|Sun, Zhanyong Sun - UNIV OF WISCONSIN|
|Lower, Richard - UNIV OF WISCONSIN|
Submitted to: HortScience
Publication Type: Abstract Only
Publication Acceptance Date: July 15, 2004
Publication Date: August 20, 2004
Citation: Sun, Z., Lower, R., Staub, J.E. 2004. Variance component analysis of parthenocarpic character in a processing cucumber (Cucumis sativus l.) population [abstract]. Hortscience. 39:402. Technical Abstract: The incorportation of genes for parthenocarpy (production of fruit without fertilization) has potential for increasing yield in pickling cucumber (Cucumis sativus L.). The inheritance of parthenocarpy in cucumber is not well understood, and thus a genetic analysis was performed on F3 cross-progeny resulting from a mating between the processing cucumber inbred line 2A (P1, gynoecious, parthenocarpic, indeterminate) and line Gy8 (P2, non-gynoecious, parthenocarpic, indeterminate). A variance component analysis was performed to fruit yield data collected at two locations (designated E-block and G-block) at Hancock, WI in 2000. The relative importance of additive genetic variance compared to dominance genetic variance changed across environments. The additive genetic variance was 0.5 and 4.3 times of dominance genetic variance in E-block and G-block, respectively. The estimated environmental variance accounted for about 90% of the total phenotypic variance on an individual plant basis in both locations. Narrow-sense heritability estimated on an individual plant basis ranged from 0.04 (E-block) to 0.12 (G-block). Broad-sense heritability estimated on an individual plant basis ranged from 0.12 (E-block) to 0.15 (G-block). The minimum number of effective factors controlling parthenocarpy was estimated to range between 5 (G-block) to 13 (E-block). These results suggest that the response to direct selection of individual plants for improved parthenocarpy character will likely be slow and difficult. Experiment procedures that minimize the effect of environment on the expression of parthenocarpy will likely maximize the likelihood of gain from selection.