Genetic resources of vegetable crops: a survey in the Brazilian germplasm collections pictured through papers published in the journals of the Brazilian Society for Horticultural Science

Abstract

The research on plant genetic resources is essential for the conservation of genetic diversity and accessions' divergence studies, as a basis for plant breeding. Aiming to know the state of art in this subject, a historical survey was carried out in Revista de Olericultura and in Horticultura Brasileira, from 1961 to 2006, searching for papers dealing with vegetable crops genetic resources. In each of the papers, the species studied, first author institution, publication year, applied software, number of accessions and descriptors, and the multivariate techniques used were registered. Based on these characteristics, papers were grouped using multivariate analysis. Sixty-one papers dealt somehow with genetic resources in the time covered by the survey, from which 91.8% were published after 1990 (60.7% from 2001 to 2005). The use of multivariate analysis was reported in 57.3% of the papers, with an average of 2.3 and maximum of 6 multivariate procedures per paper. The Tocher Method, reported in 34% of the papers, was the most frequently used multivariate analysis. Twenty-five species were studied. Capsicum was the most frequently studied genus, either considering number of papers (seven) or accessions (664). Research institutions located in the Southeast region concentrated the highest number of papers. UFV (Federal University of Viçosa), UENF (North Fluminense State University Darcy Ribeiro), Embrapa Vegetables, and UNESP (São Paulo State University) Campus of Jaboticabal responded for 45% of the papers. There was an improvement in the adequacy of the statistical techniques used along time, due mainly to the development of free-access software. The software Genes was the most frequently reported in the papers surveyed. Nevertheless, almost 50% of the authors did not mention the software used for data analysis. Quantitative morphoagronomic and evaluation descriptors were the most often used. The multivariate analysis allowed grouping the papers in nine clusters.

Heirloom tomato gene bank: assessing genetic divergence based on morphological, agronomic and molecular data using a Ward-modified location model

“…The classification of individuals and quantification of genetic diversity in gene banks is usually aimed at the identification of similarity groups based on separate analyses of continuous (e.g., plant height, fruit weight, days to flowering) and discrete variables (such as fruit color and shape, the presence or absence of a trait, or a molecular marker) (Mohammadi and Prasanna, 2003;Crossa and Franco, 2004;Sudré et al, 2007). The joint analysis of these variables is, however, becoming an interesting alternative for both breeders and gene bank curators for a better quantification of genetic variability.…”

Uso do algoritmo de Gower na determinação da divergência genética entre acessos de tomateiro do grupo cereja

“…Entretanto, estes acessos, mantidos em bancos de germoplasma, devem ser caracterizados e avaliados com o objetivo de se predizer o grau de dissimilaridade entre os acessos, para se permitir melhor compreensão da coleção de germoplasma e se possibilitar a identificação de combinações parentais que produzam progênies com o máximo de variabilidade genética, aumentando-se, assim, a oportunidade de obtenção de indivíduos superiores (REIF et al, 2005;GONÇALVES et al, 2008b;SUDRÉ et al, 2010).…”

“…Análises multivariadas são baseadas em algoritmos, ou medidas de distância, que consideram simultaneamente inúmeras características consideradas nos experimentos de caracterização e avaliação de germoplasma (SUDRÉ et al, 2007;VILELA et al, 2008). Entre as técnicas disponíveis, a análise por componentes principais, por variáveis canônicas e os métodos aglomerativos são os mais utilizados (MOHAMMADI;PRASANNA, 2003).…”

“…Este método permite que valores da matriz de distância fiquem compreendidos entre 0 e 1, sendo necessária a padronização das variáveis quantitativas e qualitativas. Alguns trabalhos, que se utilizam desta abordagem, são relatados como, por exemplo, os estudos feitos com Brassica napus L. (RODRIGUEZ et al, 2005), com Triticum aestivum L. (VIEIRA et al, 2007) e com Solanum lycopersicum (GONÇALVES et al, 2008b).…”

Integration of quantitative and qualitative descriptors for genetic diversity studies of watermelon accessions

“…A survey of publications on vegetable genetic resources conducted by Sudré et al (2007) revealed that qualitative data are poorly exploited in genetic diversity analyses and are frequently analyzed only by descriptive statistical procedures. In addition, when dissimilarity measures are calculated based on these descriptors, no joint analysis of qualitative and quantitative data is performed, especially in characterizations of more than one assay, which limits the interpretation of results.…”