# Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Rising Platemeter

^{2}, which falls freely onto the vegetation [26]. The microsonic sensor records the time difference between the transmission of a signal and its reflective return from the plate. The higher the upward displacement of the metal plate, the shorter the time between transmission and return of the reflected signal [27]. The recorded time is then translated into a distance measurement given as mm. The second output of the system is the predicted available herbage mass (kg dry matter (DM)/ha). Data is transferred via Bluetooth to a smartphone or tablet device. More details regarding the sensor system can be found in [26,27]. Available herbage mass is estimated from measured CSH (mm), the targeted residual sward height (cm), and an assumed DM concentration of herbage (g/kg fresh matter). The internal equation (further referred to as the original equation) has been developed for homogeneous, cultivated pastures with perennial ryegrass.

#### 2.2. Sampling of the Pasture Herbage

^{2}(Trials 2, 3, and 4) or 1.00 m

^{2}(Trials 1, 5, 6, and 7), which represent the sampling area, were placed randomly within a representative part of the pastures, avoiding dung patches. Within Trials 1, 5, 6, and 7, those frames were also placed within pasture exclusion cages. Those cages were built to simulate the grass regrowth on pasture, preventing cattle from grazing. The vegetation inside and outside of the cages was repeatedly sampled every 2–12 weeks over the grazing season, depending on the trial.

^{3}) from the CSH of harvested herbage (=herbage mass (kg DM/ha)/(CSH (cm) × 100)).

^{®}U23 Pro External Temperature/Relative Humidity Data Logger for measuring the ambient air temperature. Precipitation was recorded by a HOBO

^{®}Rain Gauge (Metric) Data Logger RG3-M (Onset Computer Corporation, Bourne, MA, USA). Missing data, especially annual values, were supplemented similarly to all climate data in Trials 2, 3, and 4 by values derived from close-by weather stations (WetterKontor GmbH, Ingelheim am Rhein, Germany).

#### 2.3. Statistical Analysis

^{3}. A Grubb outlier test [31] was performed thereafter to remove the statistical outliers. As a result, the final dataset, further referred to as dataset 1, was used to evaluate and improve predictions of available herbage mass and consisted of 1511 observations after removing n = 603 (28.5%) of individual observations that were considered illogical values or outliers. Those values were not equally distributed across trials (Table 1).

## 3. Results

#### 3.1. Evaluation of the Original Equation Using Measured or Constant Dry Matter Concentration

#### 3.2. Development of a New Equation

## 4. Discussion

#### 4.1. Existing Equation Is Not Valid for Seminatural, Multispecies Pastures

#### 4.2. Selected Variables for the New Equation

^{2}did not improve substantially, or they were strongly correlated with input variables already retained in the model.

#### 4.3. Adequacy of the Newly Developed Equation

^{2}of 0.71 and greater than those in previous research focusing on multispecies grasslands. Hence, R

^{2}values of herbage mass predictions by rising platemeters were only 0.31, 0.35 to 0.83, and 0.63 in studies by Sanderson et al. [49], Martin et al. [19], and Litherland et al. [50] for mixed species grasslands in the USA, Canada, or New Zealand, respectively. Instead, adequacy and precision were similar or only slightly poorer than those reported for homogenous perennial ryegrass grasslands in previous studies testing platemeters or other indirect sensor systems. For instance, Klootwijk et al. [23] determined that predictions of available herbage mass on intensively grazed perennial ryegrass pastures in the Netherlands by a rising platemeter had a RMSE of 25–31% of the observed herbage mass with an R

^{2}value of 0.83. A similar study in Ireland on trial plots and grazed paddocks dominated by perennial ryegrass found that a rising platemeter predicted herbage mass with an error of 354 kg DM/ha and a residual prediction error of 27.1% [9].

## 5. Conclusions

^{2}= 0.71) may be compensated by increasing the number of measurements per paddock and by establishing a standardized protocol. Together with the development of reliable and robust sensor technologies, the improved precision and adequacy would help to implement digital solutions to grazing management to contribute to a more sustainable and resilient forage use.

## Supplementary Materials

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Relationships between observed and predicted herbage mass on temperate seminatural, multispecies pastures when predicted with the original Equations (1) and (2)

^{1}(dataset 1; n = 1511 observations).

^{1}Equation (1) considers fixed values for herbage dry matter concentrations (i.e., 16 g/100 g fresh matter) and residual sward height (i.e., 4 cm); Equation (2) considers the measured herbage dry matter concentration and a fixed residual sward height (i.e., 4 cm).

**Figure 2.**Relationships between observed and predicted herbage mass on temperate seminatural, multispecies pastures when predicted with the original Equations (1) and (2)

^{1}based on the grouped dataset per paddock (dataset 2; n = 360 observations).

^{1}Equation (1) considers fixed values for herbage dry matter concentrations (i.e., 16 g/100 g fresh matter) and residual sward height (i.e., 4 cm); Equation (2) considers the measured herbage dry matter concentration and a fixed residual sward height (i.e., 4 cm).

**Figure 3.**Observed herbage mass plotted against the residuals in % of the observed herbage mass, including the mean bias (solid line) and the 90% confidence interval (dashed lines) per category (<500, 500–1000, 1000–1500, 1500–2000, 2000–2500, and >2500 kg dry matter/ha; n = 1511).

**Table 1.**Origin and conditions of data collection used to validate an original equation and develop a new equation of a commercial microsonic-based rising platemeter to estimate herbage mass on seminatural, multispecies pastures in Central Europe (arithmetic mean ± one standard deviation (when available)).

Trial | Year | Farms (n) | Altitude (m above Sea Level) | Annual Precipitation ^{1} (mm) | Annual Ambient Air Temperature ^{1} (°C) | Number of Paddocks (n) | Paddock Size (ha) | Sampling Area (m ^{2}) | Measurement Points er Sampling (n) | Observations per Trial before Cleaning (n) | Observations per Trial after Cleaning (n) | Sample Drying |
---|---|---|---|---|---|---|---|---|---|---|---|---|

1 | 2019 | 7 | 580 ± 202 | 975 ± 104 | 9.9 ± 1.2 | 4 ± 2.8 | 3.0 ± 1.7 | 1.00 | 5 | 287 | 220 | 45 °C 72 h |

2 | 2019 | 1 | 682 | 1212 | 8.4 | 1 | 3.0 | 0.25 | 3 | 283 | 264 | 100 °C 24 h |

3 | 2019 | 2 | 1087 ± 202 | 1174 | 7 | 5 ± 0.5 | 9.3 ± 2.5 | 0.25 | 5 | 533 | 482 | 60 °C 48 h |

4 | 2019 | 1 | 534 | 1878 | 10.5 | 1 | - | 0.25 | 3 | 39 | 37 | 60 °C 48 h |

5 | 2020 | 7 | 536 ± 206 | 774 ± 79 | 10.1 ± 1.1 | 3 ± 2.8 | 4.0 ± 1.3 | 1.00 | 5 | 429 | 290 | 45 °C 72 h |

6 | 2020 | 4 | 916 ± 80 | 1143 | 8.4 | 3 ± 0.5 | 7.8 ± 2.1 | 1.00 | 5 | 305 | 113 | 45 °C 72 h |

7 | 2021 | 4 | 919 ± 72 | 1324 | 6.9 | 2 ± 0.7 | 8.9 ± 4.0 | 1.00 | 5 | 238 | 105 | 45 °C 72 h |

^{1}Annual weather data were derived from weather stations close to each farm (WetterKontor GmbH, Ingelheim am Rhein, Germany) and were averaged per trial.

**Table 2.**Descriptive statistics of the dependent and independent variables related to agroecological conditions, management, and available herbage mass on temperate seminatural, multispecies pastures in Central Europe (n = 1511).

Dependent Variable | Mean | Standard Deviation | Min | Median | Max | |
---|---|---|---|---|---|---|

Herbage mass | kg dry matter/ha | 1218 | 774 | 59 | 1088 | 3538 |

Independent variables | ||||||

Month | from 0 to 12 | 7 | 2 | 4 | 7 | 11 |

Week | from 0 to 52 | 30 | 8 | 17 | 29 | 45 |

Altitude | m above sea level | 799 | 284 | 302 | 807 | 1297 |

Precipitation ^{1} | mm | 88.6 | 46.9 | 0.4 | 77.3 | 285.4 |

Annual precipitation | mm | 1100 | 219 | 665 | 1174 | 1878 |

Mean ambient air temperature ^{1} | °C | 13.6 | 4.5 | 3.5 | 15.2 | 20.6 |

Annual temperature | °C | 8.7 | 1.3 | 6.9 | 8.4 | 11.5 |

Canopy cover | % | 91 | 8 | 70 | 90 | 100 |

CSHpre | mm | 83.2 | 39.0 | 4.2 | 79.0 | 215.4 |

CSHpost | mm | 40.5 | 16.2 | 0.2 | 38.6 | 103.8 |

CSHpre-CSHpost | mm | 42.7 | 29.7 | 0.8 | 34.8 | 163.2 |

Dry matter | g/100 g fresh matter | 26.0 | 7.8 | 7.0 | 24.0 | 50.0 |

Density | kg ha/m^{3} | 141 | 61 | 50 | 134 | 465 |

Season | spring (18%), summer (52%), autumn (30%) | |||||

Sampling position | inside the cage (16%), outside the cage (84%) | |||||

Botanical composition | grass-rich (18%), herb-rich (33%), balanced (49%) | |||||

Slope | flat (33%), hilly (43%), steep (24%) | |||||

Grazing system | continuous (7%), rotational (71%), short grass (22%) |

^{1}two weeks prior sampling; CSHpre, compressed sward height before cutting; CSHpost, compressed sward height after cutting.

**Table 3.**Comparison of observed and predicted herbage mass using original Equations (1) and (2)

^{1}, and the newly developed equation based on multiple linear regression (Equation (3)) using dataset 1 (n = 1511).

Observed Herbage Mass | Predicted Herbage Mass | MSPE | CCC | |||||||
---|---|---|---|---|---|---|---|---|---|---|

Equation | RMSE | RMSE | ECT | ER | ED | CCC | ρ | Cb | ||

(kg DM/ha) | (kg DM/ha) | (kg DM/ha) | (% of Observed Herbage Mass) | (% of MSPE) | (% of MSPE) | (% of MSPE) | From −1 to 1 | From −1 to 1 | From 0 to 1 | |

1 | 1218 | 1223 | 540 | 44.3 | 0.01 | 24.97 | 75.03 | 0.79 | 0.80 | 0.99 |

2 | 1218 | 1923 | 1291 | 106.0 | 29.83 | 53.74 | 16.43 | 0.51 | 0.74 | 0.69 |

3 | 1218 | 1218 | 421 | 34.6 | - | - | - | 0.83 | 0.84 | 0.98 |

^{1}Equation (1) considers fixed values for herbage DM concentrations (i.e., 16 g/100 g fresh matter) and residual sward height (i.e., 4 cm); Equation (2) considers the measured herbage DM concentration and a fixed residual sward height (i.e., 4 cm). DM, dry matter; RMSE, root mean squared error; MSPE, mean squared prediction error and its partitioning into error due to central tendency (i.e., overall bias; ECT), error due to regression (ER), and error due to disturbance (i.e., random error; ED); CCC, concordance correlation coefficient; ρ, Pearson correlation coefficient; Cb, bias correction factor coefficient.

**Table 4.**Comparison of observed and predicted herbage mass using original Equations (1) and (2)

^{1}using the grouped dataset per paddock (dataset 2; n = 360 observations).

Observed Herbage Mass | Predicted Herbage Mass | MSPE | CCC | |||||||
---|---|---|---|---|---|---|---|---|---|---|

Equation | RMSE | RMSE | ECT | ER | ED | CCC | ρ | Cb | ||

(kg DM/ha) | (kg DM/ha) | (kg DM/ha) | (% of Observed Herbage Mass) | (% of MSPE) | (% of MSPE) | (% of MSPE) | From −1 to 1 | From −1 to 1 | From 0 to 1 | |

1 | 948 | 1096 | 452 | 47.7 | 10.81 | 36.51 | 52.69 | 0.84 | 0.88 | 0.95 |

2 | 948 | 1619 | 1068 | 112.7 | 39.49 | 49.59 | 10.92 | 0.58 | 0.86 | 0.68 |

^{1}Equation (1) considers fixed values for herbage DM concentrations (i.e., 16 g/100 g fresh matter) and residual sward height (i.e., 4 cm); Equation (2) considers the measured herbage DM concentration and a fixed residual sward height (i.e., 4 cm). DM, dry matter; RMSE, root mean squared error; MSPE, mean squared prediction error and its partitioning into error due to central tendency (i.e., overall bias; ECT), error due to regression (ER), and error due to disturbance (i.e., random error; ED); CCC, concordance correlation coefficient; ρ, Pearson correlation coefficient; Cb, bias correction factor coefficient.

**Table 5.**Statistical parameters and coefficient estimate of the newly developed multiple linear regression equation to estimate the herbage mass (kg dry matter/ha) on temperate seminatural, multispecies pastures in Central Europe.

Variable | Unit | Estimate | SE | p-Value |
---|---|---|---|---|

Intercept | kg dry matter/ha | −1754 | 132.0 | <0.01 |

CSH_{pre} | mm | 17.7 | 0.52 | <0.01 |

Slope | ||||

flat | 0 | - | - | |

hilly | 140 | 62.7 | 0.03 | |

steep | 134 | 71.1 | 0.06 | |

Cover | % | 15 | 1.5 | <0.01 |

Altitude | m above sea level | 0.39 | 0.05 | <0.01 |

CSH_{pre} × Slope | ||||

flat | 0 | - | - | |

hilly | −3.5 | 0.66 | <0.01 | |

steep | −4.9 | 0.77 | <0.01 | |

Adjusted R^{2} | 0.71 | |||

RMSE | 421 kg dry matter/ha; 35% of observed mean | |||

MAPE | 316 kg dry matter/ha; 35% of observed mean |

_{pre}, compressed sward height before cutting; RMSE, root mean squared error; MAPE, mean absolute percentage error; SE, standard error.

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**MDPI and ACS Style**

Werner, J.; Salazar-Cubillas, K.; Perdana-Decker, S.; Obermeyer, K.; Velasco, E.; Hart, L.; Dickhoefer, U.
Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures. *Sensors* **2024**, *24*, 2326.
https://doi.org/10.3390/s24072326

**AMA Style**

Werner J, Salazar-Cubillas K, Perdana-Decker S, Obermeyer K, Velasco E, Hart L, Dickhoefer U.
Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures. *Sensors*. 2024; 24(7):2326.
https://doi.org/10.3390/s24072326

**Chicago/Turabian Style**

Werner, Jessica, Khaterine Salazar-Cubillas, Sari Perdana-Decker, Kilian Obermeyer, Elizabeth Velasco, Leonie Hart, and Uta Dickhoefer.
2024. "Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures" *Sensors* 24, no. 7: 2326.
https://doi.org/10.3390/s24072326