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RESEARCH ARTICLE
Contents Vol 61(5)

Evaluating an active optical sensor for quantifying and mapping green herbage mass and growth in a perennial grass pasture

M. G. Trotter A B D , D. W. Lamb A B , G. E. Donald A C and D. A. Schneider A B
+ Author Affiliations
- Author Affiliations

A Cooperative Research Centre for Spatial Information, Carlton, Victoria 3053, Australia.

B Precision Agriculture Research Group, University of New England, Armidale, NSW 2351, Australia.

C CSIRO, Chiswick Research Station, Armidale, NSW 2350, Australia.

D Corresponding author. Email: mtrotter@une.edu.au

Crop and Pasture Science 61(5) 389-398 https://doi.org/10.1071/CP10019
Submitted: 20 January 2010  Accepted: 19 March 2010   Published: 12 May 2010

Abstract

Efficiently measuring and mapping green herbage mass using remote sensing devices offers substantial potential benefits for improved management of grazed pastures over space and time. Several techniques and instruments have been developed for estimating herbage mass, however, they face similar limitations in terms of their ability to distinguish green and senescent material and their use over large areas. In this study we explore the application of an active, near infrared and red reflectance sensor to quantify and map pasture herbage mass using a range of derived spectral indices. The Soil Adjusted Vegetation Index offered the best correlation with green dry matter (GDM), with a root mean square error of prediction of 288 kg/ha. The calibrated sensor was integrated with a Global Positioning System on a 4-wheel motor bike to map green herbage mass. An evaluation of representative, truncated transects indicated the potential to conduct rapid assessments of the GDM in a paddock, without the need for full paddock surveys.


Acknowledgments

This work was partially funded by the CRC for Spatial Information (CRCSI), established and supported under the Australian Government’s Cooperative Research Centres Programme. The authors wish to acknowledge the significant contribution of Matthew Monk of Sundown Pastoral Co. Pty Ltd.


References


Awty I (2009) Taking the guess work out of feeding cows. In ‘13th Annual Symposium on Precision Agriculture in Australasia’. Armidale, NSW. (Eds MG Trotter, EB Garraway, DW Lamb) p. 73. (Precision Agriculture Research Group, The University of New England: Armidale, NSW)

Baker B, Eynden T, Bogress N (1981) Hay yield determinations of mixed swards using a disk meter. Agronomy Journal 73, 67–69. open url image1

Bell AK, Allan CJ (2000) PROGRAZE – an extension package in grazing and pasture management. Australian Journal of Experimental Agriculture 40, 325–330.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Campbell NA, Arnold GW (1973) The visual assessment of pasture yield. Australian Journal of Experimental Agriculture and Animal Husbandry 13, 263–267.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Catchpole W, Wheeler C (1992) Estimating plant biomass: a review of techniques. Australian Journal of Ecology 17, 121–131.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Chen JM (1996) Evaluation of vegetation indices and a modified simple ratio for boreal applications. Canadian Journal of Remote Sensing 22, 229–242. open url image1

Devadas R, Lamb DW, Simpfendorfer S, Backhouse D (2009) Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves. Precision Agriculture 10, 459–470.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Earle DF, McGowan AA (1979) Evaluation and calibration of an automated rising plate meter for estimating dry matter yield of pasture. Australian Journal of Experimental Agriculture and Animal Husbandry 19, 337–343.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Edirisinghe A, Chapman GE, Louis JP (2001) A simplified method of retrieval of ground level reflectance of targets from airborne video imagery. International Journal of Remote Sensing 22, 1127–1141.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Ehlert D, Hammen V, Adamek R (2003) On-line sensor pendulum-meter for determination of plant mass. Precision Agriculture 4, 139–148.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Flowers M, Weisz R, Heiniger R (2001) Remote sensing of winter wheat tiller density for early nitrogen application decisions. Agronomy Journal 93, 783–789. open url image1

Flynn ES, Dougherty CT, Wendroth O (2008) Assessment of pasture biomass with normalised difference vegetation index from active ground-based sensors. Agronomy Journal 100, 114–121.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Fulkerson WJ, McKean K, Nandra KS, Barchia IM (2005) Benefits of accurately allocating feed on a daily basis to dairy cows grazing pasture. Australian Journal of Experimental Agriculture 45, 331–336.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Fulkerson WJ, Slack K (1993) Estimating mass of temperate and tropical pastures in the subtropics. Australian Journal of Experimental Agriculture 33, 865–869.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Ganguli AC, Vermeire LT, Mitchell RB, Wallace MC (2000) Comparison of four nondestructive techniques for estimating standing crop in shortgrass plains. Agronomy Journal 92, 1211–1215. open url image1

Gates DM, Keegan HJ, Schleter JC, Weidner VR (1965) Spectral properties of plants. Applied Optics 4, 11–20.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Gitelson AA, Kaufmann YJ, Stark R, Rundquist D (2002) Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment 80, 76–87.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Goel NS, Qi W (1994) Influences of canopy architecture on relationships between various vegetation indices. Remote Sensing Reviews 10, 309–347. open url image1

Gong P, Ruiliang P, Biging GS, Larrieu MR (2003) Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing 41, 1355–1362.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Gourley CJP, McGowen AA (1991) Assessing differences in pasture mass with an automated rising plate meter and a direct harvesting technique. Australian Journal of Experimental Agriculture 31, 337–339.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Haboudane D, Miller JR, Pattey E, Zarco-Telada PJ, Strachan IB (2004) Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sensing of Environment 90, 337–352.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Hanna MM, Steyn-Ross DA, Steyn-Ross M (1999) Estimating biomass for New Zealand pasture using optical remote sensing techniques. Geocarto International 14, 89–94.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Harmoney KR, Moore KJ, George JR, Brummer EC, Russell JR (1997) Determination of pasture mass using four indirect methods. Agronomy Journal 89, 665–672. open url image1

Haydock KP, Shaw NH (1973) The comparative yield method for estimating dry matter yield of pasture. Australian Journal of Experimental Agriculture and Animal Husbandry 15, 663–670. open url image1

Hill J, Sturm B (1991) Radiometric correction of multitemporal Thematic Mapper data for use in agricultural and land-cover classification and vegetation monitoring. International Journal of Remote Sensing 12, 1471–1491.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Hill NS, Stuedemann JA, Ware GO, Petersen JC (1989) Pasture sampling requirement for near infrared reflectance spectroscopy estimates of botanical composition. Crop Science 29, 774–777. open url image1

Holland KH , Schepers JS , Shanahan JF , Horst GL (2004) Plant canopy sensor with modulated polychromatic light source. In ‘7th International Conference on Precision Agriculture and Other Precision Resources Management’. Minneapolis, MN, USA. (Ed. DJ Mulla) (University of Minnesota, Department of Soil, Water and Climate: St Paul, MN)

Huete AR (1988) A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 25, 295–309.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Hutchings NJ (1991) Spatial heterogeneity and other sources of variance in sward height as measured by the sonic and HFRO sward sticks. Grass and Forage Science 46, 277–282.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Hutchinson KJ, McLean RW, Hamilton BA (1972) The visual estimation of pasture availability using standard pasture cores. Journal of the British Grassland Society 27, 29–34.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Inman D, Khosla R, Mayfield T (2005) On-the-go active remote sensing for efficient crop nitrogen management. Sensor Review 25, 209–214.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Jackson RD, Ezra CE (1985) Spectral response of cotton to suddenly induced water stress. International Journal of Remote Sensing 6, 177–185.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Jordon CF (1969) Derivation of leaf-area index from the quality of light on the forest floor. Ecology 50, 633–666. open url image1

Kaufman Y (1989) The atmospheric effect on remote sensing and its correction. In ‘Theory and applications of optical remote sensing’. (Ed. G Asrar) pp. 336–428. (John Wiley & Sons: USA)

Künnemeyer R, Schaare PN, Hanna MM (2001) A simple reflectometer for on-farm pasture assessment. Computers and Electronics in Agriculture 31, 125–136.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Laca E (2009) New approaches and tools for grazing management. Rangeland Ecology and Management 62, 407–417.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Laca EA, Demment MW, Winckel J, Kie JG (1989) Comparison of weight estimate and rising plate meter methods to measure herbage mass of a mountain meadow. Journal of Range Management 42, 71–75.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lamb DW (2000) The use of qualitative airborne multispectral imaging for managing agricultural crops – a case study in south-eastern Australia. Australian Journal of Experimental Agriculture 40, 725–738.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lamb DW, Steyn-Ross M, Schaare P, Hanna M, Silvester W, Steyn-Ross A (2002) Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modelling and experimental observations. International Journal of Remote Sensing 23, 3619–3648.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lamb DW, Trotter MG, Schneider DA (2009) Ultra low-level airborne (ULLA) sensing of crop canopy reflectance: A case study using a CropCircle™ sensor. Computers and Electronics in Agriculture 69, 86–91.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Lamb DW, Weedon MM, Rew LJ (1999) Evaluating the accuracy of mapping weeds in seedling crops using airborne digital imaging: Avena spp. in seedling triticale. Weed Research 39, 481–492.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Liang S (2003) ‘Quantitative remote sensing of land surfaces.’ (John Wiley and Sons: Hoboken, NJ)

Martin RC, Astatke T, Cooper JM, Fredeen AH (2005) A comparison of methods used to determine biomass on naturalized swards. Journal of Agronomy & Crop Science 191, 152–160.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Moges SM, Raun WR, Mullen RW, Freeman KW, Kohnson GV, Solie JB (2004) Evaluation of green, red and near infrared bands for predicting winter wheat biomass, nitrogen uptake, and final grain yield. Journal of Plant Nutrition 27, 1431–1441.
| Crossref | GoogleScholarGoogle Scholar | CAS | open url image1

Neal D, Currie P, Morris M (1976) Sampling herbaceous native vegetation with an electronic capacitance instrument. Journal of Range Management 29, 74–77.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Omer RM, Hester AJ, Gordon IJ, Swaine MD, Raffique SM (2006) Seasonal changes in pasture biomass, production and offtake under the transhumance system in northern Pakistan. Journal of Arid Environments 67, 641–660.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Paap A , Askraba S , Alameh K , Rowe J (2008) Photonic-based spectral reflectance sensor for ground-based plant detection and weed discrimination. In ‘Proceedings of SPIE, the International Society for Optical Engineering. 19th International Conference on Optical Fibre Sensors’. Perth, W. Aust. Vol. 7004. (Eds D Sampson, S Collins, K Oh, R Yamauchi) pp. 5K.1–5K.4. (SPIE: Bellingham, Washington, DC)

Robinson G, Whalley R, Taylor J (1983) The effect of prior history of superphosphate application and stocking rate on faecal and nutrient distribution on grazed natural pastures. Australian Rangeland Journal 5, 79–82.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Rouse JW , Haas JR , Schell JA , Deering DW (1974) Monitoring vegetation systems in the great plains with ERTS. In ‘Third Earth Resources Technology Satellite-1 Symposium’. (Eds S Freden, E Mercanti, M Becker) pp. 309–317. (NASA US Government Printing Office: Washington, DC)

Sanderson MA, Rotz CA, Fultz SW, Rayburn EB (2001) Estimating forage mass with a commercial capacitance meter, rising plate meter and pasture ruler. Agronomy Journal 93, 1281–1286. open url image1

Schepers JS , Shanahan JF (2009) Managing nitrogen with active sensors. In ‘13th Annual Symposium on Precision Agriculture in Australasia’. Armidale, NSW. (Eds MG Trotter, EB Garraway, DW Lamb) pp. 2–10. (Precision Agriculture Research Group, University of New England: Armidale, NSW)

Schut AGT, Lokhorst C, Hendriks MMWB, Kornet JG, Kasper G (2005) Potential of imaging spectroscopy as tool for pasture management. Grass and Forage Science 60, 34–45.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Schut AGT, van der Heijden GWAM, Hoving I, Stienezen MWJ, van Evert FK, Meuleman J (2006) Imaging spectroscopy for on-farm measurement of grassland yield and quality. Agronomy Journal 98, 1318–1325.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Scrivner JH, Center DM, Jones MB (1986) A rising plate meter for estimating production and utilization. Journal of Range Management 39, 475–477.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Sharrow SH (1984) A simple disc meter for measurement of pasture height and forage bulk. Journal of Range Management 37, 94–95.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Sheehy JE (1975) Some optical properties of leaves of eight temperate forage grasses. Annals of Botany 39, 377–386. open url image1

Shiyomi M, Akiyama T, Takahashi S (1983) A spatial pattern model of plant biomass in grazing pasture I. Journal of Japanese Grassland Science 28, 373–382. open url image1

Shiyomi M, Akiyama T, Takahashi S (1984) A spatial pattern model of plant biomass in grazing pasture II. Journal of Japanese Grassland Science 30, 40–48. open url image1

Spackman SL (2005) Using airborne multispectral imaging to forecast yield in rice crops. PhD Thesis, Charles Sturt University, NSW, Australia.

Spackman SL, Lamb DW, Louis J (2000) Using airborne multispectral imagery to manage within-field variability in rice production. Aspects of Applied Biology 60, 99–106. open url image1

Stowell L (2008) Evaluation of Geonics EM38 and NTech Greenseeker sensor array for use in precision turfgrass management. In ‘Joint Annual Meeting: The Geological Society of America; Soil Science Society of America; American Society of Agronomy; Crop Science Society of America; Gulf Coast Association of Geological Societies’. Houston, Texas. Poster 417.

Sui R, Thomasson JA, Hanks J, Wooten J (2008) Ground-based sensing system for weed mapping in cotton. Computers and Electronics in Agriculture 60, 31–38.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Tremblay N, Wang Z, Ma B-L, Belec C, Vigneault P (2009) A comparison of crop data measured by two commercial sensors for variable-rate nitrogen application. Precision Agriculture 10, 145–161.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Trotter TF , Frazier PF , Trotter MT , Lamb DL (2008) Objective biomass assessment using an active plant sensor (Crop Circle), preliminary experiences on a variety of agricultural landscapes. In ‘9th International Conference on Precision Agriculture’. Denver, Colorado. (Ed. R Khosla) (Colorado State University: Fort Collins, CO)

Tsutsumi M, Itano S (2005) Variant of estimation method of above-ground plant biomass in grassland with gamma model 1. Use of an electronic capacitance probe. Grassland Science 51, 275–279.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Vickery PJ, Bennet IL, Nicol GR (1980) An improved electronic capacitance meter for estimating herbage mass. Grass and Forage Science 35, 247–252.
| Crossref | GoogleScholarGoogle Scholar | open url image1

Virgona JM , Hackney B (2008) Within-paddock variation in pasture growth: landscape and soil factors. In ‘14th Australian Agronomy Conference’. Adelaide, South Australia. (Ed. M Unkovich) (Australian Society of Agronomy)

Whelan BM , McBratney AB , Minasny B (2001) Vesper-spatial prediction software for precision agriculture. In ‘3rd European Conference on Precision Agriculture’. Montpellier, France. (Eds G Grenier, S Blackmore) pp. 139–144. (Agro-Montpellier: France)

Yule IJ , Fulkerson WJ , Lawrence HG , Murray R (2006) Pasture measurement: the first step towards precision dairying. In ‘10th Annual Symposium on Precision Agriculture Research and Application in Australasia’. The Australian Technology Park, Eveleigh, Sydney. p. 6. (Australian Centre for Precision Agriculture, University of Sydney: Sydney)

Yule IJ , Lawrence HG , Murray RI (2005) Yield mapping to improve dairy farm production. In ‘2005 American Society of Agricultural Engineers Annual International Meeting’. Tampa, Florida. ASAE Paper No. 051074. (ASAE: St Joseph, MI)

Zwiggelaar R (1998) A review of spectral properties of plants and their potential use for crop/weed discrimination in row crops. Crop Protection 17, 189–206.
| Crossref | GoogleScholarGoogle Scholar | open url image1