The objective of this work was to evaluate the interaction between genotypes and environments for productivity and content of protein and oil, as well as to estimate the genetic parameters and genetic variation among 18 genotypes of soybean grown in four environments. The experiments were set up in the 2006/2007 agricultural year in a randomized block design with three repetitions. The content of protein and oil in the beans was determined by near infrared spectroscopy (NIR). In the four environments the significance was noted for genetic variability and genotype x environment interactions for all traits. Estimates of the heritability of the analyzed variables were high, indicating potential for selecting superior genotypes in breeding programs. In partial correlation analysis only the oil and protein contents were significantly correlated. Correspondence was observed between the UPGMA and Tocher estimation methods, dividing the genotypes into three heterotic groups, with the protein content being the character that most contributed to genetic diversity.

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Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Fiber length stands out among technological traits as one that still needs to be improved in cotton. Thus, the objectives of this work were to quantify the interrelations between agronomic and technological fiber traits and to identify traits that could be used for the indirect selection of cotton genotypes with longer fiber lengths. Agronomic and technological traits were evaluated in 36 elite lines of cotton that were cultivated in three environments. Canonical correlations were estimated between two groups of traits: agronomic and technological. Path analysis was performed that considered fiber length as the primary dependent variable. The genotypes presented variability in all the evaluated traits, and no significant genotype vs. environmental interaction was observed for any of them. The main technological traits of cotton crops can be improved by an indirect selection of agronomic traits. The selection of cotton genotypes with a smaller size and a higher mean boll weight can be used to increase fiber length and improve other technological traits. Selection indices containing plant height, mean boll weight, fiber strength, and fiber uniformity can be one of the main strategies for the selection of cotton genotypes with a high yield of cotton bolls and long fibers.

Jatropha curcas L. is a perennial oilseed crop belonging to the Euphorbiaceae family, whose oil content in seeds varies from 33 to 38%, giving a yield potential of over 1200 kg of oil per hectare. However, it is a non-domesticated species and research is required for commercial exploration of this species for biodiesel production. The strategies of Embrapa’s jatropha breeding program aim at developing cultivars with high yield and oil content, non-toxic (absence of phorbol esters), resistant to biotic and abiotic stresses and adapted to the main producing regions of Brazil. The program activities started with the enrichment and characterization of the germplasm bank, currently with over 200 accessions from different regions of Brazil. Depending on the specific objectives of the program, different selection and breeding methods are employed. In order to understand the genetic control of specific traits and to generate segregating populations, experimental designs such as diallel crosses, which allow the estimation of heterosis, general combining ability and specific combining ability among genotypes, have been adopted. In addition, molecular markers such as SSR and SNPs are being developed and may help in early selection for characters such as the absence of toxicity in the grains. The program also includes the study on genotype × environment interaction with the evaluation of the progenies/improved clones in different regions of Brazil, which is essential for recommending cultivars for specific or broad climatic conditions. In conclusion, considering that J. curcas is a perennial species and still not domesticated, approximately 5-7 years will be required to obtain improved cultivars and evidence-based information on crop production systems to support commercial cultivation.