The role of the international cocoa germplasm database and the international cocoa quarantine centre in information management and distribution of cocoa genetic resources

A range of physiological parameters (canopy light transmission, canopy shape, leaf size, flowering and flushing intensity) were measured from the International Clone Trial, typically over the course of two years. Data were collected from six locations, these being: Brazil, Ecuador, Trinidad, Venezuela, Côte d’Ivoire and Ghana. Canopy shape varied significantly between clones, although it showed little variation between locations. Genotypic variation in leaf size was differentially affected by the growth location; such differences appeared to underlie a genotype by environment interaction in relation to canopy light transmission. Flushing data were recorded at monthly intervals over the course of a year. Within each location, a significant interaction was observed between genotype and time of year, suggesting that some genotypes respond to a greater extent than others to environmental stimuli. A similar interaction was observed for flowering data, where significant correlations were found between flowering intensity and temperature in Brazil and flowering intensity and rainfall in Côte d’Ivoire. The results demonstrate the need for local evaluation of cocoa clones and also suggest that the management practices for particular planting material may need to be fine-tuned to the location in which they are cultivated.

Estimation of optimal gravity wave parameters for climate models using data assimilation

There is a current need to constrain the parameters of gravity wave drag (GWD) schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters. Because mostGWDschemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the ‘observed’ GWD) and the GWD calculated with a parametrisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed ‘true’ parameters. When real experiments using an independent estimate of the ‘observed’ GWD are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However, by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed GWD at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not in both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in theGWDfound in the tropical lower stratosphere, which are associated with part of the quasi-biennial oscillation forcing, cannot be captured by the parametrisation with optimal parameters.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Immunological parameters related to the adjuvant effect of the ordered mesoporous silica SBA-15

In 2006, the first report of a nanostructured material as adjuvant was described establishing the effectiveness of the ordered mesoporous SBA-15 silica as an immune adjuvant. The present study evaluated the SBA-15 capacity to modulate the immune responsiveness of High and Low responder mice immunized with BSA encapsulated/adsorbed in SBA-15 by the intramuscular or oral route and the adjuvant effect was compared with the responsiveness induced by BSA in aluminum hydroxide salts or emulsified in Incomplete Freund adjuvant. These results demonstrate the ability of the non-toxic SBA-15 nanoparticles to increase the immunogenicity and repair the responsiveness of the constitutively low responder individuals inducing both the IgG2a and the IgG1 isotypes, independently of the immune cell committed and conditioning the low phenotype. This new adjuvant may reveal novel therapeutic targets for immune modulation and vaccine design. (C) 2010 Elsevier Ltd. All rights reserved.

University Scheduling using Genetic Algorithm

The automated timetabling and scheduling is one of the hardest problem areas. This isbecause of constraints and satisfying those constraints to get the feasible and optimizedschedule, and it is already proved as an NP Complete (1) [1]. The basic idea behind this studyis to investigate the performance of Genetic Algorithm on general scheduling problem underpredefined constraints and check the validity of results, and then having comparative analysiswith other available approaches like Tabu search, simulated annealing, direct and indirectheuristics [2] and expert system. It is observed that Genetic Algorithm is good solutiontechnique for solving such problems and later analysis will prove this argument. The programis written in C++ and analysis is done by using variation in various parameters.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

The Physiological, Enzymatic, and Genetic Characterization of Staphylococcus sp. Chromium (VI) Reductase Function

A strain of Staphylococcus isolated by Dr. Fekete at the Sandia National Laboratory toxic metal dumping site in Sandia, New Mexico. has been found to reduce toxic Cr(VI) to the less toxic Cr(IlI) state. We have ascertained the environmental parameters for optimal bacterial growth and Cr(VI) reduction. This knowledge may be employed in a comprehensive bioremediation scheme designed to accelerate natural reparation of that Sandia ecosystem. In addition we have investigated the genetic and enzymatic basis for this Cr(VI) reducing ability. This information may allow us to create more effective bioremediation schemes based on the comprehensive knowledge of enzyme and gene function. Preliminary investigations have been carried out toward this end which may serve as the basis for a more thorough investigation.

Growth and body nutrient deposition of two broiler commercial genetic lines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Minimizing inter-genotypic competition effects to predict genetic values and selection in forestry genetic tests

The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.

Genetic associations between weight at maturity and maturation rate with ages and weights at first and second calving in Canchim beef cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genetic analysis on growth and carcass traits in Nelore cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Random regressions models to describe the genetic variation of milk yield over multiple parities in Buffaloes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Generalized linear mixed models for the genetic evaluation of binary reproductive traits: a simulation study

The objective of this study was to evaluate the use of probit and logit link functions for the genetic evaluation of early pregnancy using simulated data. The following simulation/analysis structures were constructed: logit/logit, logit/probit, probit/logit, and probit/probit. The percentages of precocious females were 5, 10, 15, 20, 25 and 30% and were adjusted based on a change in the mean of the latent variable. The parametric heritability (h²) was 0.40. Simulation and genetic evaluation were implemented in the R software. Heritability estimates (ĥ²) were compared with h² using the mean squared error. Pearson correlations between predicted and true breeding values and the percentage of coincidence between true and predicted ranking, considering the 10% of bulls with the highest breeding values (TOP10) were calculated. The mean ĥ² values were under- and overestimated for all percentages of precocious females when logit/probit and probit/logit models used. In addition, the mean squared errors of these models were high when compared with those obtained with the probit/probit and logit/logit models. Considering ĥ², probit/probit and logit/logit were also superior to logit/probit and probit/logit, providing values close to the parametric heritability. Logit/probit and probit/logit presented low Pearson correlations, whereas the correlations obtained with probit/probit and logit/logit ranged from moderate to high. With respect to the TOP10 bulls, logit/probit and probit/logit presented much lower percentages than probit/probit and logit/logit. The genetic parameter estimates and predictions of breeding values of the animals obtained with the logit/logit and probit/probit models were similar. In contrast, the results obtained with probit/logit and logit/probit were not satisfactory. There is need to compare the estimation and prediction ability of logit and probit link functions.

Models for genetic evaluation of Nelore cattle mature body weight

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)