Spatial statistical analysis and selection of genotypes in plant breeding

The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.

Base temperature and simulation model for nodes appearance in cape gooseberry (Physalis peruviana L.)

Data was analyzed on development of the solanaceen fruit crop Cape gooseberry to evaluate how well a classical thermal time model could describe node appearance in different environments. The data used in the analysis were obtained from experiments conducted in Colombia in open fields and greenhouse condition at two locations with different climate. An empirical, non linear segmented model was used to estimate the base temperature and to parameterize the model for simulation of node appearance vs. time. The base temperature (Tb) used to calculate the thermal time (TT, ºCd) for node appearance was estimated to be 6.29 ºC. The slope of the first linear segment was 0.023 nodes per TT and 0.008 for the second linear segment. The time at which the slope of node apperance changed was 1039.5 ºCd after transplanting, determined from a statistical analysis of model for the first segment. When these coefficients were used to predict node appearance at all locations, the model successfully fit the observed data (RSME=2.1), especially for the first segment where node appearance was more homogeneous than the second segment. More nodes were produced by plants grown under greenhouse conditions and minimum and maximum rates of node appearance rates were also higher.

Annonaceae substitution rates: a codon model perspective

The Annonaceae includes cultivated species of economic interest and represents an important source of information for better understanding the evolution of tropical rainforests. In phylogenetic analyses of DNA sequence data that are used to address evolutionary questions, it is imperative to use appropriate statistical models. Annonaceae are cases in point: Two sister clades, the subfamilies Annonoideae and Malmeoideae, contain the majority of Annonaceae species diversity. The Annonoideae generally show a greater degree of sequence divergence compared to the Malmeoideae, resulting in stark differences in branch lengths in phylogenetic trees. Uncertainty in how to interpret and analyse these differences has led to inconsistent results when estimating the ages of clades in Annonaceae using molecular dating techniques. We ask whether these differences may be attributed to inappropriate modelling assumptions in the phylogenetic analyses. Specifically, we test for (clade-specific) differences in rates of non-synonymous and synonymous substitutions. A high ratio of nonsynonymous to synonymous substitutions may lead to similarity of DNA sequences due to convergence instead of common ancestry, and as a result confound phylogenetic analyses. We use a dataset of three chloroplast genes (rbcL, matK, ndhF) for 129 species representative of the family. We find that differences in branch lengths between major clades are not attributable to different rates of non-synonymous and synonymous substitutions. The differences in evolutionary rate between the major clades of Annonaceae pose a challenge for current molecular dating techniques that should be seen as a warning for the interpretation of such results in other organisms.

Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

A New Model to Determine the Dispersion of Fatigue Damage Evaluations

Reliable predictions of remaining lives of civil or mechanical structures subjected to fatigue damage are very difficult to be made. In general, fatigue damage is extremely sensitive to the random variations of material mechanical properties, environment and loading. These variations may induce large dispersions when the structural fatigue life has to be predicted. Wirsching (1970) mentions dispersions of the order of 30 to 70 % of the mean calculated life. The presented paper introduces a model to estimate the fatigue damage dispersion based on known statistical distributions of the fatigue parameters (material properties and loading). The model is developed by expanding into Taylor series the set of equations that describe fatigue damage for crack initiation.

Effects of condensation in microchannels with a porous boundary: analytical investigation on heat transfer and meniscus shape

In two-phase miniature and microchannel flows, the meniscus shape must be considered due to effects that are affected by condensation and/or evaporation and coupled with the transport phenomena in the thin film on the microchannel wall, when capillary forces drive the working fluid. This investigation presents an analytical model for microchannel condensers with a porous boundary, where capillary forces pump the fluid. Methanol was selected as the working fluid. Very low liquid Reynolds numbers were obtained (Re~6), but very high Nusselt numbers (Nu~150) could be found due to the channel size (1.5 mm) and the presence of the porous boundary. The meniscus calculation provided consistent results for the vapor interface temperature and pressure, as well as the meniscus curvature. The obtained results show that microchannel condensers with a porous boundary can be used for heat dissipation with reduced heat transfer area and very high heat dissipation capabilities.

Analysis of applicability of Peleg model to the cooking-infusion of mackerel (Scomber japonicus) slices

Mass transfer kinetics in osmotic dehydration is usually modeled by Fick's law, empirical models and probabilistic models. The aim of this study was to determine the applicability of Peleg model to investigate the mass transfer during osmotic dehydration of mackerel (Scomber japonicus) slices at different temperatures. Osmotic dehydration was performed on mackerel slices by cooking-infusion in solutions with glycerol and salt (a w = 0.64) at different temperatures: 50, 70, and 90 ºC. Peleg rate constant (K1) (h(g/gdm)-1) varied with temperature variation from 0.761 to 0.396 for water loss, from 5.260 to 2.947 for salt gain, and from 0.854 to 0.566 for glycerol intake. In all cases, it followed the Arrhenius relationship (R²>0.86). The Ea (kJ / mol) values obtained were 16.14; 14.21, and 10.12 for water, salt, and glycerol, respectively. The statistical parameters that qualify the goodness of fit (R²>0.91 and RMSE<0.086) indicate promising applicability of Peleg model.