THE EFFECT OF ALTERED ASSIMILATE ALLOCATION AND PARTITIONING DUE TO PCGA2-OXIDASE OVEREXPRESSION ON THE GROWTH AND PERFORMANCE OF CREEPING BENTGRASS (AGROSTIS STOLONIFERA L.) IN FULL SUN AND REDUCED LIGHT

Creeping bentgrass (Agrostis stolonifera L.) is a species commonly used in high maintenance turf areas. When grown under shade conditions, A. stolonifera becomes thin, elongated, and looses stem and root mass which ultimately leads to loss of turfgrass coverage. These responses to light stimuli are mediated, in part, by phytohormones, gibberellins. Suppression of gibberellin levels by overexpression of genes involved in their catabolism has been proven to successfully control plant stature. Gibberellin suppression also alters plant morphology and photosynthetic characteristics. The objective of this study was to determine the effect of runner bean (Phaseolus coccineus) GA2ox gene (PcGA2ox) overexpression (which increases gibberellin catabolism) on creeping bentgrass quality and performance under various light conditions and intense, short mowing height. GA2ox overexpression resulted in superior quality of Ax6549 under all shade treatments by delaying the decline of its color and coverage. Photosynthetic characterization indicated higher photosynthate supply per leaf area unit and enhanced low light use efficiency as potential factors associated with superior performance of Ax6549 under reduced light conditions. However, growth analysis data indicated lower growth efficiency and leaf productivity in Ax6549. Although this appeared to be contradictory to data obtained through photosynthetic characterization, this contradiction could be explained by increased self shading in Ax6549 due to greater leaf width and having a more horizontal leaf orientation. Morphological data did not help clarify the methods of improved performance of Ax6549 under shaded conditions. Whole canopy photosynthetic measurements performed at different cutting heights are likely needed to further explain the incongruities between photosynthetic and growth analysis data.