Navegando por Autor "Laviola, Bruno Galveas"

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Application of neural networks to predict volume in eucalyptus
(Crop Breeding and Applied Biotechnology, 2015-03-16) Bhering, Leonardo Lopes; Cruz, Cosme Damião; Peixoto, Leonardo de Azevedo; Rosado, Antônio Marcos; Nascimento, Moysés; Laviola, Bruno Galveas
The aim of this study was to evaluate the methodology of Artificial Neural Networks (ANN) in order to predict wood volume in eucalyptus and its impacts on the selection of superior families, and to compare artificial neural network with regression models. Data used were obtained in a random block design with 140 half-sib families with five replications at three years of age, and four replications at six years of age, both with five plants per plot. The volume was estimated using ANN and regression models. It was used 2000 and 1500 data to train ANN, and 1500 and 1300 to validate ANN for 3 and 6 years of age, respectively. It is concluded that ANN can help improving the accuracy to measure the volume in eucalyptus trees, and to automate the process of forestry inventory and were more accurate in predicting wood volume than almost all regression models.
Eficiência na produção de frutos e alocação relativa de nutrientes em cultivares de cafeeiro
(Revista Ceres, 2010-02) Amaral, José Francisco Teixeira do; Martinez, Herminia Emilia Prieto; Laviola, Bruno Galveas; Fernandes Filho, Elpidio Inácio; Cruz, Cosme Damião
Considerando a baixa produtividade das plantas em solos de menor fertilidade natural e o alto custo dos insumos agrícolas, torna-se necessária a seleção de cultivares mais eficientes na absorção e utilização dos nutrientes minerais. Foram avaliados quatro cultivares de cafeeiro arábica (Acaiá IAC 474 19, Icatu Amarelo IAC 3282, Rubi MG 1192 e Catuaí Vermelho IAC 99) quanto à eficiência na produção de frutos e alocação relativa de nutrientes. O experimento foi conduzido em Viçosa MG, em condições de campo, no delineamento experimental em blocos ao acaso, envolvendo quatro cultivares, quatro repetições e três níveis de adubação (baixo, normal e alto). As parcelas úteis constituíram-se de nove plantas espaçadas de 2 x 1 m. O cultivar Icatu Amarelo IAC 3282 foi o mais produtivo no ambiente com restrição de nutrientes, enquanto Rubi MG 1192 e Catuaí Vermelho IAC 99 mostraram-se mais produtivos em ambientes com alto suprimento de nutrientes. A eficiência de produção de café em coco por unidade de P, Ca, Mg e B acumulados na planta foi maior no nível alto de adubação. Os cultivares Rubi MG-1192 e Catuaí Vermelho IAC 99 apresentaram maior eficiência de utilização de nutrientes para produção de frutos no nível alto de adubação. Considerando a média de alocação relativa de nutrientes nos frutos para os quatro cultivares, no nível normal de adubação, verificou-se que eles possuem 38,1% do N, 46,34% do P, 40,19% do S, 42,68% do K, 13,19% do Ca, 25,04% do Mg, 40,63% do Cu, 19,49% do Zn e 17,73% do B.
Establishment of new strategies to quantify and increase the variability in the Brazilian Jatropha genotypes
(Industrial Crops and Products, 2018-07) Bhering, Leonardo Lopes; Laviola, Bruno Galveas; Alves, Alexandre Alonso; Formighieri, Eduardo Fernandes; Peixoto, Leonardo de Azevedo
The genetic diversity of Brazilian Jatropha (Jatropha curcas) germplasm collection (BJGC), which consists of 192 accessions, has been previously reported based on the evaluation of a limited number of RAPD and SSR markers. In addition, accessions from other countries (Guatemala and Mexico) were introduced to this collection without prior information on their relation with the existing collection. Thus the objective of this study were to develop and validate a panel for high-density genome-wide molecular markers for Jatropha; to compare the diversity of the germplasm collected in Brazil and the materials introduced and/or generated by crossing selected genotypes; and to determine whether the germplasm introduction strategies and the controlled crossings were efficient in generating/increasing the genetic variability available to the breeding program. This study reported an evaluation on the existence and on the structure of the genetic diversity of a core collection of 92 accessions by using DArT and SNP markers. The genotyping-by-sequencing approach allowed genotyping 747 polymorphic SNP and 4007 DArTs. The pairwise genetic dissimilarity was estimated according to the Jaccard’s coefficient, and clustered by the UPGMA and Tocher’s clustering methods The genetic diversity distribution was assessed by the analysis of molecular variance (AMOVA). The mean dissimilarity between accessions was low (0.165), and it confirmed that the diversity of the BJGC is very limited. Cluster analysis demonstrated that the introduced genotypes were divergent, and they formed a separate group, indicating that new introductions such as these will be important to promote future efforts on genetic breeding. Accordingly, data from SNP also confirmed the development of a significant amount of genetic variability within families (65%), which probably resulted from the use of the Mexican accession that was found to be considerably divergent when compared with the Brazilian accessions. These results indicate that breeders should focus on two main strategies to generate variability in the BJGC: introduction of new accessions from other countries and crossings between potential genotypes.
Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy
(Industrial Crops and Products, 2019-04) Alves, Rodrigo Silva; Teodoro, Paulo Eduardo; Peixoto, Leonardo de Azevedo; Silva, Lidiane Aparecida; Laviola, Bruno Galveas; Resende, Marcos Deon Vilela de; Bhering, Leonardo Lopes; Rocha, João Romero do Amaral Santos de Carvalho
Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas.
Selection of Jatropha curcas families based on temporal stability and adaptability of genetic values
(Industrial Crops and Products, 2018-09-01) Alves, Rodrigo Silva; Peixoto, Leonardo de Azevedo; Teodoro, Paulo Eduardo; Silva, Lidiane Aparecida; Rodrigues, Erina Vitório; Resende, Marcos Deon Vilela de; Laviola, Bruno Galveas; Bhering, Leonardo Lopes
Despite its numerous important traits for biodiesel production, little research exists on the Jatropha curcas crop, mainly with respect to repeated measures over time (crop years). The present study was thus developed to evaluate repeated measures over time in Jatropha curcas and examine the applicability and efficiency of the harmonic mean of the relative performance of genetic values (HMRPGV) method in the selection of families for yield, stability, and adaptability, simultaneously. The work involved data from the evaluation of 730 individuals of 73 half-sib families, in a complete randomized block design, during six crop years, for the trait grain yield. Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) procedure was performed to estimate the variance components and predict the genetic values. Ten crop years must be evaluated to obtain 80% of the maximum coefficient of determination and 90% accuracy in terms of genetic gain from selection. The efficiency of performing 10 measurements compared with the situation in which only one measurement is used was 67%. The HMRPGV method has great potential in the selection of Jatropha curcas families for yield, stability, and adaptability, simultaneously.