data and canopy density (D) using spectral characterization were consistent with the spatial distribution of tree ages during the study period. Statistical tests were applied to evaluate performance disparities of empirical models depending on which date data were acquired. Results indicated a significant difference between models based on distinct data acquisition dates.

Parametrização e avaliação do modelo DSSAT/Canegro para variedades brasileiras de cana-de-açúcar

O objetivo deste trabalho foi parametrizar e avaliar o modelo DSSAT/Canegro para cinco variedades brasileiras de cana-de-açúcar. A parametrização foi realizada a partir do uso de dados biométricos e de crescimento das variedades CTC 4, CTC 7, CTC 20, RB 86-7515 e RB 83-5486, obtidos em cinco localidades brasileiras. Foi realizada análise de sensibilidade local para os principais parâmetros. A parametrização do modelo foi feita por meio da técnica de estimativa da incerteza de probabilidade generalizada ("generalized likelihood uncertainty estimation", Glue). Para a avaliação das predições, foram utilizados, como indicadores estatísticos, o coeficiente de determinação (R2), o índice D de Willmott e a raiz quadrada do erro-médio (RMSE). As variedades CTC apresentaram índice D entre 0,870 e 0,944, para índice de área foliar, altura de colmo, perfilhamento e teor de sacarose. A variedade RB 83-5486 apresentou resultados similares para teor de sacarose e massa de matéria fresca do colmo, enquanto a variedade RB 86-7515 apresentou valores entre 0,665 e 0,873, para as variáveis avaliadas.

Vertical growth of mini watermelon according to the training height and plant density

The watermelon is traditionally cultivated horizontally on the ground. The cultivars of small fruits (1 to 3 kg), which reach better market prices, are also being grown in a greenhouse, where the plants are trained upward on vertical supports, with branches pruning and fruits thinning. These practices make possible an increase of the plant density, fruit quality and yield compared to the traditional growth system. The aim of this experiment was to evaluate the influence of three training heights (1.7, 2.2 and 2.7 m) and two planting densities (3.17 and 4.76 plants m-2) over the productive and qualitative characteristics of mini watermelon "Smile" cultivated in greenhouse. The pruning was done at 43, 55 and 66 days after transplanting (DAT), when the plant height reached 1.7, 2.2 and 2.7 m, respectively. The dry mass of branches, petioles, leaves and total were affected by the training height, where the highest values were obtained by the plants pruned at 2.2 and 2.7 m. Leaf area, specific leaf area and leaf area index were not affected by the height of the plants. The training height of 2.7 m raised the total yield, however, marketable yield, average fruit mass and all the quality characteristics did not differ significantly from those obtained by the training height of 2.2 m. Regarding to plant density, the best option was 4.76 plants m-2, due to the increasing of marketable yield in 37.4% without reducing the average weight of fruits.

Assessing biophysical variable parameters of bean crop with hyperspectral measurements

Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.

Modified crop model estimation of depleted and potential soybean yield

Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.

Estimativa do índice de área foliar e temperatura em uma área de eucalipto

It is known that the presence of large masses of vegetation is a factor that can influence the microclimate of a region. In this paper we analyzed the correlation between leaf area index (LAI) and land surface temperature (LST), both estimated from remote sensing images from Landsat-5 TM in an area of eucalyptus plantation, and these estimates were compared to the observed data. The correlation between LAI and LST was not significant (16%), which indicates that there is no necessarily a direct influence of vegetation in the local temperature. The comparison between estimated and observed data shows that the application of remote sensing techniques in the estimative of interested variables is efficient, because the estimatives followed consistently the observed values.

Carbon fluxes and allocation pattern in an apple orchard

Carbon fluxes and allocation pattern, and their relationship with the main environmental and physiological parameters, were studied in an apple orchard for one year (2010). I combined three widely used methods: eddy covariance, soil respiration and biometric measurements, and I applied a measurement protocol allowing a cross-check between C fluxes estimated using different methods. I attributed NPP components to standing biomass increment, detritus cycle and lateral export. The influence of environmental and physiological parameters on NEE, GPP and Reco was analyzed with a multiple regression model approach. I found that both NEP and GPP of the apple orchard were of similar magnitude to those of forests growing in similar climate conditions, while large differences occurred in the allocation pattern and in the fate of produced biomass. Apple production accounted for 49% of annual NPP, organic material (leaves, fine root litter, pruned wood and early fruit drop) contributing to detritus cycle was 46%, and only 5% went to standing biomass increment. The carbon use efficiency (CUE), with an annual average of 0.68 ± 0.10, was higher than the previously suggested constant values of 0.47-0.50. Light and leaf area index had the strongest influence on both NEE and GPP. On a diurnal basis, NEE and GPP reached their peak approximately at noon, while they appeared to be limited by high values of VPD and air temperature in the afternoon. The proposed models can be used to explain and simulate current relations between carbon fluxes and environmental parameters at daily and yearly time scale. On average, the annual NEP balanced the carbon annually exported with the harvested apples. These data support the hypothesis of a minimal or null impact of the apple orchard ecosystem on net C emission to the atmosphere.