Oil content increase and toxicity reduction in jatropha seeds through family selection

Peixoto, Leonardo de Azevedo; Laviola, Bruno Galvêas; Mendonça, Simone; Costa, Tânia da Silveira Agostini; Antoniassi, Rosemar

doi:10.1016/j.indcrop.2015.10.034

Cited by 21 publications

(8 citation statements)

References 29 publications

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“…2 h estimates obtained for the traits PH12, PH40, CPR40, GY and OY are considered moderate (>50%), and are in accordance with the results reported by Laviola et al (2010Laviola et al ( , 2012b. Peixoto et al (2016), who evaluated productive traits in Jatropha, verified genetic variability between Jatropha accessions of the germplasm bank of EMBRAPA Agroenergy, and in this way, it is possible to obtain gain from selection on these traits.…”

Section: Anova and Estimates Of Genetic Parameterssupporting

confidence: 87%

“…One of the main objectives of Jatropha-breeding programs is the selection of genotypes with high yield potential (Bhering et al, 2013;Peixoto et al, 2016;Silva Junqueira et al, 2016). To this end, knowing the association between traits is necessary, especially if selecting one of them is difficult, owing to the low heritability and/or difficulty in measurement and identification.…”

Section: Introductionmentioning

confidence: 99%

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Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield

et al. 2017

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ABSTRACT. Jatropha is a species with great potential for biodiesel production, and the knowledge on how the main agronomic traits are correlated will contribute to its improvement. Therefore, the objectives of this study were to estimate the genetic parameters of the traits: plant height at 12 and 40 months, canopy projection on the row at 12 and 40 months, canopy projection between the row at 12 and 40 months, number of branches at 40 months, grain yield, and oil yield; to verify the existence of phenotypic correlation between these traits; to verify the influence of the morphological traits on oil yield by means of path analysis; and to evaluate the relationship between the productive traits in Jatropha and the morphological traits measured at different ages. Sixty-seven half-sib families were evaluated using a completely randomized block design with two replications and five plants per plot. Analysis of variance was used to estimate the genetic value. Phenotypic correlations were given by the Pearson correlation between traits. For the canonical correlation analysis, two groups of traits were established: group I, consisting of traits of economic importance for the culture, and group II, consisting of morphological traits. Path analysis was carried out considering oil yield as the main dependent variable. Genetic variability was observed among Jatropha families. Productive traits can be indirectly selected via morphological traits due to the correlation between these two groups of traits. Therefore, canonical correlations and path analysis are two strategies that may be useful in Jatrophabreeding program when the objective is to select productive traits via morphological traits.

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Section: Anova and Estimates Of Genetic Parameterssupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield

et al. 2017

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“…Jatropha curcas L. ranks among the most relevant crops for biofuel production [1,2]. Its high adaptability, which allows its cultivation under different environmental conditions, tolerance to drought, longevity and high oil quality are some desirable characteristics which highlight Jatropha curcas as an excellent alternative for renewable energy production [1,3,4].…”

Section: Introductionmentioning

confidence: 99%

Random regression for modeling yield genetic trajectories in Jatropha curcas breeding

et al. 2020

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Random regression models (RRM) are a powerful tool to evaluate genotypic plasticity over time. However, to date, RRM remains unexplored for the analysis of repeated measures in Jatropha curcas breeding. Thus, the present work aimed to apply the random regression technique and study its possibilities for the analysis of repeated measures in Jatropha curcas breeding. To this end, the grain yield (GY) trait of 730 individuals of 73 half-sib families was evaluated over six years. Variance components were estimated by restricted maximum likelihood, genetic values were predicted by best linear unbiased prediction and RRM were fitted through Legendre polynomials. The best RRM was selected by Bayesian information criterion. According to the likelihood ratio test, there was genetic variability among the Jatropha curcas progenies; also, the plot and permanent environmental effects were statistically significant. The variance components and heritability estimates increased over time. Non-uniform trajectories were estimated for each progeny throughout the measures, and the area under the trajectories distinguished the progenies with higher performance. High accuracies were found for GY in all harvests, which indicates the high reliability of the results. Moderate to strong genetic correlation was observed across pairs of harvests. The genetic trajectories indicated the existence of genotype × measurement interaction, once the trajectories crossed, which implies a different ranking in each year. Our results suggest that RRM can be efficiently applied for genetic selection in Jatropha curcas breeding programs.

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“…Thus, to install a genetic breeding program of Jatropha in Brazil numerous studies have been conducted in recent years, such as studies on genetic diversity (Rosado et al, 2010;Bhering et al, 2015), estimates of genetic parameters Teodoro et al, 2016d) and gains with selection Peixoto et al, 2016), repeatibility , Teodoro et al, 2016b, and path analysis (Teodoro et al, 2016c). However, for the formation of base populations for practicing the selection, diallel is the main genetic design used (Cruz et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Multivariate diallel analysis allows multiple gains in segregating populations for agronomic traits in Jatropha

Teodoro¹,

Rodrigues²,

Peixoto³

et al. 2017

Genet. Mol. Res.

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Oil content increase and toxicity reduction in jatropha seeds through family selection

Cited by 21 publications

References 29 publications

Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield

Path analysis and canonical correlations for indirect selection of Jatropha genotypes with higher oil yield

Random regression for modeling yield genetic trajectories in Jatropha curcas breeding

Multivariate diallel analysis allows multiple gains in segregating populations for agronomic traits in Jatropha

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