The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.

Resumo -A coleção de germoplasma de arroz da Embrapa consiste aproximadamente de 10.000 acessos. O objetivo desse trabalho foi estabelecer a Coleção Nuclear (CN) dessa coleção utilizando as informações e dados disponí-veis sobre seus acessos. A estratégia CN foi introduzida no manejo de recursos genéticos vegetais com o principal objetivo de ampliar e sistematizar o uso desses recursos. Uma CN deve ser selecionada procurando reter a variabilidade genética existente na coleção inteira (CI) com um mínimo de redundância. Os acessos da coleção de arroz foram classificados em três estratos: a) variedades tradicionais do Brasil (VT); b) linhagens/ cultivares melhoradas do Brasil (LCM); e c) linhagens/cultivares introduzidas (LCI). As variedades tradicionais foram ainda classificadas segundo o sistema de cultivo (terras altas, várzeas e facultativo). Os três estratos foram representados na Coleção Nuclear, mas ênfase maior foi dada às variedades tradicionais, que constituíram 308 acessos. Os acessos foram alocados para cada sistema de cultivo, proporcionalmente ao produto do logarítmo do número de variedades tradicionais pelo índice de Shannon (medida de diversidade) de cada um deles. A seleção dos acessos foi feita com o auxilio do Sistema de Informação Geográfica (SIG). A CN brasileira de arroz está formada por 550 acessos Termos para indexação: Oryza sativa, SIG, diversidade genética, recursos genéticos, terras altas, várzeas. Constructing a rice core collection for BrazilAbstract -The Rice Germplasm Collection of Embrapa consists of approximately 10,000 accessions. This study aimed to establish a core collection using the currently available information data for those accessions. The strategy Core Collection (CN) was introduced in the management of plant genetic resources with the main purpose of improving the use of these resources. CN should be selected in order to preserve the genetic variability of the whole collection (CI), with minimum redundancy. The accessions within the rice collection were classified into three strata: a) landraces from Brazil (VT); b) breeding materials from Brazil (LCM); and c) introductions (LCI). The landraces were further classified according to crop system (uplands, lowlands and facultative). These three strata were represented in the Core Collection, but more emphasis was considered in representing the landraces, which are represented by 308 accessions. The accessions were allocated, for each crop system, proportionally to the product of the logarithm of the number of landraces by the Shannon Diversity Index (a measure of genetic diversity) within each crop system. Curators and breeders, supported by a Geographical Information System (GIS) made the selection of the accessions. The final Brazilian rice Core Collection consists of 550 accesses.Index terms: Oryza sativa, GIS, genetic diversity, genetic resources, uplands, lowlands. IntroduçãoO arroz (Oryza sativa L.) é cultivado em todos os continentes, sendo um alimento nutritivo na dieta de mais da metade da população mundial. Foi d...

Plant genetic diversity is a major component of any agricultural ecosystem. Thus, it is essential to classify genetic resources properly to conserve, evaluate, and enhance germplasm efficiently. In maize (Zea mays L.), many classification systems have been used for delineating maize races. From the 1980s, with the use of computers, numerical taxonomy became increasingly important and multivariate methods began to be used for classifying genetic resources. The objective of this study was to compare two methods of classification of Uruguayan maize landraces: (i) a preliminary racial classification obtained through visual assessment and (ii) a numerical classification. The numerical classification was conducted by means of a two‐stage classification strategy: first, initial groups were formed by the Ward method and, next, the Modified Location Model (MLM) refined those groups. This classification was compared with the preliminary racial classification by four criteria. The Ward‐MLM strategy generated more homogeneous groups than those corresponding to the preliminary racial classification. The numerical classification maintained the structure of the more differentiated races, but divided the Cateto Sulino race into two more homogeneous groups, each with smaller variance and more differentiated than other groups. Numerical classification produced groups with clearly distinct characteristics, in terms of the numerical variables, and better, in terms of the four criteria used, than those formed on the basis of racial classification. These results will be the basis for an improved racial classification of maize landraces of Uruguay.

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