Parâmetros genéticos de características de carcaça e de crescimento de bovinos da raça Nelore

The objectives of this study were to estimate genetic parameters involving yearling weight (Ps), carcass weight (Pc), hip height (Ag) and the scores of conformation (C), precocity (P) and musculature (M) and carcass yield (Rd) and finishing score (Ac) in Nellore cattle in order to define criteria for selection in this breed. The data of the 20 732 animals were obtained from Agrope-cuária Jacarezinho, SP. Data were analyzed by restricted maximum likelihood using animal model multi-trait analysis, which included fixed effects of contemporary groups (animals born at the same month and slaughtered on the same day) and the covariate age at slaughter (linear) for carcass traits, and contemporary groups (animals of the same farm, age, sex and management group at weaning and yearling) and yearling age (linear) for growth and as random, the additive effects and residual effects. Estimates ranged from 0.13 (Ac and Rd) to 0.36 (Ag) for heritability and from -0.59 ± 0.62 (Rd with Ac) to 0.71 ± 0.17 (Pc with C) for genetic correlations. Selection for Pc, C, P, M, Ag or Ps may be efficient because their heritability estimates are of magnitude moderate. Selection for Ps and C can favor heavier Pc, considering their positive and high genetic correlation.

Energetic-environmental assessment of a scenario for Brazilian cellulosic ethanol

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

Accumulated productivity and its genetic association with reproductive traits in females Brahman

Objective. Assessment of genetic parameters for accumulative productivity trait (ACP) and genetic correlations with age at first calving (AFC), between calving interval of first and second parity (BCI1) and longevity (LONG). Materials and methods. 8584 Brahman female records were used with an animal model in multi-trait analysis with restricted maximum likelihood method, implemented using the WOMBAT software. The models considered the fixed effects of contemporary group, parity and weaning weight of first calf covariate, the only random effect was the genetic additive direct. Weaning weight (P240) was included to reduce the effect of selection on the estimation of variance components. Results. The heritability estimates were 0.3 +/- 0.04, 0.11 +/- 0.03, 0.07 +/- 0.03 and 0.24 +/- 0.04 for AFC, BCI1, LONG and ACP respectively. Correlations between ACP and the other features were moderate to high and favorable. Conclusions. ACP can be included in breeding programs for Brahman, and used as selection criteria for its moderate heritability and genetic correlation with reproductive traits.

Genetic parameter estimation for pre- and post-weaning traits in Brahman cattle in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Finishing precocity visual score and genetic associations with growth traits in Angus beef cattle

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoprocessamento na análise da vulnerabilidade ambiental desencadeada pela monocultura de cana-de-açúcar na bacia do distrito Santa Olímpia (Piracicaba/SP)

Sugar cane production is of the utmost importance to the economy of the entire Brazil, due to its multiple utility, being used as the raw material for the manufacture of various items, particularly, sugar and alcohol. In areas of sugarcane monoculture, the appropriate management of soils and water is essential, not only for the maintenance of the quality of the environment, but also for the quality of life of the population. Among the main impacts generated by the cultivation of sugar cane, stands out the withdrawal of the riparian forest, which is essential to the balance and maintenance of the ecosystem. Before that, the present work aimed at mapping the environmentally vulnerable areas in the basin of a tributary of the Corumbataí river, located in the district Santa Olímpia, in the city of Piracicaba-SP. For the purpose, techniques were used in Geoprocessing, aiming to produce thematic maps of Slope, for the Use and Occupation of Land, of Permanent Preservation Areas (APP), Soil and Geological of the basin of interest. From these mappings, the analysis was performed multi-criteria, which resulted in the Map of Environmental Vulnerability. This mapping environmental assessment of the study area, indicating proposals of practices for the management and conservation of soil and water resources, for the purpose of improving the environmental quality of the analyzed area. In this way, the research of this nature, may help in the decision-making on the part of the governmental bodies as well as civil society

Vulnerabilidade ambiental dos recursos hídricos interceptados por rodovias na bacia do rio Uberaba

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estrutura populacional e parâmetros genéticos da característica classe de tempo em corridas de equinos da raça Quarto de Milha

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

Programação por metas e análise envoltória de dados na avaliação de unidades de produção global: uma aplicação em uma empresa do segmento químico

Considering the high competitivity in the market, the application of quantitative methods can assist in analyzing the efficiency of production facilities of areas of export and import processes of the chemical industry sector. In this sense, this work aims to apply the model GPDEA-BCC optimization in order to develop an analysis of the production units of this chemical industry. So, were chosen variables relevant to the process and elaborated a final comparison between the results obtained by the optimization tool and performance indexes provided by the company. These results indicated that some production units should be monitored more carefully because some of them had a low efficiency when analyzed with multi criteria

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

Programação por metas e análise envoltória de dados na avaliação de unidades de produção global: uma aplicação em uma empresa do segmento químico

Considering the high competitivity in the market, the application of quantitative methods can assist in analyzing the efficiency of production facilities of areas of export and import processes of the chemical industry sector. In this sense, this work aims to apply the model GPDEA-BCC optimization in order to develop an analysis of the production units of this chemical industry. So, were chosen variables relevant to the process and elaborated a final comparison between the results obtained by the optimization tool and performance indexes provided by the company. These results indicated that some production units should be monitored more carefully because some of them had a low efficiency when analyzed with multi criteria

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Un modello multicriteriale di supporto alla pianificazione territoriale finalizzato alla classificazione del territorio rurale e alla caratterizzazione dell’Impronta Agro ambientale delle aree agricole periurbane.

La ricerca proposta si pone l’obiettivo di definire e sperimentare un metodo per un’articolata e sistematica lettura del territorio rurale, che, oltre ad ampliare la conoscenza del territorio, sia di supporto ai processi di pianificazione paesaggistici ed urbanistici e all’attuazione delle politiche agricole e di sviluppo rurale. Un’approfondita disamina dello stato dell’arte riguardante l’evoluzione del processo di urbanizzazione e le conseguenze dello stesso in Italia e in Europa, oltre che del quadro delle politiche territoriali locali nell’ambito del tema specifico dello spazio rurale e periurbano, hanno reso possibile, insieme a una dettagliata analisi delle principali metodologie di analisi territoriale presenti in letteratura, la determinazione del concept alla base della ricerca condotta. E’ stata sviluppata e testata una metodologia multicriteriale e multilivello per la lettura del territorio rurale sviluppata in ambiente GIS, che si avvale di algoritmi di clustering (quale l’algoritmo IsoCluster) e classificazione a massima verosimiglianza, focalizzando l’attenzione sugli spazi agricoli periurbani. Tale metodo si incentra sulla descrizione del territorio attraverso la lettura di diverse componenti dello stesso, quali quelle agro-ambientali e socio-economiche, ed opera una sintesi avvalendosi di una chiave interpretativa messa a punto allo scopo, l’Impronta Agroambientale (Agro-environmental Footprint - AEF), che si propone di quantificare il potenziale impatto degli spazi rurali sul sistema urbano. In particolare obiettivo di tale strumento è l’identificazione nel territorio extra-urbano di ambiti omogenei per caratteristiche attraverso una lettura del territorio a differenti scale (da quella territoriale a quella aziendale) al fine di giungere ad una sua classificazione e quindi alla definizione delle aree classificabili come “agricole periurbane”. La tesi propone la presentazione dell’architettura complessiva della metodologia e la descrizione dei livelli di analisi che la compongono oltre che la successiva sperimentazione e validazione della stessa attraverso un caso studio rappresentativo posto nella Pianura Padana (Italia).