ABSTRACT. One of the current focus of common bean breeding programs in Brazil is to increase iron (FeC) and zinc content (ZnC) in grains. The objectives of this study were to estimate genetic parameters for FeC and ZnC in common bean, verify the need for conducting multi-site evaluation tests, identify elite lines that combine high FeC and ZnC with good adaptability, stability, and agronomic potential, and examine the genetic association between FeC and ZnC. Elite lines (140) were evaluated for important agronomic traits in multiple environments. In one trial, FeC and ZnC were evaluated and genetic parameters were estimated. Based on the high heritability estimates and significant selection gains obtained, the conditions for a successful selection was favorable. Of the 140 evaluated lines, 17 had higher FeC and ZnC, and were included in the validation test (2013, five environments), specifically for the evaluation of FeC and ZnC. The line by environment interaction for FeC and ZnC was detected, but it was predominantly simple. The environmental effect strongly influenced FeC and ZnC . The environment Brasília/rainy season was selected as the best evaluation site for preliminary tests for FeC and ZnC, because it resulted in similar conclusions as the mean of the five environments. The lines CNFP 15701 and CNFC 15865 had higher FeC and ZnC and were highly adaptable and stable, and are recommended for utilization in breeding programs. The lines CNFC 15833, CNFC 15703, and CNFP 15676 showed excellent combined agronomic and nutritional traits, and were selected for the development of biofortified cultivars. Additionally, the genetic association between FeC and ZnC was detected.
The iron concentration (FeC) and zinc concentration (ZnC) in common bean grain are quantitative traits, and appropriate breeding techniques are required to achieve genetic gain. The aim of this study was to obtain a recurrent selection population of black bean to increase the FeC and ZnC in the grain and to select the superior progenies for formation of the next cycle and obtain lines. The base population was formed by crosses among ten parents. A total of 351 progenies were obtained, and, after two generations of selection, the 27 best progenies were evaluated in two field trials for FeC, ZnC, 100 seed weight and yield. Analyses of variance were carried out and genetic parameters were estimated. The heritability estimates ranged from 59 to 94% for the four traits. The estimates of expected gain from direct selection for each trait (3 to 21%) and simultaneous selection (1 to 4%) indicate success from selection. The eight progenies, selected based on simultaneous selection, have superior mean values, including to those of 'BRS Supremo' (10% for FeC, 8% for ZnC, 5% for 100 seed weight and 3.8% for yield), the Brazilian black bean cultivar with the highest FeC and ZnC. The recurrent selection population shows high genetic variability and potential for obtaining lines superior to the cultivars currently on the market, allying high agronomic performance and high FeC and ZnC in the grain. Furthermore, this population shows potential for generating a new recurrent selection cycle, from recombination of the eight superior progenies.
The root system architecture (RSA) of plants and its functioning play a fundamental role in a number of plant growth mechanisms including water and nutrient uptake. Optimization of the RSA is important for stable and increased plant productivity under adverse conditions. Despite its great importance, studying the RSA is notoriously laborious because of the difficulty of accessing the rooting system of plants. We developed a root phenotyping platform, PhenoRoots, which allows for the non-invasive study of plant RSA. The system was built using inexpensive material and was designed to provide medium throughput. Substrate or soil-filled rhizotrons are used to grow plantlets, whose roots are directly visible through a glass plate. An experiment conducted on a panel of twenty Upland cotton (Gossypium hirsutum L.) varieties demonstrated the usefulness of the platform in assessing RSA traits. A number of traits, destructive and nondestructive, related to the RSA were measured and statistically analyzed. The non-destructive traits based on image analysis of roots were more accurate and showed high correlation with the time-consuming destructive measurements. The platform allowed for capturing the phenotypic and genetic variability found in the panel of cotton varieties, and to define three contrasting RSA patterns. PhenoRoots provides an inexpensive alternative to the medium throughput analysis of RSA traits in plants.
The aim of common bean (Phaseolus vulgaris) breeding has always been to increase agronomic quality. Recently, the nutritional quality of the grain has been gaining importance. The aim of this study was to estimate genetic parameters for traits related to nutritional and agronomic quality and to select lines for an assessment stage in multiple environments and/or for use as new parents. Initially, 37 lines were evaluated in three environments for nine agronomic and nutritional traits. Of these lines, 15 stood out and were assessed in another five environments. The mixed model (restricted maximum likelihood-best linear unbiased prediction) procedure and multivariate analysis were adopted for processing the phenotypic data. There was genetic variability among the lines assessed for all the traits. The heritability estimates for the agronomic traits ranged from 29% for plant architecture to 94% for reaction to anthracnose. Heritability estimates for the nutritional traits were 77% for grain iron concentration and 79% for zinc concentration. Multivariate analysis, based on all the traits and on all the environments (eight), identified three groups of lines and allowed selection of the lines CNFC 18092, CNFC 18097, CNFC 18114, and BRS Sublime to carry out new crosses, for they showed specific superiority for some traits and the possibility of greater genetic diversity in the populations. The lines CNFC 18091, CNFC 18092, and CNFC 18106 were selected for assessment in experiments in multiple environments because they combine high agronomic and nutritional quality. INTRODUCTIONCommon (dry, edible) bean (Phaseolus vulgaris) is one of the main crops grown and consumed in Brazil, representing the Abbreviations: 100SW, 100-seed weight; ALS, reaction to angular leaf spot; AN, reaction to anthracnose; ARC, plant architecture; BLUP, best linear unbiased prediction; CFe, concentration of iron in the grain; CZn, concentration of zinc in the grain; GA, grain appearance; LOD, plant lodging; REML, restricted maximum likelihood.
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