About
99
Publications
7,319
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
340
Citations
Citations since 2017
Publications
Publications (99)
In this study, marker-assisted recurrent selection was evaluated for pyramiding resistance gene alleles against coffee leaf rust (CLR) and coffee berry diseases (CBD) in Coffea arabica. A total of 144 genotypes corresponding to 12 hybrid populations from crosses between eight parent plants with desired morphological and agronomic traits were evalua...
The presence of non-informative markers in Genome Wide Selection (GWS) needs to be evaluated so that the genomic prediction is more efficient in a breeding program. This study proposes to evaluate the efficiency of RR-BLUP after reducing the dimensionality of SNP's markers in the presence of different levels of dominance, heritability, and epistati...
The study of traits in crops enables breeders to guide strategies for selecting and accelerating the progress of genetic breeding. Although the simultaneous evaluation of characteristics in the plant breeding programme provides large quantities of information, identifying which phenotypic characteristic is the most important is a challenge facing b...
Among the multi-trait models selected to study several traits and environments jointly, the Bayesian framework has been a preferred tool when constructing a more complex and biologically realistic model. In most cases, non-informative prior distributions are adopted in studies using the Bayesian approach. However, the Bayesian approach presents mor...
Genomic wide selection (GWS) is one contributions of molecular genetics to breeding. Machine learning (ML) and artificial neural networks (ANN) methods are non-parameterized and can develop more accurate and parsimonious models for GWS analysis. Multivariate Adaptive Regression Splines (MARS) is considered one of the most flexible ML methods, autom...
The objectives of this study were to use a bayesian multi-trait model, estimate genetic parameters, and select flood-irrigated rice genotypes with better genetic potentials in different evaluation environments. For this, twenty-five rice genotypes and six traits belonging to the flood-irrigated rice improvement program were evaluated. The experimen...
The objective of this work was to evaluate a procedure for the elicitation of informative prior distribution, compared with non-informative prior distribution, in a small sample size, using 14 traits of three linseed (Linum usitatissimum) genotypes in seven sowing seasons. The values of the hyperparameters regulate the informativeness of the prior...
Information on the genetic diversity of commercial cultivars is of fundamental importance for crop improvement. In addition, information about possible interactions between the maintainers who develop these cultivars can help design a breeding program. Therefore, the objective of this work was to study the genetic diversity of soybean cultivars rel...
The objective of this work was to estimate the best approach for prediction and establish a network with better predictive power in white oat using methodologies based on regression, artificial intelligence, and machine learning. Seventy-eight white oat genotypes were evaluated in 2008 and 2009. Were evaluated without and with fungicide, establishe...
Persistence plays a key role in alfalfa cultivation in tropical areas, but it is still a restriction for breeding programs. The objectives of this study were to identify persistent alfalfa accessions evaluated under tropical conditions, and to propose a method for selecting persistent accessions based on Random Regression (RR) models using Artifici...
The biggest challenge for the reproduction of flood-irrigated rice is to identify superior genotypes that present development of high-yielding varieties with specific grain qualities, resistance to abiotic and biotic stresses in addition to superior adaptation to the target environment. Thus, the objectives of this study were to propose a multi-tra...
The present study aimed to implement a Bayesian framework for genetic analysis in crop species breeding and present different procedures for informative prior elicitation. Genetic Bayesian estimation in crop breeding was performed using ten years of evaluation in the white oat population. The Bayesian framework was based on the MCMC Generalized Lin...
The objectives of this work were to simulate and quantify epistatic effects on oligogenic traits and to verify the efficiency of Artificial Neural Networks (ANN) and Ridge Regression Best Linear Unbiased Predictor (RRBLUP) in the prediction of genetic values of oligogenic traits controlled by epistatic genes. We simulated 10 F2 populations in Hardy...
The mass and diameter traits of peach fruits are important parameters to define fruit quality, harvest planning, and management of peach production through the estimation of fresh mass. However, currently, fruit mass estimation methods are based on conventional destructive analyzes which, as they are invasive measurements, can take considerable tim...
The giant challenge breeding flood-irrigated rice is to identify superior genotypes that present high-yielding with specific grain qualities, resistance to abiotic and biotic stresses, excellent adaptation to the target environment. Thus, the objectives of this study were to propose a bayesian multi-trait model, estimate genetic parameters, and sel...
The objectives of this study were to use a bayesian multi-trait model, estimate genetic parameters, and select flood-irrigated rice genotypes with better genetic potentials in different evaluation environments. For this, twenty-five rice genotypes belonging to the flood-irrigated rice improvement program were evaluated. The grain yields, grain leng...
Many methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle differen...
The present study evaluated the importance of auxiliary traits of a principal trait based on phenotypic information and previously known genetic structure using computational intelligence and machine learning to develop predictive tools for plant breeding. Data of an F 2 population represented by 500 individuals, obtained from a cross between contr...
The GxE interaction is one of the major difficulties of plant breeding programs, both in the selection phase and in the recommendation of cultivars. To assess adaptability and stability, various statistical methods are used. The simultaneous use of some methodologies, using multi-information criteria for cultivar’s recommendation, can extract infor...
The biggest challenge for the reproduction of flood-irrigated rice is to identify superior genotypes that present development of high-yielding varieties with specific grain qualities, resistance to abiotic and biotic stresses in addition to superior adaptation to the target environment.Thus, the objectives of this study were to propose a multi-trai...
The aim of this study was to use fuzzy logic as an auxiliary tool in the assessment of adaptability and stability, using grain-yield data from flood-irrigated rice, evaluated in different agricultural years. Eighteen rice genotypes belonging to flood-irrigated rice breeding programme were evaluated over four agricultural years, 2012/2013 to 2015/20...
The soybean crop is prominent in national and international scenarios. A large part of the world production of soybean is cultivated in Brazil and this has been possible due to the performance of different technological areas, among them genetics and plant breeding. Soybean breeding has acted in the development and launch of new cultivars and for t...
This study aimed to fit nonlinear regression models to model the growth of the characters fruit length (FL) and fruit width (FW) of pepper genotypes (Capsicum annuum L.) over time using the method of ordinary least squares (OLS); and identify the model with the best fit and compare it to the model obtained via nonlinear quantile regression (QR) in...
Plant breeding aims to develop cultivars with good agronomic traits through gene recombination and elite genotype selection. To support Coffea arabica breeding programs and assist parent selection, molecular characterization, genetic diversity (GD) analyses, and circulating diallel studies were strategically integrated to develop new cultivars. Mol...
The use of resistant cultivars is the most effective strategy for controlling coffee leaf rust caused by the fungus Hemileia vastatrix. To assist the development of such cultivars, amplified fragment-length polymorphism (AFLP) markers linked to two loci of coffee resistance to races I and II as well as pathotype 001 of H. vastatrix were converted t...
The correct choice of parents that will compose optimal segregating populations is the key to success for breeding programs. It was postulated the hypothesis that this choice of these parents could be made based on information of molecular markers analyzed in the context of population structure. Ten parental populations were simulated and 45 hybrid...
The objective of this study was to verify the genetic influence of male parents in the expression of emergence and vigor traits of the sour passion fruit seedling, and to select the ones that contributed with the highest selection results. Controlled hybridizations were performed between genotypes of the Sour Passion Fruit Breeding Program of the U...
The present study evaluated 57 genotypes of rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg.] utilizing 33 morphological descriptors at juvenile stage to determine importance for phenotypic characterization. This study compares different dissimilarity matrices and proposes a new way of calculating the distance matrix of multica...
Genomic‐wide selection (GWS) consists of the use of a large number of molecular markers for the prediction of genetic values and has been shown to be highly relevant for genetic improvement. The objective of this work was to evaluate and compare the predictive performance of statistical (RR‐Blup and BayesB) and machine learning methods through GWS...
Several factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the characteristics of the coffee produced. The most efficient models choice to be applied should take...
Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such methodologies require certain assumptions about the data, such as the normality of the distribution of ph...
Esta obra visa proporcionar aos técnicos, pesquisadores, e docentes, conhecimentos introdutórios e fundamentais sobre a Genética de Populações. Ela norteia o leitor ao entendimento de conceitos e técnicas em atividade didáticas no aplicativo livre GPOP – Genética de Populações, desenvolvido como ferramenta auxiliar de ensino e aprendizagem. Estudos...
Empirical patterns of linkage disequilibrium (LD) can be used to increase the statistical power of genetic mapping. This study was carried out with the objective of verifying the efficacy of factor analysis (AF) applied to data sets of molecular markers of the SNP type, in order to identify linkage groups and haplotypes blocks. The SNPs data set us...
Flowering is an important agronomic trait that presents non-additive gene action. Genome-enabled prediction allow incorporating molecular information into the prediction of individual genetic merit. Artificial neural networks (ANN) recognize patterns of data and represent an alternative as a universal approximation of complex functions. In a Genomi...
The objective of this work was to describe the sensory profile of 11 arabica coffee genotypes with different levels of resistance to rust and to evaluate their genetic potential for the production of specialty coffees. The experiments were conducted in three coffee producing municipalities, in the region of Matas de Minas, in Minas Gerais state, Br...
Parent selection is a crucial step in breeding programs. In the present study, we evaluated the genetic diversity in tropical wheat genotypes using best linear unbiased predictions (BLUPs) by different grouping methods. We identified potential parents to compose a crossing block with the aim of improving wheat for the Brazilian Cerrado. A total of...
Passion fruit breeding programs often use a single fruit to obtain progeny. Open-pollination progenies are considered half-siblings since they allow the occurrence of a mixture of pollens during pollination. However, there are no studies able to prove that these progenies are, in fact, consequence of a mixture of pollens. The contribution of male g...
This paper aimed to evaluate the effectiveness of subset selection of markers for genome-enabled prediction of genetic values using radial basis function neural networks (RBFNN). To this end, an F1 population derived from the hybridization of divergent parents with 500 individuals genotyped with 1000 SNP-type markers was simulated. Phenotypic trait...
The importance of rice (Oryza sativa) is indisputable this cereal is the staple food for half of the global population. Genetic progress estimation allows evaluation of the effectiveness of genetic improvement of crops and helps in the planning of breeding programs. This paper aims to estimate the genetic yield progress made by the program in the s...
Genetic diversity studies are performed based on information on a set of traits measured in a group of genotypes, considering one or more environments. The pattern recognition methods allow classifying genotypes from a set of important agronomic information. Thus, this study aimed to present and compare pattern recognition methods to inquire about...
Trait selection is occasionally necessary to save money and time, as well as accelerate breeding program processes. This study aimed to propose two criteria to select traits based on a Procrustes analysis that are poorly explored in genetic breeding: Criterion 1 (backward algorithm) and Criterion 2 (exhaustive algorithm). Then, these two criteria w...
In response to the new requirements of the sugar-energy sector, sugarcane breeding programs are addressing the selection of clones for different purposes, e.g., sucrose production, ethanol production for first-generation (1G) and second-generation (2G) biofuels. Consequently, agronomic variables such as fiber content, sucrose content and biomass yi...
The study of the potential of a plant population makes the selection of a breeding program more efficient, allowing satisfactory genetic gains and identifying the potential of this population, among others, for advances in generations. The genetic potential of Eucalyptus benthamii is still poorly studied. This species has relevant characteristics f...
The study of adaptability and stability underlies the cultivar recommendation process for all crops. There is a considerable number of statistical methods available for this purpose, but little is known about their actual adoption by the Brazilian scientific community. The objective of this study was to carry out a systematic review of the scientif...
Alfalfa (Medicago sativa L.) is a forage legume of great interest because of its role in milk production schemes. Although it has the potential to be cultivated in different edaphoclimatic regions, the fodder production in tropical regions is limited. The objectives of this study were to perform phenotypic and molecular characterization of alfalfa...
Híbrido de Timor is the principal source for disease and pest resistance genes in C. arabica breeding program worldwide. The part of the chromosome responsible for resistance introgressed from C. canephora to Híbrido de Timor are claimed to affect the cup quality of the C. arabica cultivars derived from the crossing program of Híbrido de Timor. The...
This study aimed to evaluate the relationship among traits related to yield and nutritive value of alfalfa genotypes grown under deficit and full irrigation conditions. Seventy-seven alfalfa genotypes were evaluated in two different cuts, the first one with full irrigation, and the second, with water deficit. A randomized block design with three re...
The maintenance of genetic diversity is fundamental to ensure the population’s viability and to perceive how the evolutionary factors act on these. Using self-organizing maps (SOM) may be interesting to organize the genetic diversity and evidence of the effects caused by dispersive and systematic factors. The objective of this work was to verify if...
The genotype by environment interaction is essential in any plant breeding program. Methodologies allowing the evaluation of nonlinear genotype responses to environmental variation allied to prior beliefs on unknown parameters bring new insights for breeders. In this context, we aimed to propose a Bayesian segmented regression model to infer on phe...
The objective of this study was to adjust nonlinear quantile regression models for the study of dry matter accumulation in garlic plants over time, and to compare them to models fitted by the ordinary least squares method. The total dry matter of nine garlic accessions belonging to the Vegetable Germplasm Bank of Universidade Federal de Viçosa (BGH...
The objective of this work was to evaluate the similarity network graphic methodology for the classification of flood-irrigated rice (Orzya sativa) genotypes regarding their adaptability and stability. Two statistical measures were used to represent the proximity of the behavior (based on Pearson’s correlation) or values (based on Gower’s distance)...
