Multidimensional scaling analysis (MDS) showing the first two principal components based on 1,248 markers that were run on the 78 genotypes of Jatropha.

<p>Multidimensional scaling analysis (MDS) showing the first two principal components based on 1,248 markers that were run on the 78 genotypes of Jatropha.</p

Genetic and environmental parameters estimated by REML analysis.

<p>Genetic and environmental parameters estimated by REML analysis.</p

Jatropha half-sib family selection with high adaptability and genotypic stability

<div><p>Jatropha (<i>Jatropha curcas</i>) has become one of the most important species for producing biofuels. Currently, Genotype x Environment (GxE) interaction is the biggest challenge that breeders should solve to increase the section accuracy in the plant breeding. Therefore, the objectives in this study were to estimate the parameters in the 180 half-sib families in Jatropha evaluated for five production years, to verify the significance of the GxE interaction variance, to evaluate the adaptability and stability for each family based on three prediction methods, to select superior half-sib families based on the adaptability and stability analyses, and to predict the accuracy for the sixth production year. Jatropha half-sib families were classified and selected using the follow adaptability and stability methods: linear regression, bi-segmented linear regression and mixed models concepts called harmonic mean of the relative performance of genetic values (HMRPGV). The prediction accuracy was estimated by the Pearson correlation between the predicted genetic values by adaptability and stability methods and the phenotypic value in the sixth production year. In result, most half-sib families were classified as general adaptability and general stability for the evaluated traits. The selection gain obtained via HMRPGV was higher than other methods. The prediction accuracy for the sixth production year was 0.45. Therefore, HMRPGV is efficient to maximize the genetic gain, and it can be a useful strategy to select genotype with high adaptability and stability in Jatropha breeding as well as other species that should be evaluated for many years to take a suitable selection accuracy.</p></div

Classification of the 180 Jatropha half-sib families based on adaptability and stability parameters via Cruz <i>et al</i>. [9] method for weight of 100 seeds (W100S) evaluated during four years.

<p>Families highlighted with red color have mean superior with the overall mean.</p

Graphic analysis of the minimum number of measurements required to reach a determined degree of certainty for phenolic compounds and chlorophyll according to different methods: ANOVA–analysis of variance; PCA-COV—principal component analysis associated with covariance matrix; PCA-COR—principal component analysis associated with correlation matrix; structural analysis; MM–mixed model.

<p>DZI—Daidzein; GI—Gensitin; MD–Malonyl Daidzin; R—Quercetin-3-O-Rutinoside; MG–Malonyl Genistin; GEI–Genistein; C–Coumestrol; and CLO–Chlorophyll.</p

Classification of the 180 Jatropha half-sib families based on adaptability and stability parameters via Eberhart and Russell [8] method for yield production (PROD) evaluated during five years.

<p>Families highlighted with red color have mean superior with the overall mean.</p

Classification of the 180 Jatropha half-sib families based on adaptability and stability parameters via Eberhart and Russell [8] method for weight of 100 seeds (W100S) evaluated during four years.

<p>Families highlighted with red color have mean superior with the overall mean.</p

Coincidence index among adaptability and stability methods based on the 20 superior Jatropha half-sib families for yield production (PROD–superior diagonal) and weight of 100 seeds (W100S –inferior diagonal).

<p>Coincidence index among adaptability and stability methods based on the 20 superior Jatropha half-sib families for yield production (PROD–superior diagonal) and weight of 100 seeds (W100S –inferior diagonal).</p

Estimative of genetic parameters via analysis of variance (ANOVA) and mixed models for yield production (PROD) and weight of 100 seeds (W100S) evaluated in 180 Jatropha half-sib families during five years.

<p>Estimative of genetic parameters via analysis of variance (ANOVA) and mixed models for yield production (PROD) and weight of 100 seeds (W100S) evaluated in 180 Jatropha half-sib families during five years.</p

Mean, heritability (h²) and coefficient of variation (CV, %) for the 14 traits evaluated in soybean plants inoculated or non-inoculated with <i>Phakopsora pachyrhizi</i> during four consecutive measurements (48, 96, 144, 192 hours after inoculation).

<p>Mean, heritability (h²) and coefficient of variation (CV, %) for the 14 traits evaluated in soybean plants inoculated or non-inoculated with <i>Phakopsora pachyrhizi</i> during four consecutive measurements (48, 96, 144, 192 hours after inoculation).</p