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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #291062
Title: Application of a rising plate meter to estimate forage yield on dairy farms in PA

Author
item Orr, Aimee
item Soder, Kathy
item Rubano, Melissa
item Stout, Robert

Submitted to: Joint Abstracts of the American Dairy Science and Society of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: 4/1/2014
Publication Date: 7/20/2014
Citation: Orr, A.N., Soder, K.J., Rubano, M.D., Stout, R.C. 2014. Application of a rising plate meter to estimate forage yield on dairy farms in PA[Abstract]. Joint Abstracts of the American Dairy Science and Society of Animal Science. 96 (E-Suppl. 1):87.

Interpretive Summary: An interpretive summary is not required.

Technical Abstract: Accurately assessing pasture forage yield is necessary to budget feed expenses. The rising plate meter (RPM) is a rapid method of estimating dry matter (DM) forage yield but calibrations and equations provided by manufactures may be unreliable. The objective of this study was to evaluate the ability of a RPM to accurately estimate pasture forage yield on dairy farms with multiple plant species and determine the best calibration equation. The 3 PA farms in this study used rotational grazing with lactating dairy cows. Forage mass was estimated in each pasture, a day prior to grazing, using 45 measurements from a FILIPS RPM (n=180-225 per farm). To measure forage DM yield, 15 clippings (n=60-75 per farm) of 1 m x 10 cm were taken alongside RPM measurements. Visual estimates of botanical composition were made within each pasture to assess species diversity. Equations for estimating pasture forage mass were determined by regressing measured DM yield on the corresponding RPM value. Four calibration equations based on measurements were evaluated: (1) pooled from all farms; (2) by farm; (3) by season (summer or fall); and (4) by farm and season. Two equations provided by the RPM manufacturer were also evaluated: a default and a seasonal equation. Equations were evaluated by regression procedures (PROC REG, SAS) and estimated standard error of prediction (SEP). Measured DM forage yield was 1209, 896, and 2,246 kg ha**-1 for farms 1, 2 and 3, respectively. Grasses made up 23, 44, and 63% of pasture composition; legumes composed 48, 25, and 20%, for the three farms. Equations provided by the manufacturer had the greatest SEP (32 and 38% of measured forage yield, respectively) and low r**2 (0.58 and 0.51, respectively). Error levels for calibration equations 1, 2 and 4 were greater than the 10% level considered acceptable by previous studies (12 to 21 %). The equation considering season had the lowest SEP (9%) and a high r**2 (0.76). Our results indicate that manufacturer equations are unreliable for estimating DM forage yield on farms in PA in pastures with multiple species. Calibration equations should be developed and adjusted for each season to insure the greatest accuracy.