Rhiannon Schneider, Horticulture and Crop Science, The Ohio State University, Columbus, OH, Leah McHale, Horticulture and Crop Science, Ohio State University, Columbus, OH and Anne E. Dorrance, Plant Pathology, Ohio State University, Wooster, OH
Phytophthora root and stem rot of soybean (Glycine max), caused by the oomycete pathogen Phytophthora sojae can cause devastating yield losses in soybean amounting to ~$300 million dollars annually in the US. While numerous cultivars exist with race-specifc resistance to P. sojae, the extensive diversity of pathogen populations often make these sources of genetic resistance ineffective. In contrast, partial resistance to P. sojae is a complex trait expressed quantitatively and controlled by multiple genes, each contributing to a small portion of the variation observed in populations segregating for partial resistance. Partial resistance is theoretically effective against all races of P. sojae and is considered to be more durable than race-specific resistance (Rps genes) because it does not place strong directional selection on the P. sojae populations. Although North American cultivars generally have low levels of partial resistance to P. sojae, cultivars developed from the Ohio State University (OSU) are expected to have higher partial resistance because they are trialed in regions where Phytophthora root and stem rot is common. In addition, plant introductions (PIs) from South Korea, a region of genetic diversity for soybean, frequently exhibit high levels of partial resistance. The objective of this study is to evaluate partial resistance to P. sojae in three populations: 1) 103 key North American cultivars from each decade (courtesy of Dr. Brian Diers, U of Illinois), 2) 202 cultivars and lines from the OSU soybean breeding program, 3) 1,470 PIs from South Korea. Partial resistance was evaluated via layer test with root rot score and shoot and root dry weight recorded for inoculated and non-inoculated seedlings. The data from this study will be applied to selection of parental lines and among breeding lines and, in combination with genotypic data, can be applied to association mapping and evaluation of genomic selection methods.