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.