Soil nitrous oxide emissions in long-term cover crops-based rotations under subtropical climate

It has been shown that cover crops can enhance soil nitrous oxide (N(2)O) emissions, but the magnitude of increase depends on the quantity and quality of the crop residues. Therefore, this study aimed to evaluate the effect of long-term (19 and 21 years) no-till maize crop rotations including grass [black oat (Avena strigosa Schreb)] and legume cover crops [vetch (Vigna sativa L), cowpea (Vigna unguiculata L. Walp), pigeon pea (Cajanus cajan L. Millsp.) and lablab (Dolichos lablab)] on annual soil N(2)O emissions in a subtropical Acrisol in Southern Brazil. Greater soil N(2)O emissions were observed in the first 45 days after the cover crop residue management in all crop rotations, varying from -20.2 +/- 1.9 to 163.9 +/- 24.3 mu g N m(-2) h(-1). Legume-based crop rotations had the largest cumulative emissions in this period, which were directly related to the quantity of N (r(2) = 0.60, p = 0.13)and inversely related to the lignin:N ratio(r(2) = 0.89,p = 0.01) of the cover crop residues. After this period, the mean fluxes were smaller and were closely related to the total soil N stocks (r(2) = 0.96, p = 0.002). The annual soil N(2)O emission represented 0.39-0.75% of the total N added by the legume cover crops. Management-control led soil variables such as mineral N (NO(3)(-) and NH(4)(+)) and dissolved organic C influenced more the N(2)O fluxes than environmental-related variables as water-filled pore space and air and soil temperature. Consequently, the synchronization between N mineralization and N uptake by plants seems to be the main challenge to reduce N(2)O emissions while maintaining the environmental and agronomic services provided by legume cover crops in agricultural systems. (C) 2009 Elsevier B.V. All rights reserved.

Host suitability of oats for Pratylenchus brachyurus

Host suitability of oats for Pratylenchus brachyurus Black oat (Avena strigosa), white oat (A. sativa) and Algerian oat (A. byzantina) are extensively cultivated in the south of Brazil for grain, forage, hay and silage production, or as cover crop in no-tillage and crop-pasture integration systems. In both systems, the genotypes of oat used as cover crop must be nonhosts or poor hosts of damaging nematodes for summer cash crops. Taking into account the relevance of Pratylenchus brachyurus as a pathogen for many cash crops in Brazil, two experiments were carried out in a glasshouse in order to evaluate the host suitability of selected oat cultivars to this nematode. The initial population inoculated (Pi) were 92 specimens/plot in experiment 1, and 270 in experiment 2. At the end of experimental periods (86 days after inoculation in experiment 1 and 67 days in experiment 2), the final population (Pf) of P. brachyurus was estimated and the reproductive factor (RF = Pf/Pi) was calculated. The results demonstrated that black oat (RF = 0.04-1.03) is more valuable than Algerian oat (RF = 2.63-2.88) or white oat (RF = 1.37-1.93) for the management of P. brachyurus.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Host Status of Graminaceous Cover Crops for Pratylenchus brachyurus

Taking into account that information about the host status of cover crops for Pratylenchus brachyurus is scarce or contradictory, this study was undertaken to assess the host status of selected graminaceous cover crops by estimating nematode reproduction and their ability to decrease the nematode density in glasshouse conditions. Furthermore, the reproductive fitness of three P. brachyurus populations was assessed for Brachiaria grasses. Silage and forage sorghum proved to be good hosts for P. brachyurus; consequently, they should be avoided in fields infested with this lesion nematode, mainly before susceptible crop such as soybean, common bean, cowpea, and cotton. Dictyoneura grass, the pearl millet cv. ADR 300, and black oat were poor hosts for P. brachyurus but may increase densities of this nematode over time. Consequently, these cover crops might be used in infested fields for only short periods, because they could increase the P. brachyurus population density slowly but progressively.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

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.

Numerical evidence against a conjecture on the cover time of planar graphs

We investigate a conjecture on the cover times of planar graphs by means of large Monte Carlo simulations. The conjecture states that the cover time tau (G(N)) of a planar graph G(N) of N vertices and maximal degree d is lower bounded by tau (G(N)) >= C(d)N(lnN)(2) with C(d) = (d/4 pi) tan(pi/d), with equality holding for some geometries. We tested this conjecture on the regular honeycomb (d = 3), regular square (d = 4), regular elongated triangular (d = 5), and regular triangular (d = 6) lattices, as well as on the nonregular Union Jack lattice (d(min) = 4, d(max) = 8). Indeed, the Monte Carlo data suggest that the rigorous lower bound may hold as an equality for most of these lattices, with an interesting issue in the case of the Union Jack lattice. The data for the honeycomb lattice, however, violate the bound with the conjectured constant. The empirical probability distribution function of the cover time for the square lattice is also briefly presented, since very little is known about cover time probability distribution functions in general.

The Amazon Frontier of Land-Use Change: Croplands and Consequences for Greenhouse Gas Emissions

The Brazilian Amazon is one of the most rapidly developing agricultural frontiers in the world. The authors assess changes in cropland area and the intensification of cropping in the Brazilian agricultural frontier state of Mato Grosso using remote sensing and develop a greenhouse gas emissions budget. The most common type of intensification in this region is a shift from single-to double-cropping patterns and associated changes in management, including increased fertilization. Using the enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, the authors created a green-leaf phenology for 2001-06 that was temporally smoothed with a wavelet filter. The wavelet-smoothed green-leaf phenology was analyzed to detect cropland areas and their cropping patterns. The authors document cropland extensification and double-cropping intensification validated with field data with 85% accuracy for detecting croplands and 64% and 89% accuracy for detecting single-and double-cropping patterns, respectively. The results show that croplands more than doubled from 2001 to 2006 to cover about 100 000 km(2) and that new double-cropping intensification occurred on over 20% of croplands. Variations are seen in the annual rates of extensification and double-cropping intensification. Greenhouse gas emissions are estimated for the period 2001-06 due to conversion of natural vegetation and pastures to row-crop agriculture in Mato Grosso averaged 179 Tg CO(2)-e yr(-1),over half the typical fossil fuel emissions for the country in recent years.

Soil carbon stocks under no-tillage mulch-based cropping systems in the Brazilian Cerrado: An on-farm synchronic assessment

No-tillage mulch-based (NTM) cropping systems have been widely adopted by farmers in the Brazilian savanna region (Cerrado biome). We hypothesized that this new type of management should have a profound impact on soil organic carbon (SOC) at regional scale and consequently on climate change mitigation. The objective of this study was thus to quantify the SOC storage potential of NTM in the oxisols of the Cerrado using a synchronic approach that is based on a chronosequence of fields of different years under NTM. The study consisted of three phases: (1) a farm/cropping system survey to identify the main types of NTM systems to be chosen for the chronosequence; (2) a field survey to identify a homogeneous set of situations for the chronosequence and (3) the characterization of the chronosequence to assess the SOC storage potential. The main NTM system practiced by farmers is an annual succession of soybean (Glycine max)or maize (Zea mays) with another cereal crop. This cropping system covers 54% of the total cultivated area in the region. At the regional level, soil organic C concentrations from NTM fields were closely correlated with clay + silt content of the soil (r(2) = 0.64). No significant correlation was observed (r(2) = 0.07), however, between these two variables when we only considered the fields with a clay + silt content in the 500-700 g kg(-1) range. The final chronosequence of NTM fields was therefore based on a subsample of eight fields, within this textural range. The SOC stocks in the 0-30 cm topsoil layer of these selected fields varied between 4.2 and 6.7 kg C m(-2) and increased on average (r(2) = 0.97) with 0.19 kg C m(-2) year(-1). After 12 years of NTM management, SOC stocks were no longer significantly different from the stocks under natural Cerrado vegetation (p < 0.05), whereas a 23-year-old conventionally tilled and cropped field showed SOC stocks that were about 30% below this level. Confirming our hypotheses, this study clearly illustrated the high potential of NTM systems in increasing SOC storage under tropical conditions, and how a synchronic approach may be used to assess efficiently such modification on farmers` fields, identifying and excluding non desirable sources of heterogeneity (management, soils and climate). (C) 2010 Elsevier B.V. All rights reserved.

Effects of land cover on chemical characteristics of streams in the Cerrado region of Brazil

The Cerrado is the second largest Brazilian biome and contains the headwaters of three major hydrological basins in Brazil. In spite of the biological and ecological relevance of this biome, there is little information about how land use changes affect the chemistry of low-order streams in the Cerrado. To evaluate these effects streams that drain areas under natural, rural, and urban land cover were sampled near Brasilia, Brazil. Water samples were collected between September 2004 and December 2006. Chemical concentrations generally followed the pattern of Urban > Rural > Natural. Median conductivity of stream water of 21.6 (interquartile: 22.7) mu S/cm in urban streams was three and five-fold greater relative to rural and natural areas, respectively. In the wet season, despite of increasing discharge, concentration of many solutes were higher, particularly in rural and natural streams. Streams also presented higher total dissolved N (TDN) loads from natural to rural and urban although DIN:DON ratios did not differ significantly. In natural and urban streams TDN was 80 and 77% dissolved organic N, respectively. These results indicate that alterations in land cover from natural to rural and urban are changing stream water chemistry in the Cerrado with increasing solute concentrations, in addition to increased TDN output in areas under urban cover, with potential effects on ecosystem function.

Runoff sources and land cover change in the Amazon: an end-member mixing analysis from small watersheds

The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end-member mixing analysis (EMMA) to 10 small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end-members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27-28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45-57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60-89% in pasture watersheds of less than 10 ha to 0% in forest and 27-28% in pastures in watersheds greater than 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.

Economic viability of doses and split-applications of nitrogen fertilization in corn crop in a eutrophic Red Latosol

Nitrogen is the nutrient that is most absorbed by the corn crop, with the most complex management, and has the highest share on the cost of corn production. The objective of this work was to evaluate the economic viability of different rates and split-applications of nitrogen fertilization, as such as urea, in the corn crop in a eutrophic Red Latosol (Oxisol). The study was carried out in the Experimental Station of the Regional Pole of the Sao Paulo Northwest Agribusiness Development (APTA), in Votuporanga, State of Sao Paulo, Brazil. The experimental design was randomized complete blocks with nine treatments and four replications, consisting of five N rates: 0, 55, 95, 135 and 175 kg ha(-1), 15 kg ha-l applied in the seeding and the remainder in top dressing: 40 and 80 kg ha(-1) N at forty days after seeding (DAS), or 1/2 + 1/2 at 20 and 40 DAS; 120 kg ha-1 N split in 1/2 + 1/2 or 1/3 + 1/3 + 1/3 at 20, 40 or 60 DAS; 160 kg ha(-1) N split in 1/4 + 3/8 + 3/8 or 114 + 1/4 + 1/4 + 1/4 at 20, 40, 60 and 80 DAS. The application of 135 kg ha-l of N split in three times provided the best benefit/cost ratio. The non-application of N provided the lowest economic return, proving to be unviable.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Leaching of nutrients from a sugarcane crop growing on an Ultisol in Brazil

Leaching is disadvantageous, both for economical and environmental reasons since it may decrease the ecosystem productivity and may also contribute to the contamination of surface and ground water. The objective of this paper was to quantify the loss of nitrogen and sulfur by leaching, at the depth of 0.9 m, in an Ultisol in Sao Paulo State (Brazil) with high permeability, Cultivated with sugarcane during the agricultural cycle of crop plant. The following ions were evaluated: nitrite, nitrate, ammonium, and sulfate. Calcium, magnesium, potassium, and phosphate were also evaluated at the same depth. The sugarcane was planted and fertilized in the furrows with 120 log ha(-1) of N-urea. In order to find out the fate of N-fertilizer, four microplots with (15)N-enriched fertilizer were installed. Input and output of the considered ions at the depth of 0.9 m were quantified from the flux density of water and the concentration of the elements in the soil solution at this soil depth: tensiometers, soil water retention curve and soil solution extractors were used for this quantification. The internal drainage was 205 mm of water, with a total loss of 18 kg ha(-1) of N and 10 kg ha(-1) of S. The percentage of N in the soil solution derived from the fertilizer (%NSSDF) was 1.34, resulting in only 25 g ha(-1) of N fertilizer loss by leaching during all agricultural cycle. Under the experimental conditions of this crop plant, that is, high demand of nutrients and high incorporation of crop residues, the leached N represented 15% of applied N and S leaching were not considerable; the higher amount of leached N was native nitrogen and a minor quantity from N fertilizer; and the leached amount of Ca, Mg, K and P did not exceed the applications performed in the crop by lime and fertilization. (C) 2009 Elsevier B.V. All rights reserved.

Estimating hourly net radiation for leaf wetness duration using the Penman-Monteith equation

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.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.