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Improving Published Descriptions of Germplasm
Author(s) -
White Jeffrey W.,
Dierig David A.
Publication year - 2011
Publication title -
journal of plant registrations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 21
eISSN - 1940-3496
pISSN - 1936-5209
DOI - 10.3198/jpr2010.07.0414opp
Subject(s) - germplasm , pedigree chart , biology , selection (genetic algorithm) , adaptation (eye) , population , database , computer science , demography , agronomy , artificial intelligence , sociology , biochemistry , neuroscience , gene
Descriptions of new germplasm published in the Journal of Plant Registrations ( JPR ), and previously in Crop Science , are important vehicles for informing researchers about advances in plant breeding. Launched in 2007, JPR introduced a format that allowed more detailed descriptions of registrations; however, an informal review suggests that further improvements are possible. This paper explores these suggestions. To support our arguments, we assessed the new format by reviewing 234 papers from JPR , focusing on 106 papers (53 each in the old— Crop Science —and new— JPR —formats) for cultivar releases in 14 self‐pollinated crops. We examined genealogies (pedigrees), breeding processes, experimental techniques, phenotypes, and genotypes. In the new format, there was more extensive information on the chronology of the breeding process, the expected area of adaptation, experimental techniques, the quantification of phenotypes, and citation of web‐based reports. Nonetheless, improvement appeared possible, including by (i) documenting genealogies in databases structured for breeding records; (ii) quantifying the degree of relatedness to other germplasm; (iii) describing the breeding process in tables that include key dates, population types and sizes, and numbers of test environments; (iv) describing adaptation through standardized scales, environmental classifications, or quantitative responses; (v) providing genotypic data; and (vi) providing access to supplementary materials from databases or Internet resources.

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