Influência da estrutura de corantes azo na cinética de degradação por processo foto-Feton e ferro zero e na toxicidade

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

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).

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.

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.

Modeling Yield Surfaces of Various Structural Shapes

This study investigates the possibility of custom fitting a widely accepted approximate yield surface equation (Ziemian, 2000) to the theoretical yield surfaces of five different structural shapes, which include wide-flange, solid and hollow rectangular, and solid and hollow circular shapes. To achieve this goal, a theoretically “exact” but overly complex representation of the cross section’s yield surface was initially obtained by using fundamental principles of solid mechanics. A weighted regression analysis was performed with the “exact” yield surface data to obtain the specific coefficients of three terms in the approximate yield surface equation. These coefficients were calculated to determine the “best” yield surface equation for a given cross section geometry. Given that the exact yield surface shall have zero percentage of concavity, this investigation evaluated the resulting coefficient of determination (

The influence of zero value subtraction on the performance of a new laser fluorescence device for approximal caries detection

The aim of this study was to assess the influence of the zero value subtraction on the performance of laser fluorescence (LFpen) for approximal caries detection. Three areas (cuspal, middle and cervical) of both mesial and distal buccal surfaces of 78 permanent molars were assessed using both wedge-shaped (WDG) and tapered wedge-shaped (TWDG) tips. With the addition of the average, one cut-off value for each area was obtained and the performance was assessed. The areas under the receiver operating characteristics (ROC) curve, specificity, sensitivity and accuracy with and without the zero value subtraction were calculated. The McNemar test revealed a statistically significant difference for specificity at thresholds D(1), D(2) and D(3) (WDG) and D(1) and D(2) (TWDG) when the zero value subtraction was not performed. Influence of the zero value subtraction on the LFpen performance was observed for approximal caries detection. However, when modified cut-off values were used, the zero value subtraction could be eliminated.

Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound

We explore the macroeconomic effects of a compression in the long-term bond yield spread within the context of the Great Recession of 2007–09 via a time-varying parameter structural VAR model. We identify a “pure” spread shock defined as a shock that leaves the policy rate unchanged, which allows us to characterize the macroeconomic consequences of a decline in the yield spread induced by central banks’ asset purchases within an environment in which the policy rate is constrained by the effective zero lower bound. Two key findings stand out. First, compressions in the long-term yield spread exert a powerful effect on both output growth and inflation. Second, conditional on available estimates of the impact of the Federal Reserve’s and the Bank of England’s asset purchase programs on long-term yield spreads, our counterfactual simulations suggest that U.S. and U.K. unconventional monetary policy actions have averted significant risks both of deflation and of output collapses comparable to those that took place during the Great Depression.

Comparison of energy expenditure, eating pattern and physical activity of grazing and zero-grazing dairy cows at different time points during lactation

An experiment was conducted to determine the effect of grazing versus zero-grazing on energy expenditure (EE), feeding behaviour and physical activity in dairy cows at different stages of lactation. Fourteen Holstein cows were subjected to two treatments in a repeated crossover design with three experimental series (S1, S2, and S3) reflecting increased days in milk (DIM). At the beginning of each series, cows were on average at 38, 94 and 171 (standard deviation (SD) 10.8) DIM, respectively. Each series consisted of two periods containing a 7-d adaptation and a 7-d collection period each. Cows either grazed on pasture for 16–18.5 h per day or were kept in a freestall barn and had ad libitum access to herbage harvested from the same paddock. Herbage intake was estimated using the double alkane technique. On each day of the collection period, EE of one cow in the barn and of one cow on pasture was determined for 6 h by using the 13C bicarbonate dilution technique, with blood sample collection done either manually in the barn or using an automatic sampling system on pasture. Furthermore, during each collection period physical activity and feeding behaviour of cows were recorded over 3 d using pedometers and behaviour recorders. Milk yield decreased with increasing DIM (P<0.001) but was similar with both treatments. Herbage intake was lower (P<0.01) for grazing cows (16.8 kg dry matter (DM)/d) compared to zero-grazing cows (18.9 kg DM/d). The lowest (P<0.001) intake was observed in S1 and similar intakes were observed in S2 and S3. Within the 6-h measurement period, grazing cows expended 19% more (P<0.001) energy (319 versus 269 kJ/kg metabolic body size (BW0.75)) than zero-grazing cows and differences in EE did not change with increasing DIM. Grazing cows spent proportionally more (P<0.001) time walking and less time standing (P<0.001) and lying (P<0.05) than zero-grazing cows. The proportion of time spent eating was greater (P<0.001) and that of time spent ruminating was lower (P<0.05) for grazing cows compared to zero-grazing cows. In conclusion, lower feed intake along with the unchanged milk production indicates that grazing cows mobilized body reserves to cover additional energy requirements which were at least partly caused by more physical activity. However, changes in cows׳ behaviour between the considered time points during lactation were too small so that differences in EE remained similar between treatments with increasing DIM.

Increased CO2 modifies the carbon balance and the photosynthetic yield of two common Arctic brown seaweeds: Desmarestia aculeata and Alaria esculenta

Ocean acidification affects with special intensity Arctic ecosystems, being marine photosynthetic organisms a primary target, although the consequences of this process in the carbon fluxes of Arctic algae are still unknown. The alteration of the cellular carbon balance due to physiological acclimation to an increased CO2 concentration (1300 ppm) in the common Arctic brown seaweeds Desmarestia aculeata and Alaria esculenta from Kongsfjorden (Svalbard) was analysed. Growth rate of D. aculeata was negatively affected by CO2 enrichment, while A. esculenta was positively affected, as a result of a different reorganization of the cellular carbon budget in both species. Desmarestia aculeata showed increased respiration, enhanced accumulation of storage biomolecules and elevated release of dissolved organic carbon, whereas A. esculenta showed decreased respiration and lower accumulation of storage biomolecules. Gross photosynthesis (measured both as O2 evolution and 14C fixation) was not affected in any of them, suggesting that photosynthesis was already saturated at normal CO2 conditions and did not participate in the acclimation response. However, electron transport rate changed in both species in opposite directions, indicating different energy requirements between treatments and species specificity. High CO2 levels also affected the N-metabolism, and 13C isotopic discrimination values from algal tissue pointed to a deactivation of carbon concentrating mechanisms. Since increased CO2 has the potential to modify physiological mechanisms in different ways in the species studied, it is expected that this may lead to changes in the Arctic seaweed community, which may propagate to the rest of the food web.

Short-term effects of four tillage practices on soil physical properties, soil water potential, and maize yield

The area cultivated using conservation tillage has recently increased in central Spain. However, soil compaction and water retention with conservation tillage still remains a genuine concern for landowners in this region be- cause of its potential effect on the crop growth and yield. The aim of this research is to determine the short- term influences of four tillage treatments on soil physical properties. In the experiment, bulk density, cone index, soil water potential, soil temperature and maize (Zea mays L.) productivity have been measured. A field experiment was established in spring of 2013 on a loamy soil. The experiment compared four tillage methods (zero tillage, ZT; reservoir tillage, RT; minimum tillage, MT; and conventional tillage, CT). Soil bulk density and soil cone index were measured during maize growing season and at harvesting time. Furthermore, the soil water potential was monitored by using a wireless sensors network with sensors at 20 and 40 cm depths. Also, soil temperatures were registered at depths of 5 and 12 cm. Results indicated that there were significant differ- ences between soil bulk density and cone index of ZT method and those of RT, MT, and CT, during the growing season; although, this difference was not significant at the time of harvesting in some soil layers. Overall, in most soil layers, tillage practice affected bulk density and cone index in the order: ZT N RT N MT N CT. Regardless oftheentireobservationperiod,results exhibited that soils under ZT and RT treatments usually resulted in higher water potential and lower soil temperature than the other two treatments at both soil depths. In addition, clear differences in maize grain yield were observed between ZT and CT treatments, with a grain yield (up to 15.4%) increase with the CT treatment. On the other hand, no significant differences among (RT, MT, and CT) on maizeyieldwerefound.Inconclusion,the impact of soil compaction increase and soil temperature decrease,pro- duced by ZT treatment is a potential reason for maize yield reduction in this tillage method. We found that RT could be certainly a viable option for farmers incentral Spain,particularly when switching to conservation tillage from conventional tillage. This technique showed a moderate and positive effect on soil physical properties and increased maize yields compared to ZT and MT, and provides an opportunity to stabilize maize yields compared to CT.

The Zeros of Riemann Zeta Partial Sums Yield Solutions to f(x) + f(2x) + · · · + f(nx) = 0

This paper proves that every zero of any n th , n ≥ 2, partial sum of the Riemann zeta function provides a vector space of basic solutions of the functional equation f(x)+f(2x)+⋯+f(nx)=0,x∈R . The continuity of the solutions depends on the sign of the real part of each zero.

Pendant drop formation of shear-thinning and yield stress fluids

A volume-of-fluid numerical method is used to predict the dynamics of shear-thinning liquid drop formation in air from a circular orifice. The validity of the numerical calculation is confirmed for a Newtonian liquid by comparison with experimental measurements. For particular values of Weber number and Froude number, predictions show a more rapid pinch-off, and a reduced number of secondary droplets, with increasing shear-thinning. Also a minimum in the limiting drop length occurs for the smallest Weber number as the zero-shear viscosity is varied. At the highest viscosity, the drop length is reduced due to shear-thinning, whereas at lower viscosities there is little effect of shear-thinning. The evolution of predicted drop shape, drop thickness and length, and the configuration at pinch-off are discussed for shear-thinning drops. The evolution of a drop of Bingham yield stress liquid is also considered as a limiting case. In contrast to the shear-thinning cases, it exhibits a plug flow prior to necking, an almost step-change approach to pinch-off of a torpedo shaped drop following the onset of necking, and a much smaller neck length; no secondary drops are formed. The results demonstrate the potential of the numerical model as a design tool in tailoring the fluid rheology for controlling drop formation behaviour. (c) 2006 Elsevier Inc. All rights reserved.

Zero weights and non-zero slacks:different solution to the same problem

This paper re-assesses three independently developed approaches that are aimed at solving the problem of zero-weights or non-zero slacks in Data Envelopment Analysis (DEA). The methods are weights restricted, non-radial and extended facet DEA models. Weights restricted DEA models are dual to envelopment DEA models with restrictions on the dual variables (DEA weights) aimed at avoiding zero values for those weights; non-radial DEA models are envelopment models which avoid non-zero slacks in the input-output constraints. Finally, extended facet DEA models recognize that only projections on facets of full dimension correspond to well defined rates of substitution/transformation between all inputs/outputs which in turn correspond to non-zero weights in the multiplier version of the DEA model. We demonstrate how these methods are equivalent, not only in their aim but also in the solutions they yield. In addition, we show that the aforementioned methods modify the production frontier by extending existing facets or creating unobserved facets. Further we propose a new approach that uses weight restrictions to extend existing facets. This approach has some advantages in computational terms, because extended facet models normally make use of mixed integer programming models, which are computationally demanding.