Calibrating and Validating the Use of Rising Plate Meter to Estimate Herbage Mass in Multispecies Swards

ABSTRACT Grazing management critically depends on practical, efficient, and parsimonious methods for estimating herbage mass to enable prompt decision‐making under diverse pasture conditions. This study evaluated the rising plate meter (RPM) as a rapid, non‐destructive tool for herbage mass estimation in multispecies swards (MSS) compared to perennial ryegrass (PRG) and PRG–white clover (PRGWC) swards. Five field trials at three Irish sites produced a dataset of 1220 observations (herbage mass range per harvest: 310–3991 kg DM ha −1 ). Five calibration models were developed and compared: Model 1 used a fixed multiplier approach (herbage height [HH] × 250); Model 2 included HH; Model 3 incorporated HH and sward type; Model 4 included HH and season and Model 5 incorporated HH, season and sward type along with their interaction. Model 5 achieved the highest statistical performance with the lowest root mean square error (RMSE; 244 kg DM ha −1 ), highest coefficient of determination ( R 2 ; 0.81) and lowest AIC value demonstrating the theoretical benefit of including seasonal and sward‐specific effects. However, Model 1, while slightly less accurate (RMSE = 277 kg DM ha −1 ; R 2 = 0.75), performed robustly despite its greater parsimony and ease of use. For routine on‐farm decision‐making, the marginal improvements provided by Model 5 may not justify its added complexity. These results suggest that the simple RPM calibration equations can provide herbage mass estimation in MSS that are no less effective than those used in PRG and PRGWC systems.

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Publication Details

Journal
Grass and Forage Science
Published
2025-12-01
DOI
https://doi.org/10.1111/gfs.70030
Primary Topic
Soil Geostatistics and Mapping
Type
article
Field-Weighted Citation Impact
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article

Calibrating and Validating the Use of Rising Plate Meter to Estimate Herbage Mass in Multispecies Swards

John A. Finn, Shona Baker, Helen Sheridan, Israel Ikoyi et al.
Grass and Forage Science
Soil Geostatistics and Mapping
article

Calibrating and Validating the Use of Rising Plate Meter to Estimate Herbage Mass in Multispecies Swards

John A. Finn, Shona Baker, Helen Sheridan, Israel Ikoyi, Cornelia Grace, M.B. Lynch, Guylain Grange, Jane Shackleton
article en

Abstract

ABSTRACT Grazing management critically depends on practical, efficient, and parsimonious methods for estimating herbage mass to enable prompt decision‐making under diverse pasture conditions. This study evaluated the rising plate meter (RPM) as a rapid, non‐destructive tool for herbage mass estimation in multispecies swards (MSS) compared to perennial ryegrass (PRG) and PRG–white clover (PRGWC) swards. Five field trials at three Irish sites produced a dataset of 1220 observations (herbage mass range per harvest: 310–3991 kg DM ha −1 ). Five calibration models were developed and compared: Model 1 used a fixed multiplier approach (herbage height [HH] × 250); Model 2 included HH; Model 3 incorporated HH and sward type; Model 4 included HH and season and Model 5 incorporated HH, season and sward type along with their interaction. Model 5 achieved the highest statistical performance with the lowest root mean square error (RMSE; 244 kg DM ha −1 ), highest coefficient of determination ( R 2 ; 0.81) and lowest AIC value demonstrating the theoretical benefit of including seasonal and sward‐specific effects. However, Model 1, while slightly less accurate (RMSE = 277 kg DM ha −1 ; R 2 = 0.75), performed robustly despite its greater parsimony and ease of use. For routine on‐farm decision‐making, the marginal improvements provided by Model 5 may not justify its added complexity. These results suggest that the simple RPM calibration equations can provide herbage mass estimation in MSS that are no less effective than those used in PRG and PRGWC systems.

Grass and Forage ScienceVol. 80(4)
University College Dublin (IE), Teagasc - The Irish Agriculture and Food Development Authority (IE), University College Cork (IE), Shannon Applied Biotechnology Centre (IE)
Openalex Percentile: Top 61%
Soil Geostatistics and Mapping
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