Poultry litter and pig slurry applications in an integrated crop-livestock system.

2016

Soil carbon stock in integrated crop-livestock-forest system in the Central Region of Minas Gerais.

2016

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

Cover Crops and Nitrogen Fertilization Effects on Nitrogen Soil Fractions under Corn Cultivation in a No-Tillage System.

ABSTRACT: The use of cover crops has recently increased and represents an essential practice for the sustainability of no-tillage systems in the Cerrado region. However, there is little information on the effects of nitrogen fertilization and cover crop use on nitrogen soil fractions. This study assessed changes in the N forms in soil cropped to cover crops prior to corn growing. The experiment consisted of a randomized complete block design arranged in split-plots with three replications. Cover crops were tested in the plots, and the N topdressing fertilization was assessed in the subplots. The following cover species were planted in succession to corn for eight years: Urochloa ruziziensis, Canavalia brasiliensis M. ex Benth, Cajanus cajan (L.) Millsp, and Sorghum bicolor (L.) Moench. After corn harvesting, the soil was sampled at depths of 0.00-0.10 and 0.10-0.20 m. The cover crops showed different effects at different soil depths. The soil cultivated with U. ruziziensis showed higher contents of total-N and particulate-N than the soil cultivated with C. cajan. Particulate-N was the most sensitive to changes in the soil management among the fractions of N assessed. The soil under N topdressing showed a lower content of available-N in the 0.10-0.20 m layer, which may be caused by the season in which the sampling was conducted or the greater uptake of the available-N by corn.

Effects of row spacing and nitrogen topdressing fertilization on the yield of upland rice in a no-tillage system.

This study aimed to evaluate the effect of row spacing and nitrogen topdressing fertilization of two materials (genotype 07SEQCL441 CL and cultivar BRS Esmeralda) on the plant height, yield components, grain yield, and quality of an upland rice crop grown in a no-tillage system. Trials were conducted for two growing seasons under field conditions in a 3 x 4 factorial, randomized, complete block design, with four replications. For each material, treatments consisted of the combination of row spacing (0.225, 0.35, and 0.45 m) with nitrogen (N) applied as topdressing (0, 50, 100, and 150 kg ha-1). The lowest row spacing (0.225 m) for genotypes 07SEQCL441 CL and BRS Esmeralda provided a higher number of tillers, number of panicles m-2, and grain yield of rice. Increasing rates of N in the topdressing improved the rice grain yield for both cultivars, but for 07SEQCL441 CL, the grain yield was positively affected only to applications up to 50 kg N ha-1. Row spacing and N rates did not affect the rice grain quality. Therefore, these results indicate that the narrowest row spacing used (0.225 m) with N fertilization as topdressing increased the rice grain yield most in the no-tillage system.