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.

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.

Epistatic effects on grain yield of soybean [Glycine max (L.) Merrill]

Studies addressing the estimation of genetic parameters in soybean have not emphasized the epistatic effects. The purpose of this study was to estimate the significance of these effects on soybean grain yield, based on the Modified Triple Test Cross design. Thirty-two inbred lines derived from a cross between two contrasting lines were used, which were crossed with two testers (L1 and L2). The experiments were carried out at two locations, in 10 x 10 triple lattice designs with 9 replications, containing 32 lines (Pi ), 64 crosses (32 Pi x L1 and 32 Pi x L2 ) and controls. The variation between ( ͞L1i + ͞L2i - ͞Pi ) revealed the presence of epistasis, as well as an interaction of epistasis x environment. Since the predominant component of epistasis in autogamous species is additive x additive (i type), we suggest postponing the selection for grain yield to later generations of inbreeding in order to exploit the beneficial effects of additive x additive epistasis.