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ABSTRACT. The objective of this study was to select genitors based on F 1 and F 2 generations, evaluated in different environments, to obtain segregating populations for the identification of strains showing improved earliness, yield, and carioca-type grains. Nine bean strains were crossed in a partial diallel scheme (4 x 5), in which group 1 included 4 strains with early cycles and group 2 included 5 elite strains. The F 1 and F 2 generations and the genitors were assessed in Coimbra and Viçosa in randomized blocks with 3 replications. The following characteristics were evaluated: days between sowing and emergence, and grain yield. We observed an interaction between the effects of general combining ability and specific combining ability with the environments (crop, location, and generation) for both grain earliness and yield. Genetic analysis of earliness revealed a predominance of additive effects and grain yield dominance effects. The strain Goiano Precoce may be used as a genitor in breeding programs to improve earliness, while strains RP1 and VC33 can be used to increase grain N.M. Vale et al. 8220©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 14 (3): 8219-8228 (2015) yield. We observed genetic complementation between strains Goiano Precoce and RP1, BRSMG Madrepérola and BRS Estilo for earliness and between RP1 and Rosinha Precoce for grain yield.

The present work aimed to select populations for the breeding of common bean targeting fusarium wilt resistance and grain yield. Twelve carioca bean lines, which mainly differ in fusarium wilt resistance and grain yield, were crossed in a 6x6 partial diallel scheme. The parents and their 36 F1’s hybrids were evaluated for fusarium wilt severity caused by FOP isolate UFV 01 (FWS), and grain yield (YIELD). 34 F4’s populations, 12 parents and three other lines were also evaluated for grain yield per plant. The data of F1's parents and hybrids were submitted to diallel analysis. Using the grain yield data per plant, the potential of the 34 F4’s populations was predicted by the Jinks and Pooni method (1976). In the diallel analysis, BRSMG Talismã, CVIII 8511, BRS Pérola, VC 25 and VC 13 stood out in terms of the frequency of favorable alleles for FWS. Except for BRSMG Uai and IAC Formoso, these lines presented the most dominant genes associated in Fusarium wilt resistance. For YIELD, there was a predominance of dominant genes determining higher yield. The 20 F4’s populations with the highest potential included the best 12 of the 20 populations, based on diallel analysis for YIELD. Thus, the 12 populations received the addition of four that were highlighted only by the methodology of Jinks and Pooni (1976), and four based on diallel analysis, which totaled 20 populations. The use of information from more advanced inbreeding generations in complementarity with those of diallel is a promising strategy.

ABSTRACT. Recombinant inbred lines (RILs) are a valuable resource for building genetic linkage maps. The presence of genetic variability in the RILs is essential for detecting associations between molecular markers and loci controlling agronomic traits of interest. The main goal of this study was to quantify the genetic diversity of a common bean 2 L.C. Silva et al. Genetics and Molecular Research 15 (3): gmr.15038112 RIL population derived from a cross between Rudá (Mesoamerican gene pool) and AND 277 (Andean gene pool). This population was developed by the single seed descent method from 500 F 2 plants until the F 10 generation. Seven quantitative traits were evaluated in the field in 393 RILs, the parental lines, and five control cultivars. The plants were grown using a randomized block design with additional controls and three replicates. Significant differences were observed among the RILs for all evaluated traits (P < 0.01). A comparison of the RILs and parental lines showed significant differences (P < 0.01) for the number of days to flowering (DFL) and to harvest (DH), productivity (PROD) and mass of 100 beans (M100); however, there were no significant differences for plant architecture, degree of seed flatness, or seed shape. These results indicate the occurrence of additive x additive epistatic interactions for DFL, DH, PROD, and M100. The 393 RILs were shown to fall into 10 clusters using Tocher's method. This RIL population clearly contained genetic variability for the evaluated traits, and this variability will be crucial for future studies involving genetic mapping and quantitative trait locus identification and analysis.

In common bean (Phaseolus vulgaris L.) breeding, several trials are carried out in field conditions to predict the genotypic values, but experimental designs may not be sufficient to capture the field heterogeneity in the experimental area. The objective of this work was to evaluate the potential of spatial models to correct data from a common bean breeding program for spatial trends and improve the prediction of genotypic values. We used real data from 19 field trials from a common bean breeding program and three experimental designs. The traditional statistical model with design effects and independent errors was fitted and used as the basic model. Later, we fitted a sequence of spatial models to include different residual (co)variance structures for local trends and fixed and random effects based on plot position information to capture global and extraneous trends. The basic model and the best-fit spatial model were compared regarding the estimates of heritability, accuracy, prediction error variance, and discordance in the top-ranking genotypes. In most cases, the use of spatial models improved the estimates of heritability and accuracy or, at least, reduced the estimates of prediction error variance. Also, changes in the genotypic values classification were observed. Because no single model presented the best fit for all trials, some of the tested models were recommended for future trials based on the patterns of spatial trends observed. Thus, the use of spatial models helped to improve the data analysis and the prediction of genotypic values by capturing the field heterogeneity in our common bean field trials.