Exploiting the pasture capacitance probe in agricultural research: a comparison with other methods of measuring herbage mass

Crosbie, S. F.; Smallfield, Bruce M.; Hawker, H. W.; Floate, M. J. S.; Keoghan, J.M.; Enright, P.; Abernethy, R.J.

doi:10.1017/s0021859600064224

Cited by 12 publications

(5 citation statements)

References 6 publications

(6 reference statements)

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“…Plots were grazed 3 times a year, a grazing regime suited to Maku lotus (Sheath 1981) and recommended for high country runs (Lowther et al 1987). Intertussock herbage yields before grazing were assessed by an electronic pasture probe (Crosbie et al 1987) with calibration standards cut to the approximate grazing height of 2 em. Samples cut to the same height were taken from each plot for herbage dissection.…”

Section: Legumementioning

confidence: 99%

Comparison of Maku lotus (Lotus pedunculatus)-based and clover (Trifoliumspp.)-based swards with and without regular phosphorus fertiliser

Lowther¹

1991

New Zealand Journal of Agricultural Research

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Grazedclover(Trifolium spp.)-based and lotus (Lotus pedunculatus)-based pastures were compared over 6 years under differentmaintenance phosphorus (P) regimes. With biennial applications of P, herbage yields were higher from lotus-based than from clover-based swards irrespective of the rate of P applied (ID-40 kg P/ha). Herbage yields declined in the absence of maintenance fertiliser, with the declinebeinggreaterin clover-based than in lotus-based swards. Six years after maintenance P application ceased, clover and lotus sward yields were57 and 75% respectively of yieldsfrombiennial P applications. Declines were more rapid and differences more marked in the legume component of the swards with clover declining to 35% by the third year compared to 66% with lotus, with little further change. The results support the use of Maku lotus under low maintenanceP regimes.

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Section: Legumementioning

confidence: 99%

Comparison of Maku lotus (Lotus pedunculatus)-based and clover (Trifoliumspp.)-based swards with and without regular phosphorus fertiliser

Lowther¹

1991

New Zealand Journal of Agricultural Research

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“…The Pasture Probe® (Design Electronics, Palmerston North, NZ), has recently received interest since it is thought to measure sward surface area and to be less sensitive to herbage water content than earlier models (Vickery et al, 1980). The relationship between HM and CAP has been shown to be influenced by sampling technique and sward structure (Greathead et al, 1987), although studies to evaluate the relationship between CAP and HM have been conducted primarily with temperate grass-clover mixtures (Crosbie et al, 1987;George et al, 1987).…”

mentioning

confidence: 99%

Plant Height, Disk, and Capacitance Meters Used to Estimate Bermudagrass Herbage Mass

1990

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Rapid and reliable techniques for estimating herbage mass (HM) are essential for germplasm evaluation and proper grazing management. Since hand‐clipping small quadrats is time consuming, mathematical relationships between easy to use, nondestructive techniques and hand‐clipped estimates of HM (double sampling) have been utilized. This study was conducted to quantify relationships between HM and three commonly utilized nondestructive sward measurement techniques [plant height (HT), settled disk meter height (DISK), and capacitance (CAP)] in field plantings of ‘Brazos’ bermudagrass [Cynodon dactylon (L.) Pers.]. Estimates of HM, HT, DISK, and CAP were obtained from the same location in irrigated plots and nonirrigated, grazed pastures. Linear equations were observed to describe the relationship between HM and HT [ Y = 414 + 12.9X (r2 = 0.86), Y = 37 + 21.7X (r2 = 0.86)] and CAP [ Y = ‐1276 + 2.4X(r2 = 0.77), Y = 1289 + 2.8X (r2 = 0.89)] for plots and pastures, respectively. The relationship between HM and DISK was linear [ Y = 282 + 29.3X (r2 = 0.91)] and quadratic [ Y = 421 + 44.9X ‐ 0.7X2 (r2 = 0.80)] for the pasture and plot studies, respectively. For all HM relationships, the ability to predict HM was generally better in pastures than in small plots. Problems associated with lodged herbage in plots greatly influenced the HM predictive relationships of all techniques presumably by increasing the variability at high HM levels. Due to the large differences in the range of HM, in tiller height and tiller density, separate equations were required to predict HM in pastures and plots, regardless of the technique utilized. No single technique was observed to best predict HM. In the pastures, CAP and DISK were more efficient at estimating HM, while in the plots HT was the most efficient estimator of HM. This study suggests, while double‐sampling may allow for the estimation of HM in bermudagrass, factors such as tiller height and tiller density will influence the predictive relationships of all techniques requiring separate prediction equations to be developed where differences in sward composition are expected.

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“…In Experiment 3, herbage mass was estimated from relationships between capacitance probe and dry mass estimates. From the centre section three random corrected meter readings using a Design Electronics Pasture Meter (Crosbie et al, 1987) were taken. For all treatments within Experiment 3, herbage from the centre section was cut to 6 cm above ground level, the exception being treatment 3, which was cut to 2 cm.…”

Section: Sward Measurementsmentioning

confidence: 99%

The influence of sward canopy structure on foraging decisions by grazing cattle. I. Patch selection

Griffiths

Hodgson

Arnold

2003

Grass and Forage Science

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Patch selection by grazing dairy cows in response to simultaneous variation in combinations of sward structural characteristics was examined in three experiments in which four mature dairy cows were offered a choice of patches (typically 0.9 m × 0.9 m) of perennial ryegrass (Lolium perenne) presented in a linear arrangement. Treatments involved combinations of variations in sward height, stubble height and/or depth of regrowth, prepared by preliminary cutting treatments. They were arranged in balanced sets of four to nine treatments, which were arranged in linear sequences of eighteen to twenty‐seven patches. Within experiments, sequences were balanced across replicate sets of patches, which were grazed separately by individual cows. The number of bites removed and the residence time for each patch were highly correlated in all three experiments, and the results are reported using number of bites per patch as an estimator of foraging behaviour. In the first experiment, with vegetative swards, cows preferentially selected the tallest swards. When swards comprising reproductive stem were offered in Experiment 2, cows selectively grazed short‐stubble swards rather than tall‐stubble swards, although both offered a similar depth of regrowth. Cows did not exhibit preference for swards comprising the greatest quantity of leaf mass, indicating that the spatial distribution of plant components assumed greater importance. In the third experiment, the number of bites removed increased with increasing depth of regrowth, and was negatively correlated with sward height. The three patch‐appraisal cues investigated were broadly ranked in order of importance as (i) depth of regrowth, (ii) sward maturity and (iii) sward height. There was no evidence, at least at a short temporal scale, that patch behaviour was influenced by conditions in adjacent patches, suggesting that the cows assessed grazing opportunities on a patch‐by‐patch basis.

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Exploiting the pasture capacitance probe in agricultural research: a comparison with other methods of measuring herbage mass

Cited by 12 publications

References 6 publications

Comparison of Maku lotus (Lotus pedunculatus)-based and clover (Trifoliumspp.)-based swards with and without regular phosphorus fertiliser

Comparison of Maku lotus (Lotus pedunculatus)-based and clover (Trifoliumspp.)-based swards with and without regular phosphorus fertiliser

Plant Height, Disk, and Capacitance Meters Used to Estimate Bermudagrass Herbage Mass

The influence of sward canopy structure on foraging decisions by grazing cattle. I. Patch selection

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