Relationship between sweet orange yield and intensity of Citrus Variegated Chlorosis

Citrus Variegated Chlorosis (CVC) is currently present in approximately 40% of citrus plants in Brazil and causes an annual loss of around 120 million US dollars to the Brazilian citrus industry. Despite the fact that CVC has been present in Brazil for over 20 years, a relationship between disease intensity and yield loss has not been established. In order to achieve this, an experiment was carried out in a randomized block design in a 3 x 2 factorial scheme with 10-year-old Natal sweet orange. The following treatments were applied: irrigation with 0, 50 or 100% of the evapotranspiration of the crop, combined with natural infection or artificial inoculation with Xylella fastidiosa, the causal agent of CVC. The experiment was evaluated during three seasons. A negative exponential model was fitted to the relationships between yield versus CVC severity and yield versus Area Under Disease Progress Curve (AUDPC). In addition, the relationship between yield versus CVC severity and canopy volume was fitted by a multivariate exponential model. The use of the AUDPC variable showed practical limitations when compared with the variable CVC severity. The parameter values in the relationship of yieldCVC severity were similar for all treatments unlike in the multivariate model. Consequently, the yieldCVC intensity relationship (with 432 data points) could be described by one single model: y = 114.07 exp(-0.017 x), where y is yield (symptomless fruit weight in kg) and x is disease severity (R2 = 0.45; P < 0.01).

Geochronological constraints on the age of a Permo-Triassic impact event: U-Pb and Ar-40/Ar-39 results for the 40 km Araguainha structure of central Brazil

Impact cratering has been a fundamental geological process in Earth history with major ramifications for the biosphere. The complexity of shocked and melted rocks within impact structures presents difficulties for accurate and precise radiogenic isotope age determination, hampering the assessment of the effects of an individual event in the geological record. We demonstrate the utility of a multi-chronometer approach in our study of samples from the 40 km diameter Araguainha impact structure of central Brazil. Samples of uplifted basement granite display abundant evidence of shock deformation, but U/Pb ages of shocked zircons and the Ar-40/Ar-39 ages of feldspar from the granite largely preserve the igneous crystallization and cooling history. Mixed results are obtained from in situ Ar-40/Ar-39 spot analyses of shocked igneous biotites in the granite, with deformation along kink-bands resulting in highly localized, partial resetting in these grains. Likewise, spot analyses of perlitic glass from pseudotachylitic breccia samples reflect a combination of argon inheritance from wall rock material, the age of the glass itself, and post-impact devitrification. The timing of crater formation is better assessed using samples of impact-generated melt rock where isotopic resetting is associated with textural evidence of melting and in situ crystallization. Granular aggregates of neocrystallized zircon form a cluster of ten U-Pb ages that yield a "Concordia" age of 247.8 +/- 3.8 Ma. The possibility of Pb loss from this population suggests that this is a minimum age for the impact event. The best evidence for the age of the impact comes from the U-Th-Pb dating of neocrystallized monazite and Ar-40/Ar-39 step heating of three separate populations of post-impact, inclusion-rich quartz grains that are derived from the infill of miarolitic cavities. The Pb-206/U-238 age of 254.5 +/- 3.2 Ma (2 sigma error) and Pb-208/Th-232 age of 255.2 +/- 4.8 Ma (2 sigma error) of monazite, together with the inverse, 18 point isochron age of 254 +/- 10 Ma (MSWD = 0.52) for the inclusion-rich quartz grains yield a weighted mean age of 254.7 +/- 2.5 Ma (0.99%, 2 sigma error) for the impact event. The age of the Araguainha crater overlaps with the timing of the Permo-Triassic boundary, within error, but the calculated energy released by the Araguainha impact is insufficient to be a direct cause of the global mass extinction. However, the regional effects of the Araguainha impact event in the Parana-Karoo Basin may have been substantial. (C) 2012 Elsevier Ltd. All rights reserved.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

Interpolation estimate for a finite-element space with embedded discontinuities

We consider a recently proposed finite-element space that consists of piecewise affine functions with discontinuities across a smooth given interface Γ (a curve in two dimensions, a surface in three dimensions). Contrary to existing extended finite element methodologies, the space is a variant of the standard conforming Formula space that can be implemented element by element. Further, it neither introduces new unknowns nor deteriorates the sparsity structure. It is proved that, for u arbitrary in Formula, the interpolant Formula defined by this new space satisfies Graphic where h is the mesh size, Formula is the domain, Formula, Formula, Formula and standard notation has been adopted for the function spaces. This result proves the good approximation properties of the finite-element space as compared to any space consisting of functions that are continuous across Γ, which would yield an error in the Formula-norm of order Graphic. These properties make this space especially attractive for approximating the pressure in problems with surface tension or other immersed interfaces that lead to discontinuities in the pressure field. Furthermore, the result still holds for interfaces that end within the domain, as happens for example in cracked domains.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.