The 2008 Joint Meeting of the Society for Range Management and the America Forage and Grassland Council.

Thursday, January 31, 2008 - 9:00 AM

Relationship of Sward Height and Herbage Mass for Orchardgrass (Dactylis glomerata L.), Smooth Bromegrass (Bromus inermis Leyss.), and Perennial Ryegrass (Lolium perenne L.) in a Pasture System

Laura K. Hooper1, Glenn E. Shewmaker1, and Thomas C. Griggs2. (1) Department of Plant, Soil and Entomological Sciences, University of Idaho, Twin Fall Research and Extension Center, P. O. Box 1827, Twin Falls, ID 83303-1827, (2) Department of Plants, Soils and Climate, Utah State University, 4820 Old Main Hill, Logan, UT 84322-4820

The prediction of pasture herbage mass can give producers estimates of carrying capacity, stocking rate, stocking density, and regrowth rate. There are limited data describing the relationship of sward height to herbage mass in the western United States. Thus, there is a need to develop dependable equations that can predict biomass production of several forages species. Four Idaho rotationally-grazed, irrigated pastures were sampled in 2006. The mixed grass and legume pastures represented orchardgrass (Dactylis glomerata L.), smooth bromegrass (Bromus inermis Leyss.), and perennial ryegrass (Lolium perenne L.) in mixtures with Medicago and Trifolium spp. Sward height, density, and herbage mass were determined weekly within three densities (60-75%, 75-90%, and 90-100% canopy cover) during the growing season. Grasses were sorted by species, weighed, and oven dried. Preliminary data across species and growth periods indicate a linear increase (r2 = 0.71) in herbage mass with sward height. Combination of sward height with sward density improved the relationship from R2 0.66 to 0.71. Forage mass averaged 148, 189, 155, and 210 kg (ha cm)-1 for bromegrass, mixed orchardgrass/bromegrass, mixed orchardgrass/legume, and mixed ryegrass/orchardgrass, respectively. Factors that influence predictive values are sward density, plant species, and sward height. These regression functions will enable pasture managers in the West to predict and allocate pasture mass based on sward height measurements.