Rayburn, Edward Barrow

Rayburn, Susan Brand

English

The Research Repository @ WVU (West Virginia University)

Faculty & Staff Scholarship 3-1-1998 A Standardized Plate Meter for Estimating Pasture Mass in On-farm Research Trials Edward Barrow Rayburn West Virginia University, ed.rayburn@mail.wvu.edu Susan Brand Rayburn Cornell Coopertive Extension Follow this and additional works at: https://researchrepository.wvu.edu/faculty_publications Digital Commons Citation Rayburn, Edward Barrow and Rayburn, Susan Brand, "A Standardized Plate Meter for Estimating Pasture Mass in On-farm Research Trials" (1998). Faculty & Staff Scholarship. 3190. https://researchrepository.wvu.edu/faculty_publications/3190 This Article is brought to you for free and open access by The Research Repository @ WVU. It has been accepted for inclusion in Faculty & Staff Scholarship by an authorized administrator of The Research Repository @ WVU. For more information, please contact beau.smith@mail.wvu.edu. 238 AGRONOMY JOURNAL, VOL. 90, MARCH–APRIL 1998scale descriptions. This is apparent in the percentages A STANDARDIZED PLATE METER FORof dry matter in the grain presented in the correlationESTIMATING PASTURE MASS INof the BBCH and Hanway scales in the grain ripeningphase (Table 1). ON-FARM RESEARCH TRIALSThe scientific goal of developing universally applica-Edward B. Rayburn* and Susan B. Rayburnble crop scales conflicts with the programming goal ofproviding maximal error checking. We chose to make Abstractthe SCALES 2 programs applicable over a wide varietyA plate meter for estimating pasture mass (PM) was constructed ofof conditions, thus relying on the user to supply accurate5.6-mm-thick acrylic plastic cut into a 46-cm square and fitted withinputs. As standardization of crop development scalesa 3.8-cm center hole. (The acrylic is stable under varying humidity,progresses, and more crops and staging systems arereadily available, inexpensive, and easy to work.) A meter stickadded to computerized staging systems, error checking through the center hole measures the plate height (PH) resting onmay become even more difficult to accomplish without the pasture canopy. The meter was tested on six rotationally grazedrestricting the user to common conditions. pastures (0.2–2.4 ha), measured before eight grazing events. EachAs more crops and staging scales are included in scale pasture was double-sampled for PH and clipped PM at 10 to 30locations. The calibration regression slope was 452 kg (ha cm)21, withconversion programs, it may be desirable to combinea residual standard deviation (RSD) of 753 kg ha21 and an r 2 of 0.52.them into a single computer program. We chose not toThe high RSD is typical of forage stands, which vary widely in foragedo so, because the existing scales for corn and smallbulk density. The relatively low r 2 was probably due to the uniformgrains are so different that the code diverged immedi-height of these rotationally grazed (as opposed to continuously grazed)ately after the user indicated the crop. Retaining bothpastures resulting in a small range in PH. The validation regressiontypes of crops in a single computer program would result had a slope of 0.72 and a RSD of 808 for individual samples and ain more lengthy and confusing code with no gain in effi- slope of 1.11 and RSD of 155 for means of 20 samples. The reductionciency. in RSD with increasing sample size points to the need to take 15to 30 measurements when calibrating the plate meter or samplingrotationally grazed pastures, to have an estimate within 10% of theSpecifications, Documentation, and Availabilitymean PM. This simple plate meter provides as accurate a measureof PH and PM as the more sophisticated metal plate meters, is practicalSCALES 2 is written in ANSI standard Fortran 77.for carrying in the field, and in 1996 cost $12.The program is designed for IBM-compatible micro-computers running DOS version 3.3 or greater.2 A harddisk and math coprocessor are not required.Reliable and inexpensive estimates of pasture massSCALES 2 is available from the Soil and Water Con- are necessary when studying the effects of grazingservation Research Unit, 119 Keim Hall, University ofmanagement or planning and implementing grazing sys-Nebraska, Lincoln, NE, 68583-0934. The source code,tems. When applying pasture management research onexecutable program, and documentation are distributedfarms a practical, low-cost, readily available tool ison 3.5-inch diskettes.needed for measuring pasture mass.Several methods are available for estimating pastureReferencesmass. These include ground cover (2,3,5,7), canopyAfuakwa, J.J., and R.K. Crookston. 1984. Using the kernel milk line height (3,5,7,8), the product of ground cover and canopyto visually monitor grain maturity in maize. Crop Sci. 24:687–691.height (2,3,5), the bulk height of the forage canopy com-Bauer, A., D. Smika, and A. Black. 1983. Correlation of five wheatpressed by a weighted disk or board (1,3,5,8,9), andgrowth stage scales used in the Great Plains. Publ. AAT-NC-7.USDA-ARS, Peoria, IL. an electronic capacitance meter (6). The ground coverCrookston, R.K., and J.E. Kurle. 1987. Corn kernel milk line: Use it method predicted pasture mass of low-yielding blue-as a key for harvesting silage. Crops Soils 39:14–15. grass (Poa pratensis L.) pastures, but it was less accurateHarrell, D.M., W.W. Wilhelm, and G.S. McMaster. 1993. SCALES:in more productive mixed orchardgrass (Dactylis glo-A computer program to convert among three developmental stagemerata L.) and clover (Trifolium sp.) pastures (7). Inscales for wheat. Agron. J. 85:758–763.Haun, J.R. 1973. Visual quantification of wheat development. Agron. alfalfa (Medicago sativa L.), there was a high correlationJ. 65:116–119. between forage height and dry matter yield, and theLancashire, P.D., H. Bleiholder, T. van den Boom, P. Langeluddeke, correlation was improved by using forage height com-R. Stauss, E. Weber, and A. Witzenberger. 1991. A uniform decimalpressed by a weighted disk (3). The weighted plate orcode for growth stages of crops and weeds. Ann. Appl. Biol.119:561–601. weighted disk meter appears to account for differencesLarge, E.C. 1954. Growth stages in cereals. Plant Pathol. 3:128–129. in sward density between sites.Ritchie, S.W., J.J. Hanway, and G.O. Benson. 1986. How a corn plantdevelops. Rev. ed. Iowa State Univ. Coop. Ext. Serv. Spec. Rep. 48.Abbreviations: PH, plate height; PM, pasture mass; RSD, residualZadoks, J.C., T.T. Chang, and C.F. Konzak. 1974. A decimal codestandard deviation.for the growth stages of cereals. Weed Res. 14:415–421.E.B. Rayburn, West Virginia Univ., 1078 Agricultural Science Bldg.,P.O. Box 6108, Morgantown, WV 26506-6108, and S.B. Rayburn,Cornell Coop. Ext.–Cattaraugus County, Ellicottville, NY 14731-9701.This information is published with the approval of the Director ofthe West Virginia Agric. & Forestry Exp. Stn. as Scientific Articleno. 2550. Received 22 Apr. 1996. *Corresponding author (erayburn@2 Mention of a trademark or proprietary product does not constitute wvu.edu).an endorsement by the authors, the University of Nebraska, or theUSDA. Published in Agron. J. 90:238–241 (1998).NOTES AND UNIQUE PHENOMENA 239Fig. 1. Schematic diagram of the plate meter made from acrylic plastic, used to measure the bulk height of pasture canopies.carried and lowered to the pasture surface using a piece ofWeighted disk meters are made from disks of sheetstring tied through four of the 3.2-mm holes, with the stringmetal, with etched metal measuring rods (1,3,9). Ply-held by a finger of the hand holding the measuring stickwood and acrylic plastic have also been used (5,8). The(Fig. 1).effects of different disk sizes and disk weights (1,3) andThe plate meter was tested on six cool-season, grass–legumeof season and harvest (1,3,9) on the performance ofpastures before eight rotational grazing events. Four of thesethese meters have been reported. Bransby et al. (1) grazing events were used for calibration and four were usedfound that a 0.20-m2 disk, with a weight from 5 to 15 for validation of the calibration. Pastures ranged from 0.2 tokg m22, provided regression slope standard errors equal 2.4 ha in size and were grazed for 0.5 to 6 d. These pasturesto 5 to 12% of the slope for summer and fall pasture consisted of orchardgrass, timothy (Phleum pratense L.), red-with residual standard deviations ranging form 406 to top (Agrostis gigantea Roth; syn. Agrostis alba L.) and other1012 kg ha21. Agrostis spp., sweet vernal grass (Anthoxanthum odoratumL.), and white clover (T. repens L.). The pastures were locatedTo determine pasture mass in a cooperative regional,on three farms in western New York and all data were col-multifarm pasture project in the U.S. Northeast, thelected by one person.weighted disk meter was chosen as a research-provenThe plate meter was calibrated using paired samples fromtool. The commercial forms of metal disk meters de-10 to 30 locations per pasture, depending on pasture sizescribed in the literature were too expensive to purchase(Table 1). Ten sample points were taken at 3-m intervals alongin large numbers, so there was a need for an alternative a randomly located 30-m transects. Transects were used dueconstruction that would accomplish the same results. to the needs of a concurrent selective grazing study beingThe purposes of this study were to design an inexpen- conducted. Calibration samples are normally taken by select-sive, weight-stable plate meter, one easy to construct ing a range of plate heights, to improve the calibration r 2from materials readily available across the region, andto calibrate the plate meter for use under rotationalgrazing. Acrylic plastic sheeting was chosen, since itis inexpensive, does not absorb water, and is readilyavailable from local glass distributors.Materials and MethodsA 46-cm square (0.21 m2) was cut from 5.6-mm-thick acrylicplastic sheeting (Fig. 1). A 3.8-cm-diameter hole was cut inthe center of this plate to allow the insertion of a meter stickfor measuring the plate height above the ground when theplate is set on the sward (Fig. 2). The edges of the center holewere smoothed with a wood rasp to prevent rough edges fromcatching on the meter stick. An additional 24 holes, 3.2-mmin diameter, were drilled along five lines set at 7.6-cm intervalsstarting 7.6 cm from the plate’s edge. These holes allow theuse of the plate as a point quadrat for estimating groundcover in thin stands or stubble aftermath or for measuring the Fig. 2. The acrylic plastic plate meter being used to measure the bulkheight of a grass–clover pasture.occurrence of forage species under the plate. The plate was240 AGRONOMY JOURNAL, VOL. 90, MARCH–APRIL 1998value, as recommended by Bransby et al. (1). The plate meterwas placed gently on the forage until the canopy supportedthe plate. The plate height of the pasture canopy was measuredfrom the ground to the top of the plate, using a meter stickthrough the plate’s center hole. A quadrat (46-cm square) wasused for the calibration clipping. The quadrat was placed overthe sample site after the plate height was measured and theplate meter removed. The forage was separated along theedges of the quadrat, allowing the quadrat to lie on the ground.The forage was cut as close to ground level as possible, using10.2-cm-wide battery-powered lawn edgers. An alternativemethod used was to clip two strips, 46 cm long, within thearea measured with the plate meter. The harvested area wasthe total length of cut times the clipper width. The forage wasweighed wet in the field using 500-g capacity spring scales.The 10 samples from each transect were composited for drymatter determination. The samples were frozen, then driedin screen-bottom trays with ambient air and later oven-driedby the Northeast Dairy Herd Improvement Forage TestingLaboratory in Ithaca, NY. Dry matter yield per hectare wascalculated based on the forage dry matter harvested in theclipped sample, using ambient and oven-drying moisturelosses, and the clipped area.The plate meter was calibrated using linear regression ofthe paired plate height and pasture mass values from thecalibration data set (4). The calibration was validated using Fig. 3. Calibration data set regression and individual data points.the paired samples from the validation data set. For eachwhile Griggs and Stringer (3) reported r 2 values as highdata point, the pasture mass (PM) was predicted using thecalibration equation and sampled plate height (PH). The pre- as 0.94 for alfalfa stands sampled over the entiredicted PM was compared with the measured PM using linear growth period.regression to estimate the error of prediction of individual The calibration RSD is comparable to that found bysamples. The calibration was also validated for sample means, Bransby et al. (1) and Vartha and Matches (9). Theseusing 61 sample means obtained by randomly sampling the high RSD values are due to the large variability in foragevalidation data set for 20 data points per mean. The mean density (PM per unit PH) at the one-quarter squarepredicted PM was compared with the mean measured PM meter scale and show the need to take a large numberusing linear regression.of samples during calibration.For these pastures, which were rotationally grazed toResults and Discussion a short residual height, the intercept was not signifi-The calibration equation for the plate meter was cantly different from zero. This is likely due to littlePM 5 452 PH 1 3, with an r 2 of 0.52 and a residual thatch buildup in the paddocks which if present wouldstandard deviation (RSD) of 753 (Fig. 3). The standard add to a regression intercept.error was 49 for the slope and 246 for the intercept.This relatively low r 2 value is due in part to the uni-form height of the pastures used. Bransby et al. (1)reported r-values between 0.79 and 0.94 (0.62–0.88 r 2)and showed that the r-value obtained in calibrating aplate meter increases as the range in plate heights usedin the calibration increases. Vartha and Matches (9)reported r 2 values ranging from 0.09 to 0.84 for pasturesTable 1. Description of the six rotationally grazed pastures sam-pled over eight grazing events used to calibrate and validatethe calibration of the plate meter.ClippedPasture Plate height pasture massID Date Size N Mean SD Mean SDha no. cm kg ha21Calibration data setR2 10 July 2.4 30 14.0 2.8 2331 954R2 30 Aug. 2.4 30 7.9 1.8 1621 589B1 2 Oct. 0.2 10 13.2 3.6 2904 780F4 5 Oct. 0.2 10 11.7 2.0 2895 571Validation data setR3 17 July 2.4 30 17.8 4.1 3096 1276R3 2 Sept. 2.4 30 8.6 1.8 1903 684B3 4 Oct. 0.2 10 14.5 3.6 3018 1327F1 2 Oct. 0.2 10 15.5 4.6 4517 1112 Fig. 4. Validation regression using individual data points.NOTES AND UNIQUE PHENOMENA 241mean on the RSD of the predicted PM, the RSD de-creased from 400 to 100 as the number of observationsincreased from 5 to 30 (Fig. 6). When using 30 observa-tions in a mean, this validation set produced a lowerRSD than that reported by Bransby et al. (1), which isprobably due to the more uniform sward found in theserotationally grazed pastures compared with the setstocked pastures worked with in their study.For practical on-farm use of the plate meter, addi-tional calibrations are needed over pastures differing inspecies composition, season of the year, and regrowthage. These calibrations could be used to determine dif-ferent calibration domains and to see if pastures can beeasily described for placement in an appropriate calibra-tion domain, so that calibration clippings would not haveto be made for each pasture.This simple plate meter provides as accurate a mea-sure of plate height and pasture mass as the more sophis-ticated metal plate meters. The r 2 values and RSD ofindividual samples in this study were similar to thosefound in previous research. The magnitude of the RSDemphasizes the need to take 20 to 30 paired samples percalibration and 30 or more observations when predictingpasture mass, in order to obtain an estimate within 10%Fig. 5. Validation regression using means composed of 20 subsamplesfrom the validation data set per data point. of the mean. This plate meter, which is easily carriedin the field, is proving to be a practical, low-cost ($12,When the calibration was validated using individual in 1996) alternative to metal disk meters for use indata points the regression was PMmeasured 5 0.72 quantitative pasture assessment and management andPMpredicted 1 645 with an r 2 of 0.38 and a RSD of 808 is being used by farmers, extension agents, and research-(Fig. 4). This shows that there was some bias in the ers in the U.S. Northeast to measure pasture mass.calibration model when applied to the validation dataAcknowledgmentsset. When the calibration was validated using 61 meansof 20 data points each, the validation regression was This study was sponsored by Seneca Trail Resource Conser-PMmeasured 5 1.11 PMpredicted 2 250, with an r 2 of 0.32 and vation and Development Area, Franklinville, NY, and Cornella RSD of 155 (Fig. 5). This magnitude of the RSD of Cooperative Extension–Cattaraugus County, Ellicottville,predicted means is very satisfactory for research and NY, and was supported in part by funds of USDA CooperativeAgreement 88 COOP-1-3524, USDA National Research andon-farm management purposes. As the number of sam-Extension Program on Low Input Agriculture–Northeastples in a PM mean increases, the RSD of the predictedRegion.mean decreases (1). When using the validation data setto compare the effects of number of observations in aReferences1. Bransby, D.I., A.G. Matches, and G.F. Krause. 1977. Disk meterfor rapid estimation of herbage yield in grazing trials. Agron. J.69:393–396.2. Evans, R.A., and M.D. Jones. 1958. Plant height times groundcover versus clipped samples in estimating forage production.Agron. J. 50:504–506.3. Griggs, T.C., and W.C. Stringer. 1988. Prediction of alfalfa herb-age mass using sward height, ground cover, and disk technique.Agron. J. 80:204–208.4. Hintze, J.L. 1991. Solo statistical system. BMDP Statistical Soft-ware, Los Angeles.5. Michalk, D.L., and P.K. Herbert. 1977. Assessment of four tech-niques for estimating yield on dryland pastures. Agron. J. 69:864–868.6. Neal, D.L., and J.L. Neal. 1973. Uses and capabilities of electroniccapacitance instruments for estimating standing herbage: I. His-tory and development. J. Br. Grassl. Soc. 28:81–89.7. Pasto, J.K., J.R. Allison, and J.B. Washko. 1957. Ground coverand height of sward as a means of estimating pasture production.Agron. J. 49:407–409.8. Sharrow, S.H. 1984. A simple disc meter for measurement ofpasture height and forage bulk. J. Range Manage. 37:94–95.Fig. 6. The effect of increasing the number of observations per mean9. Vartha, E.W., and A.G. Matches. 1977. Use of a weighted-diskon the residual standard deviation of the estimated mean usingmeasure as an aid in sampling the herbage yield on tall fescuethe validation data set.pastures grazed by cattle. Agron. J. 69:888–890.

A Standardized Plate Meter for Estimating Pasture Mass in On-farm Research Trials

https://researchrepository.wvu.edu/cgi/viewcontent.cgi?article=4131&context=faculty_publications

A Standardized Plate Meter for Estimating Pasture Mass in On-farm Research Trials

Abstract

Similar works

Full text

Available Versions

The Research Repository @ WVU (West Virginia University)