Plate Meter Research Articles

PSI-5 Effects of Two Rotational Grazing Management Systems on Forage Quality, Forage Availability, and Cow Performance

Abstract The objective was to compare the effects of 2 rotational grazing systems on forage quality, forage availability, and cow performance. Multiparous, fall-calving beef cows (n = 360; BW = 613 ± 66 kg) were stratified by sire, age, body condition score (BCS), and body weight (BW), and allotted to 6 groups. Groups were randomly assigned to 1 of 2 treatments: 8-paddock system rotated every 5 d or 6-paddock system rotated every 7 d. Endophyte-infected tall fescue paddocks (6.1 ha) were grazed in 2 rounds of rotations from April to July. Cow BW and BCS were obtained on d 0, 28, 56, and 84. Forage heights were measured using a rising plate meter before and after grazing. Forage samples were clipped from each paddock prior to grazing for proximate analysis. Data were analyzed using the MIXED procedure of SAS 9.4. During round 1, forage from the 8-paddock system tended (P = 0.07) to have greater percent dry matter (DM), but no differences were detected (P ≥ 0.12) in organic matter (OM), neutral detergent fiber (NDF), acid detergent fiber (ADF), or crude protein (CP). During round 2, forage percent DM tended (P = 0.08) to be greater while CP tended (P = 0.10) to be lesser in the 8-paddock system. Additionally, the 8-paddock system had greater (P ≤ 0.05) forage NDF and ADF than the 6-paddock system, but OM was not different (P = 0.17) in round 2. However, grazing system did not affect (P ≥ 0.21) forage availability after grazing in either round. Cow BW and BCS were not affected (P ≥ 0.18) by grazing system on d 0, 28, 56, or 84. Despite minor differences in forage quality, rotational grazing management system did not impact forage availability or cow performance.

Multi-site calibration and validation of a wide-angle ultrasonic sensor and precise GPS to estimate pasture mass at the paddock scale

Ultrasonic sensors are a tool for pasture biomass measurement but there has been a lack of on-farm validation to prove their practicality and applicability. As a result, uptake of such sensors is still low. This study sought to perform a multi-site and multi-season calibration and validation of a wide-angle, vehicle-mounted, ultrasonic sensor gathering data while the unit was used in motion on seven commercial dairy farms. This was facilitated by the integration of the ultrasonic sensor, a Real-Time Kinematic Geographic Positioning System (RTK-GPS), and a datalogger into a single system that was attached via a custom bracket to the bull bar of an all-terrain vehicle. The resulting dataset was gathered over a 12-month period, and comprised 1886 reference biomass values from destructive cutting of perennial ryegrass pastures, accompanied by ultrasonic sensor height readings and compressed height readings from a rising plate meter (RPM): a tool that is widely used on commercial farms. The final root mean square errors of prediction (RMSEP) were 1034 and 904 kg DM/ha for Ultrasonic sensor and RPM respectively across all sites and seasons. These were considered high in comparison to previous literature, but this could be attributed to the very broad applicability of the models created. It was also demonstrated that the ultrasonic instrument could be used to create accurate biomass maps for paddocks in the same time taken to survey a whole paddock by RPM, a method that only results in a single paddock average value. Considering the ultrasonic sensor was only slightly less precise and accurate than the RPM at estimating biomass, but considerably more functional in its ability to determine within paddock biomass variation, it was concluded that the ultrasonic sensor was the more informative option.

Dynamic algorithmic conversion of compressed sward height to dry matter yield by a rising plate meter

The strategic allocation of pasture grazing area to dairy cows is essential for optimal management and increased outputs. Rising plate meters are frequently used to estimate pasture herbage mass, i.e. dry matter yield per hectare, by employing simple regression equations that relate compressed sward height to herbage mass. However, to improve the accuracy and precision of these equations, so that inherent variation of grasslands is captured, there is a need to incorporate differences in grass types and seasonal growth. Using a total of 308 grass plots, the variation of growth for both perennial ryegrass and hybrid ryegrass was recorded over the seven-month growing season, i.e. March–September. From these data three dynamic equations were derived. The models showed reduced levels of error in comparison to most other conventional equations. As such, the derived models represent a considerable advance for predictive assessment of herbage mass and will support more efficient grassland utilisation by farmers. Although all equations were found to be highly accurate and precise, only a single equation was considered the most effective (R2 = 0.7; RMSE = 248.05), allowing herbage mass to be predicted reliably from compressed sward height data in relation to ryegrass type and calendar month. Although further research will be required, the results presented allow farm operators to calculate herbage mass, as well as support the development of decision support tools to improve on-farm grassland management, particularly at the local paddock rather than national level.

Exploring the potential of rising plate meter techniques to analyse ecosystem services from multi-species grasslands

Context Continuous grazing in extensive grassland creates grazed and ungrazed patches, which are important for ecosystem service delivery. One possibility for optimising ecosystem services is to target a defined compressed sward height, which can be measured with rising plate meters supplied with internal global navigation satellite system (GNSS) receivers. Aims We assessed the ability of a modern rising plate meter to map long-term patch structure in extensively grazed grassland as a means to improve estimation of phytodiversity at paddock scale as a paramount ecosystem service. Methods The patch class proportions obtained from interpolating the georeferenced compressed sward height values were used to calculate phytodiversity indicators at paddock scale as determined by dry-weight ranking. In addition, a modern rising plate meter with internal GNSS receiver was compared with an established one without GNSS receiver. Key results The mapping of the patch classes revealed decreasing proportions of tall patches with increasing stocking intensity. Phytodiversity at paddock scale depended on the proportions of respective patches, highlighting the importance of accurate mapping of patches for ecosystem service assessment. Conclusions The new rising plate meter extends the utilisation of compressed sward height measurements into a spatial context. Patch size, spatial distribution of patches within a paddock and spatial clustering of patches, as well as repeated mapping over time, can be utilised to detect change and monitor long-term management schemes without the need for sophisticated remote-sensing applications. Implications The combination of the new rising plate meter and dry-weight ranking extends grazing management towards biodiversity monitoring in an easy-to-learn approach.

Evaluating nondestructive forage sampling techniques in alfalfa–bermudagrass mixtures in the southeastern United States

AbstractThe increased use of legume–grass mixtures in grazing systems has resulted in the need for more accurate forage estimation techniques for these diverse mixtures. In mixed stands, variations in species composition and canopy density make the estimation of herbage mass (HM) challenging. Three nondestructive sampling techniques [a rising plate meter (RPM), a pasture ruler, and digital image analysis] were compared with traditional botanical hand separation to determine their effectiveness in predicting HM in bermudagrass [Cynodon dactylon (L.) Pers.] and alfalfa (Medicago sativa L.) pastures when harvested to a 1‐ or 4‐inch stubble height. All models calibrated to forages harvested to 1 inch failed to meet the formal assumptions of the F‐test. The height and RPM were moderately successful at predicting HM when calibrated to samples harvested to 4 inches. However, the models were unable to predict HM above 4,000 lb acre−1 in their current form. Future research in alfalfa–bermudagrass mixtures should focus on isolating how HM changes within the canopy and increase the sample area used to collect the calibration data.

Comparison of virtually fencing and electrically fencing sheep for pasture management

Context Virtual fencing technology has potential for application in intensive grazing management. However, it is unknown whether the presence of the virtual fence will affect the grazing behaviour of sheep under intensive grazing situations. Aims This study compared pasture consumption by sheep when pasture access is restricted using either a virtual fence (n = 12) or a conventional electric fence (n = 12), tested over three cohorts. Methods The sheep were given access to a small section of pasture (8 × 8 m) for approximately 4 h, over a total of 4 days of grazing, being moved onto a fresh plot each day. Within the grazing plot, average pasture dry matter, normalised difference vegetation index (NDVI), and rising plate meter (RPM) height, were measured before and after grazing. NDVI and RPM height were also measured along the fence line before and after grazing. Key results For within plot measures, there was no effect of treatment on biomass (P = 0.42), pasture height (P = 0.69) or NDVI (P = 0.72). The same was observed for measures taken at the fence line. The results of this study indicated that using a virtual fence to restrict access to pasture to create targeted grazing is as effective as using an electric fence. Conclusions The similarity in pasture consumption between the groups indicated that the virtual fence does not affect normal grazing behaviour of sheep, nor discourage them from grazing up to the fence line. Further work should be conducted in larger flocks and using automated systems. Implications Virtual fencing has the potential to be used to restrict sheep access to pasture to create targeted grazing that is as effective as is using an electric fence.

Botanical and mineral composition of dominant wild forages for feeding of dairy goats in Payakumbuh Region

The objectives of this study were (i) to identify the diversity of forages that are usually consumed or fed to the dairy goats, (ii) to assess the mineral composition of dominant forages concerning the soil mineral status of growing areas. Eight dairy goat farms surveyed and collected forage samples to define the diversity and dominant forages used to feed the goat. Samples of three dominant forages (Asystasia gangetica, Axonopus compressus, and Panicum maximum) and soils were then collected in five different areas where the farmers usually derived the forages (banana plantation, idle lands, riverbanks, roadside, and rice field edge). Plant samples were collected by using a plate meter used for the calculation of botanical composition. Fresh samples were then chopped, dried, and then ground in meal form before analysis for dry matter (DM), and minerals of Ca, P, Mg, K, Na, and S. The same minerals were analyzed for soil samples. Data were subjected to analysis of variance (ANOVA) in a completely randomized design of 5x3 consisting of 3 plant species and five growing areas as replications. Data were statistically analyzed using correlation and variance analysis in Random Block Design (RBD). Results showed of the total about 45 types of plants commonly consumed by goats, there were three dominant species, i.e., P. maximum (38.60%), A. gangetica (24.23%), and A. compressus (17.23%). The Ca content of forages highly correlated with the Ca in the soils, while magnesium in the forage was negatively correlated with the magnesium in the soil. It was concluded that the dominant forages were found a good source of Ca and Mg but deficient phosphorus.

Effects of herbage mass and herbage allowance on bite mass of grazing dairy cows

Dry matter intake (DMI) of herbage is a product of bite rate and bite mass and is a determinant of the performance of grazing ruminants. This research tested the effect of herbage allowance and herbage mass on average bite mass of individual dairy cows grazing perennial ryegrass herbage (Lolium perenne L.). Two experiments were conducted, one in each of winter (Experiment 1) and spring (Experiment 2). In each experiment, 24 Holstein-Friesian dairy cows grazed individual perennial ryegrass plots over 10 d. In each experiment cows grazed one of six treatments: low or medium herbage mass (1900 or 2200 kg DM.ha−1 in Experiment 1 and 2200 or 3000 kg DM.ha−1 in Experiment 2) combined with either low, medium or high herbage allowance (15, 25 or 40 kg DM.cow−1.d−1 in Experiment 1 and 20, 30 or 40 kg DM.cow−1.d-1 in Experiment 2). Grazing behaviour was measured with jaw movement sensors and DMI was determined by herbage disappearance measured with a rising plate meter daily, and at hourly intervals during the first 4 h of grazing after the morning milking. Average bite mass (g DM.bite−1) per day and per hour was determined as the mass of herbage that had disappeared in each period (g.d−1 or g. h−1) divided by number of prehension bites in that period. The combined data from two experiments was analysed by Linear Mixed Model and it was found there was no effect of herbage mass (P = 0.686) on bite mass per day. However, cows offered high herbage allowance had greater (P < 0.001) bite mass per day (0.62 g DM.bite-1) than cows offered the lowest herbage allowance (0.38 g DM.bite-1) across both experiments. The effect of herbage allowance was similar across both herbage masses. Bite mass per hour was the highest (P < 0.001) in the first hour of grazing in both experiments with average bite mass per hour across two experiments in the first hour of grazing (0.69 g DM.bite−1) greater than in the second (0.40 g DM.bite−1), third (0.35 g DM.bite−1) and fourth (0.32 g DM.bite−1) hours of grazing. We conclude that herbage allowance is a significant factor in determining bite mass and should be included in models aimed at predicting bite mass and hence daily herbage intake of grazing dairy cows.

45 Effects of Grazing Management Systems on Forage Quality, Forage Availability, and Cow Performance

Abstract The objectives were to compare the effects of two rotational grazing systems on forage quality, forage availability, and cow performance. Multiparous, fall-calving beef cows (n = 360; BW = 597±62 kg) were stratified by body weight (BW), body condition score (BCS), age, and sire and allotted to 6 groups. Groups were randomly assigned to 1 of 2 treatments: 8-paddock system rotated every 5 d or 6-paddock system rotated every 7 d. All paddocks (6.1 ha) contained endophyte-infected tall fescue and were grazed in two rounds. Cow BW and BCS were obtained on d 0, 28, 56, and 84. Forage heights were measured using a rising plate meter upon the groups entering and exiting each paddock. Forage samples were clipped from each paddock for proximate analysis. Data were analyzed using the MIXED procedure of SAS. During the first and second grazing rounds, grazing management system had no effects (P ≥ 0.11) on dry matter, organic matter, neutral detergent fiber, acid detergent fiber, and crude protein of the forage. The 8-paddock system tended (P = 0.09) to have greater forage availability than the 6-paddock system at the end of each rotation in the first round with 3,665 and 3,263 kg DM/ha, respectively. However, grazing system did not affect (P = 0.13) forage availability at the end of the rotation in the second round. Cow BW was not affected (P ≥ 0.63) by grazing system on d 0, 28, or 56. On d 84, cows rotationally grazed through an 8-paddock system had greater (P = 0.04) BW than those who grazed the 6-paddock system. Treatment had no effect (P ≥ 0.37) on BCS at any time point. In conclusion, grazing management system did not affect forage quality; however, the 8-paddock system resulted in greater forage availability which led to greater cow BW.

PSI-3 Effects of Mowing on Forage Availability and Quality During the Summer

Abstract The objective was to determine how mowing date affected forage availability and quality. Cool season grass plots were randomly assigned to 4 treatments (n=2): mowed on day 1 (M1), mowed on day 15 (M15), mowed on day 29 (M29), and not mowed (NM). During the 56-day experiment, forage heights were measured using a rising plate meter to determine forage availability and samples were clipped for proximate analysis. The MIXED procedure of SAS was used to analyze data. On day 14, CP in M1 was 37.5% greater (P = 0.05) than the composite of M15, M29, and NM. However, the composite of M15, M29, and NM had greater (P = 0.02) forage availability than M1 on day 14. On day 28, M15 had greater (P = 0.02) ADF than M1, while the composite of M29 and NM was intermediate and not different than other treatments. There was also a treatment effect (P &amp;lt; 0.01) on forage availability on day 28; the composite of M29 and NM was greatest followed by M1 and M15, respectively. On day 42, the NDF of M29 was greater (P = 0.01) than M1, M15, and NM. Decreased CP was observed (P = 0.05) for NM compared with M1, M15, and M29 on day 42. Forage availability was different (P &amp;lt; 0.01) for all treatments on day 42 with NM being the greatest followed by M1, M15, M29, respectively. On day 56, NM tended (P = 0.08) to have the greatest DM, but there was no difference (P ≥ 0.31) in NDF, ADF, and CP. Forage availability was different (P &amp;lt; 0.01) for all treatments on day 56 with NM being the greatest followed by M1, M15, M29, respectively. In conclusion, mowing reduced forage availability as expected, but it also increased CP on day 14 and 42.

Using multispectral data from an unmanned aerial system to estimate pasture depletion during grazing

Accurate measurement of pasture depletion and, therefore, dry matter intake (DMI) is fundamental in both research and commercial settings for understanding the behaviour and nutrition of grazing animals. Remote sensing technologies such as unmanned aerial vehicles (UAV) equipped with sensors have been used to estimate biomass of crops and un-grazed pastures. The aim of the experiment reported here was to develop and validate empirical models to estimate pasture depletion in paddocks while cattle are grazing using an UAV-borne multispectral sensor with a rising plate meter measurements as the reference data. Data were collected in winter and spring with 24 different cows used in each period and grazing in individual plots. UAV flights were undertaken before cows entered the paddock and then every hour for the first 5 h of grazing coinciding with rising plate meter measurements. Four types of datasets were prepared and compared to determine which produced the best estimate of herbage mass. The first two datasets were created by extracting data from either the cow’s whole AM plot (AP) area, or a small polygon of homogenous data (SP) subjectively chosen from within the AM plot area. A further two training datasets were created by combining either the AM plot data or small polygon data with additional extreme data (EX) collected pre (0 h) and post (24 h) grazing from days before or after the days of UAV measurements. Therefore, the four training datasets compared were AP, SP, APEX and SPEX. The best performing model was the APEX model with a concordance correlation coefficient of 0.67, an r2 of 0.54 and RSME of 406 kg DM/ha in independent validation, however accuracy of estimates decreased with pasture biomass below 1,000 kg DM/ha and above 2,000 kg DM/ha. Dry matter intake estimated using the UAV images and the APEX model had a concordance of 0.39 with the RPM method. The APEX model was also used to demonstrate how this model allowed pasture depletion to be mapped through time during a grazing session. This research has highlighted the potential of using a UAV-borne multispectral imaging system for estimating pasture depletion in paddocks while cows graze, however, we suggest further research is required to improve the accuracy of our models for estimating extreme values of pasture biomass before it can be used to estimate daily DMI.

Utilising grassland management and climate data for more accurate prediction of herbage mass using the rising plate meter

Efficient grass-based livestock production depends on precise allocation of pasture to the herd in the form of herbage mass (HM). Accurate measurement of HM results in increased utilisation of grass in the herd’s diet and consequently reductions in whole-farm feed inputs, emissions and costs. The rising plate meter (RPM) is an established method of estimating HM, but there is scope to improve its accuracy. Real-time meteorological data and pasture management information have never been analysed in combination with the RPM. This study aimed to utilise such data to improve the accuracy of HM prediction using multiple linear regression (MLR) and machine learning through the random forest (RF) algorithm. Seventeen variables were assessed and models were evaluated in terms of relative prediction error (RPE). Decreases of 6–12% RPE were observed for the MLR models compared with conventional models. Further decreases of 11–17% were recorded for RF models. An MLR model comprising of management data that were readily available to farmers was deemed optimum for on-farm use and included coefficients for: compressed sward height (mm), nitrogen fertiliser rate (kg ha−1) and grazing rotation number (RMSE = 324 kg DM ha−1). The addition of meteorological variables resulted in a further 0.9% decrease in RPE (RMSE = 312 kg DM ha−1), but was not practical considering the expense of on-farm meteorological sensors. The RF model with meteorological variables (RMSE = 262 kg DM ha−1) had 1.5% lower RPE compared with the RF model without (RMSE = 243 kg DM ha−1).

62 Effects of forage allowance and supplementation on performance of steers grazing wheat pasture

Abstract A 72-d trial was conducted to estimate the combined effect of forage allowance and a fiber-based energy supplement in stocker cattle grazing wheat. Eight pastures (2.7 to 5.1 ha) each contained seven test steers (initial BW = 210 ± 36 kg). Weekly, additional steers were stocked in each pasture in a put and take method to achieve forage allowance of either 2.5 or 5.5 kg forage DM / kg steer BW (4 pastures each). Two pastures in each forage allowance were fed daily with a supplement containing 50% wheat midds and 50% soybean hulls at the rate of 1.5 kg per steer. Forage mass was measured twice weekly using a calibrated rising plate meter. Cattle were weighed weekly on calibrated scales. Data were analyzed using linear regression with pasture as the experimental unit. Mean ADG was 1.36 kg/d. One pasture in the high forage allowance, non-supplemented treatment was removed because we were unable to maintain the designed forage allowance. The interaction of forage allowance and supplement was not significant (P = 0.37) for ADG, and supplementation did not affect ADG (P = 0.20), however increased forage allowance tended to improve ADG (P = 0.06, 0.21 kg ADG per kg forage allowance). To further investigate forage DMI, a 14-d trial began on day 36. Three of the seven test steers in each pasture were randomly chosen and administered 7 ± 0.1 g of TiO2 daily at 0700 as an external marker to estimate fecal output. Forage DMI (at an assumed 72% DM digestibility) averaged 2.1% of midpoint BW, below our expectation. Additional forage allowance tended to improve estimated forage DMI (P= 0.06), but supplement had minimal effect (P = 0.30).

63 Effects of forage allowance and supplementation on performance of steers grazing wheat pasture

Abstract A 72-d trial was conducted to estimate the combined effect of forage allowance and a fiber-based energy supplement in stocker cattle grazing wheat. Eight pastures (2.7 to 5.1 ha) each contained seven test steers (initial BW = 210 ± 36 kg). Weekly, additional steers were stocked in each pasture in a put and take method to achieve forage allowance of either 2.5 or 5.5 kg forage DM / kg steer BW (4 pastures each). Two pastures in each forage allowance were fed daily with a supplement containing 50% wheat midds and 50% soybean hulls at the rate of 1.5 kg per steer. Forage mass was measured twice weekly using a calibrated rising plate meter. Cattle were weighed weekly on calibrated scales. Data were analyzed using linear regression with pasture as the experimental unit. Mean ADG was 1.36 kg/d. One pasture in the high forage allowance, non-supplemented treatment was removed because we were unable to maintain the designed forage allowance. The interaction of forage allowance and supplement was not significant (P = 0.37) for ADG, and supplementation did not affect ADG (P = 0.20), however increased forage allowance tended to improve ADG (P = 0.06, 0.21 kg ADG per kg forage allowance). To further investigate forage DMI, a 14-d trial began on day 36. Three of the seven test steers in each pasture were randomly chosen and administered 7 ± 0.1 g of TiO2 daily at 0700 as an external marker to estimate fecal output. Forage DMI (at an assumed 72% DM digestibility) averaged 2.1% of midpoint BW, below our expectation. Additional forage allowance tended to improve estimated forage DMI (P= 0.06), but supplement had minimal effect (P = 0.30).

Estimating Plant Pasture Biomass and Quality from UAV Imaging across Queensland’s Rangelands

The aim of this research was to test recent developments in the use of Remotely Piloted Aircraft Systems or Unmanned Aerial Vehicles (UAV)/drones to map both pasture quantity as biomass yield and pasture quality as the proportions of key pasture nutrients, across a selected range of field sites throughout the rangelands of Queensland. Improved pasture management begins with an understanding of the state of the resource base, UAV based methods can potentially achieve this at improved spatial and temporal scales. This study developed machine learning based predictive models of both pasture measures. UAV-based structure from motion photogrammetry provided a measure of yield from overlapping high resolution visible colour imagery. Pasture nutrient composition was estimated from the spectral signatures of visible near infrared hyperspectral UAV sensing. An automated pasture height surface modelling technique was developed, tested and used along with field site measurements to predict further estimates across each field site. Both prior knowledge and automated predictive modelling techniques were employed to predict yield and nutrition. Pasture height surface modelling was assessed against field measurements using a rising plate meter, results reported correlation coefficients (R2) ranging from 0.2 to 0.4 for both woodland and grassland field sites. Accuracy of the predictive modelling was determined from further field measurements of yield and on average indicated an error of 0.8 t ha−1 in grasslands and 1.3 t ha−1 in mixed woodlands across both modelling approaches. Correlation analyses between measures of pasture quality, acid detergent fibre and crude protein (ADF, CP), and spectral reflectance data indicated the visible red (651 nm) and red-edge (759 nm) regions were highly correlated (ADF R2 = 0.9 and CP R2 = 0.5 mean values). These findings agreed with previous studies linking specific absorption features with grass chemical composition. These results conclude that the practical application of such techniques, to efficiently and accurately map pasture yield and quality, is possible at the field site scale; however, further research is needed, in particular further field sampling of both yield and nutrient elements across such a diverse landscape, with the potential to scale up to a satellite platform for broader scale monitoring.

Evaluation of the precision of the rising plate meter for measuring compressed sward height on heterogeneous grassland swards

Accurate estimation of herbage mass (HM) is essential for optimising grass utilisation and increasing profit for pasture-based livestock agriculture. The rising plate meter (RPM) is used for predicting HM based on average compressed sward height (CSH). Sampling resolution and distribution are primary parameters in determining spatial heterogeneity of HM. There is no definitive sampling protocol for the RPM. The objectives of this study were to: investigate spatial variation of HM within pastures, determine the number of RPM measurements required to accurately predict mean HM, and assess the precision of the RPM in terms of measurement repeatability. Intensive CSH measurements and HM reference cuts were carried out on controlled plots and grazed paddocks over two grazing seasons. Sward heterogeneity was estimated as the coefficient of variation (CV) of CSH and compared to empirically derived ‘true’ sward heterogeneity in terms of HM CV. Retrospective analysis simulations were performed to identify the effect of various reduced measurement resolutions on estimated mean CSH error. Repeated measures analysis was performed on grass samples to determine RPM measurement system precision. Results indicated that pasture heterogeneity varied by 36% across the growing season and was affected by grazing, fertilisation, sward composition and seasonality. Mean CSH could be estimated to within 5% relative prediction error by recording 24 measurements per ha in a random stratified manner. The standard deviation of RPM measurement repeatability was calculated to be 4.34 mm. The findings of this study will be used to inform the implementation of a more optimum grass measurement protocol.

Spatial and Temporal Pasture Biomass Estimation Integrating Electronic Plate Meter, Planet CubeSats and Sentinel-2 Satellite Data

There is a substantial opportunity to lift feed utilization and profitability on pasture-based dairy systems through both increased pasture monitoring accuracy and frequency. The first objective of this experiment was to determine the impact of the number of electronic rising plate meter (RPM) readings and walking pattern on the accuracy of the RPM to determine pasture biomass. The second objective was to evaluate current satellite technology (i.e., small CubeSats and traditional large satellites) in combination with the electronic RPM as an accurate tool for systematic pasture monitoring. The experiment was conducted from October to December 2019 at Camden, Australia. Two experimental paddocks, each of 1.1 ha, were sown with annual ryegrass and monitored with an electronic RPM integrated with Global Navigation Satellite System and with two different satellites (Planet CubeSats and Sentinel-2 satellite). Here we show that 70 RPM readings achieve a ± 5% error in the pasture biomass estimations (kg DM/ha), with no effect of the walking pattern on accuracy. The normalized difference vegetation index (NDVI) derived from satellites showed a good correlation with pasture biomass estimated using the electronic RPM (R2 0.74–0.94). Satellite pasture biomass and growth rate estimations were similar to RPM in one regrowth period but underestimated by ≈20% in the other. Our results also reveal that the accuracy of uncalibrated satellites (i.e., biomass estimated using NDVI to kg DM/ha standard equations) is low (R2 0.61, RMSE 566–1307 kg DM/ha). However, satellites calibrated with a RPM showed greater accuracy in the estimations (R2 0.72, RMSE 255 kg DM/ha). Current satellite technology, when used with the electronic RPM, has the potential to not only reduce the time required to monitor pasture biomass manually but provide finer scale measurements of pasture biomass within paddocks. Further work is required to test this hypothesis, both spatially and temporally.

Development of a grass measurement optimisation tool to efficiently measure herbage mass on grazed pastures

Accurate and efficient estimation of herbage mass is essential for optimising grass utilisation and increasing profit for pasture farming. There is no definitive sampling protocol for grass measurement on Irish pastures. This paper presents the Grass Measurement Optimisation Tool (GMOT), designed to generate measurement protocols that optimise for time and accuracy. The GMOT was designed in the form of a decision support tool that generates interactive paddock maps that guide the farmer on how to optimally measure their pastures in a random stratified manner based on GPS co-ordinates, resulting in accurate non-biased estimations of mean herbage mass. Rising plate meter (RPM) measurements and reference herbage cuts were performed on trial plots and grazed paddocks over three years. Measurement routes were optimised using a genetic algorithm based on a traveling salesman problem. Actual survey error was estimated in terms of relative prediction error using Monte Carlo simulations that combined measurement and calibration error distributions for the RPM. Cost benefit analysis was conducted to evaluate the feasibility of using the GMOT on Irish grasslands. Actual error for the RPM decreased from 37% to 26% as measurement rates increased from 1 to 8 ha−1 and reductions in error were negligible (<1%) as measurements increased from 8 to 32 ha−1. Calibration error was the largest source of error (25.9%) compared to measurement error (8%). Optimal measurement value was achieved by performing 8 measures ha−1 and further increasing the measurement rate resulted in diminishing returns. The GMOT is compatible with a range of pasture measurement technologies.

Monitoring Forage Mass with Low-Cost UAV Data: Case Study at the Rengen Grassland Experiment

Monitoring and predicting above ground biomass yield of grasslands are of key importance for grassland management. Established manual methods such as clipping or rising plate meter measurements provide accurate estimates of forage yield, but are time consuming and labor intensive, and do not provide spatially continuous data as required for precision agriculture applications. Therefore, the main objective of this study is to investigate the potential of sward height metrics derived from low-cost unmanned aerial vehicle-based image data to predict forage yield. The study was conducted over a period of 3 consecutive years (2014–2016) at the Rengen Grassland Experiment (RGE) in Germany. The RGE was established in 1941 and is since then under the same management regime of five treatments in a random block design and two harvest cuts per year. For UAV-based image acquisition, a DJI Phantom 2 with a mounted Canon Powershot S110 was used as a low-cost aerial imaging system. The data were investigated at different levels (e.g., harvest date-specific, year-specific, and plant community-specific). A pooled data model resulted in an R2 of 0.65 with a RMSE of 956.57 kg ha−1, although cut-specific or date-specific models yielded better results. In general, the UAV-based metrics outperformed the traditional rising plate meter measurements, but was affected by the timing of the harvest cut and plant community.

A Standard Methodology for Evaluation of Mechanical Maize Seed Meters for Smallholder Farmers Comparing Devices from Latin America, Sub-Saharan Africa, and Asia

Precision planting represents an opportunity for farmers to increase income. Seeders and associated seed meters are prerequisite to achieve optimal plant density. However, to assure seed meter performance in smallholder conditions, a comprehensive procedure is lacking. This study develops a methodology for mechanical maize meter evaluation that compares diverse meters in terms of seed singulation, seed damage, and spatial distribution. An experiment assessed 10 m, representing roller types, and inclined, vertical, and horizontal plates collected from various continents and representative of commonly used devices by smallholders. A conveyer-belt setup allowed for seed distribution analysis and the influence of vibration and topography on the seed singulation was determined. Results revealed that a rotational velocity of 20 revolutions per minute (RPM) was optimum for most meters, while all complied with the norm NMX-O-168-SCFI-2009 in terms of seed damage. Independent of the singulation mechanism, devices with the ability to adjust to seed size performed better. The Fitarelli horizontal plate, followed by the BARI-9 inclined plate meter, are considered ‘best-bet’ performers. Although, considering absolute efficiency, two inclined plate devices worked at near-perfect performance with large seeds. Our study develops a low-cost methodology, easily replicated and implemented, and provides a baseline for continued research on seed meter evaluation.