|Rotz, Clarence - Al|
Submitted to: Agronomy Journal
Publication Type: Peer reviewed journal
Publication Acceptance Date: 1/2/2001
Publication Date: 11/20/2001
Citation: Sanderson, M.A., Rotz, C.A., Fultz, S.W., Rayburn, E.B. 2001. Estimating forage mass with a commercial capacitance meter, rising plate meter, and pasture ruler. Agronomy Journal. 93(6):1281-1286. Interpretive Summary: Accurately measuring pasture yield is key to budgeting forage in grazing systems; however, producers often do not accurately measure pasture yields because they are not convinced that it pays. ARS scientists at University Park, Pennsylvania, in collaboration with farmers and extension specialists in Maryland, West Virginia, and Pennsylvania used the computer model DAFOSYM to simulate the economic effects of inaccuracies in estimating forage production on pasture. Results showed that accurately measuring forage production in pastures can save producers up to $80 per acre of pasture per year, depending on the type of grazing system used. Thus, the use of an accurate method of measuring forage, and regular monitoring of pastures, can substantially reduce production costs for graziers.
Technical Abstract: Accurate assessment of forage mass in pastures is key to budgeting forage in grazing systems. Our objective was to determine the accuracy of an electronic capacitance meter, a rising plate meter, and a pasture ruler in measuring forage mass and to determine the cost of measurement inaccuracy. Forage mass was estimated in grazed pastures on farms in Pennsylvania, Maryland, and West Virginia in 1998 and 1999. Forage mass estimated by each method was compared with forage mass estimated by hand clipped samples. None of these indirect methods were accurate or precise and error levels ranged from 26 to 33% of the mean forage mass measured on the pastures. The computer model DAFOSYM was used to simulate farm performance and the resulting effects of inaccuracies in estimating forage mass on pasture. A representative grazing dairy farm was developed and the costs and returns from "optimum" management were calculated. Different scenarios swere then simulated, including under- or overestimating forage yield on pastures by 10 or 20%. All scenarios simulated resulted in lower returns compared to the optimum farm, with decreases in net return ranging from $8 to $198 ha-1 yr-1. Underestimating forage mass resulted in less hay and silage being harvested, more pasture being consumed, and more forage purchased compared to the optimum scenario. The opposite occurred for overestimation of forage mass. Our results indicate that achieving greater accuracy (to within 10% of actual pasture yield) in estimating pasture yields will improve forage budgeting and increase net returns for the farms.