Use of proximal sensors to evaluate at the sub-paddock scale a pasture growth-rate model based on light-use efficiency

Crop and Pasture Science

Volumn 65, Issue 4, 2014, Pages 400-409

  Rahman, M M ^a   Lamb, D W ^a   Stanley, J N ^a   Trotter, M G ^a  

^a UNIVERSITY OF NEW ENGLAND   (Australia)

Author keywords

active optical sensor (AOS); LUE; PGR.; tall fescue

Indexed keywords

AVHRR; GRAZING; GROWTH RATE; LIGHT USE EFFICIENCY; LIVESTOCK FARMING; PASTURE; PHOTOSYNTHETICALLY ACTIVE RADIATION; SOIL MOISTURE; SPATIAL RESOLUTION; VEGETATION INDEX;

EID: 84900400788     PISSN: 18360947     EISSN: 18365795     Source Type: Journal    
DOI: 10.1071/CP14071     Document Type: Article

References (71)

1. Baret F, Guyot G (1991) Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment 35, 161-173. doi:10.1016/0034-4257(91)90009-U
2. Barrett PD, Laidlaw AS, Mayne CS (2005) GrazeGro: A European herbage growth model to predict pasture production in perennial ryegrass swards for decision support. European Journal of Agronomy 23, 37-56. doi:10.1016/j.eja. 2004.09.006
3. Bell AK, Allan CJ (2000) PROGRAZE-an extension package in grazing and pasture management. Australian Journal of Experimental Agriculture 40, 325-330. doi:10.1071/EA98017
4. BoM (2013) Climate statistics for Armidale. Available at: www.bom.gov.au/climate/averages/tables/cw-056037-All.shtml (accessed 2 May 2013)
5. Brisco B, Pultz TJ, Brown RJ, Topp GC, Hares MA, Zebchuk WD (1992) Soil moisture measurement using portable dielectric probes and time domain reflectometry. Water Resources Research 28, 1339-1346. doi:10.1029/92WR00057
6. Burke JJ, Mahan JR, Hatfield JL (1988) Crop-specific thermal kinetic windows in relation to wheat and cotton biomass production. Agronomy Journal 80, 553-556. doi:10.2134/agronj1988.0002196200 8000040001x
7. Cook SE, Bramley RGV (2001) Is agronomy being left behind by precision agriculture? In 'Proceedings of the 10th Australian Agronomy Conference'. Hobart, Tas. (Australian Society of Agronomy/The Regional Institute: Gosford, NSW) Available at: www.regional.org.au/au/asa/2001/plenary/2/cook.htm
8. Coops N (1999) Improvement in predicting stand growth of Pinus radiata (D. Don) across landscapes using NOAA AVHRR and Landsat MSS imagery combined with a forest growth process model (3-PGS). Photogrammetric Engineering and Remote Sensing 65, 1149-1156.
9. Di Bella C, Faivre R, Ruget F, Seguin B (2005) Using VEGETATION satellite data and the crop model STICS-Prairie to estimate pasture production at the national level in France. Physics and Chemistry of the Earth Parts A/B/C 30, 3-9. doi:10.1016/j.pce.2004.08.018
10. Dickinson RE (1983) Land surface processes and climate-surface albedos and energy balance. Advances in Geophysics 25, 305-353. doi:10.1016/S0065- 2687(08)60176-4
11. Donald GE, Edirisinghe A, Henry DA, Mata G, Gherardi SG, Oldham CM, Gittins SP, Smith RCG (2004) Pastures from Space-Validation of predictions of pasture growth rates. Proceedings Australian Society for Animal Production 25, 232.
12. Donnelly JR, Freer M, Salmon L, Moore AD, Simpson RJ, Dove H, BolgerTP (2002) Evolution of the GRAZPLAN decision support tools and adoption by the grazing industry in temperate Australia. Agricultural Systems 74, 115-139. doi:10.1016/S0308-521X(02)00024-0
13. Ellis RH, Summerfield RJ, Edmeades GO, Roberts EH (1992) Photoperiod, temperature, and the interval from sowing to tassel initiation in diverse cultivars of maize. Crop Science 32, 1225-1232. doi:10.2135/cropsci1992. 0011183X003200050033x
14. Field C, Randerson J, Malmström C (1995) Global net primary production: Combining ecology and remote sensing. Remote Sensing of Environment 51, 74-88. doi:10.1016/0034-4257(94)00066-V
15. Fisher PD, Abuzar M, Rab MA, Best F, Chandra S (2009) Advances in precision agriculture in south-eastern Australia. I. A regression methodology to simulate spatial variation in cereal yields using farmers' historical paddock yields and normalised difference vegetation index. Crop & Pasture Science 60, 844-858. doi:10.1071/CP08347
16. Fitzpatrick EA, Nix HA (1970) The climatic factor in Australian grassland ecology. In 'Australian grasslands'. (Ed. RM Moore) pp. 3-26. (Australian National University Press: Canberra, ACT)
17. Fulkerson W, Slack K (1993) Estimating mass of temperate and tropical pastures in the subtropics. Australian Journal of Experimental Agriculture 33, 865-869. doi:10.1071/EA9930865
18. Gallagher JN, Biscoe PV (1978) Radiation absorption, growth and yield of cereals. The Journal of Agricultural Science 91, 47-60. doi:10.1017/ S0021859600056616
19. Gallo KP, Daughtry CST, Bauer ME (1985) Spectral estimation of absorbed photosynthetically active radiation in corn canopies. Remote Sensing of Environment 17, 221-232. doi:10.1016/0034-4257 (85)90096-3
20. Gamon JA, Field CB, Goulden ML, Griffin KL, Hartley AE, Joel G, Peñuelas J, Valentini R (1995) Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types. Ecological Applications 5, 28-41. doi:10.2307/1942049
21. Gherardi SG, Anderton L, Sneddon J, Oldham C, Mata G (2005) Pastures from Space-Application of satellite-derived pasture predictions improve the profitability of Australian sheep producers. In 'Proceedings of the 20th International Grasslands Congress'. (Eds FP O'Mara et al.) pp. 859-860. (Wageningen Academic Publishers: The Netherlands)
22. Goward S, Dye D (1997) Global biospheric monitoring with remote sensing. In 'The use of remote sensing in the modeling of forest productivity'. Vol. 50. (Eds H Shimoda, H Gholz, K Nakane) pp. 241-272. (Springer: Dordrecht, the Netherlands)
23. Goward SN, Waring RH, Dye DG, Yang J (1994) Ecological remote sensing at OTTER: Satellite macroscale observations. Ecological Applications 4, 322-343. doi:10.2307/1941937
24. Gower ST, Kucharik CJ, Norman JM (1999) Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems. Remote Sensing of Environment 70, 29-51. doi:10.1016/
25. S0034-4257(99)00056-5, Green CF (1987) Nitrogen nutrition and wheat growth in relation to absorbed solar radiation. Agricultural and Forest Meteorology 41, 207-248. doi:10.1016/0168-1923(87)90080-3
26. Hanan NP, Prince SD, Bégué A (1995) Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data. Agricultural and Forest Meteorology 76, 259-276. doi:10.1016/0168-1923(95)02229-Q
27. Haxeltine A, Prentice IC (1996) A general model for the light-use efficiency of primary production. Functional Ecology 10, 551-561. doi:10.2307/2390165
28. 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.
29. Hedley P, Kolver E, Glassey C, Thorrold T, Van Bysterveldt A, Roche JR, Macdonald K (2006) Achieving high performance from a range of farm systems. In 'Proceedings of Dairy3 Farmers Conference'. Hamilton, New Zealand. Vol. 4. (Ed. IM Brookes) pp. 147-167. (Dairy NZ: Hamilton, New Zealand) Available at: www.dairynz.co.nz/page/pageid/2145856682/2006-Volume-4-Proceedings-of-the-4th- Dairy
30. Hill MJ, Donald GE, Hyder MW, Smith RCG (2004) Estimation of pasture growth rate in the south west of Western Australia from AVHRR NDVI and climate data. Remote Sensing of Environment 93, 528-545. doi:10.1016/j.rse.2004.08.006
31. Holland KH, Lamb DW, Schepers JS (2012) Radiometry of proximal active optical sensors (AOS) for agricultural sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5, 1793-1802. doi:10.1109/JSTARS.2012.2198049
32. Isbell RF (2002) 'The Australian Soil Classification.' Revised edn (CSIRO Publishing: Melbourne)
33. Landsberg JJ, Waring RH (1997) A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management 95, 209-228. doi:10.1016/S0378- 1127(97)00026-1
34. Landsberg JJ, Prince SD, Jarvis PG, McMurtrie RE, Luxmoore R, MedlynBE (1997) Energy conversion and use in forests: An analysis of forest production in terms of radiation utilisation efficiency. In 'The use of remote sensing in the modeling of forest productivity'. Vol. 50. (Eds H Shimoda, H Gholz, K Nakane) pp. 273-298. (Springer: Dordrecht, the Netherlands)
35. Lauenroth WK, Hunt HW, Swift DM, Singh JS (1986) Estimating aboveground net primary production in grasslands: A simulation approach. Ecological Modelling 33, 297-314. doi:10.1016/0304-3800 (86)90045-1
36. Law BE, Waring RH (1994) Remote sensing of leaf area index and radiation intercepted by understory vegetation. Ecological Applications 4, 272-279. doi:10.2307/1941933
37. Leblon B, Guerif M, Baret F (1991) The use of remotely sensed data in estimation of PAR use efficiency and biomass production of flooded rice. Remote Sensing of Environment 38, 147-158. doi:10.1016/0034-4257(91)90076-I
38. Monteith JL (1972) Solar radiation and productivity in tropical ecosystems. Journal of Applied Ecology 9, 747-766. doi:10.2307/2401901
39. Moore KJ, Moser LE, Vogel KP, Waller SS, Johnson BE, Pedersen JF (1991) Describing and quantifying growth stages of perennial forage grasses. Agronomy Journal 83, 1073-1077. doi:10.2134/agronj1991.00021962 008300060027x
40. Myneni RB, Ramakrishna R, Nemani R, Running SW (1997) Estimation of global leaf area index and absorbed par using radiative transfer models. IEEE Transactions on Geoscience and Remote Sensing 35, 1380-1393. doi:10.1109/36.649788
41. Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ, Myneni RB, Running SW (2003) Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300, 1560-1563. doi:10.1126/science.1082750
42. Nix HA (1981) Simplified simulation models based on specified minimum data sets: The CROPEVAL concept. In 'Application of remote sensing to agricultural production forecasting'. (Ed. A Berg) pp. 151-169. (A.A. Balkema: Rotterdam, the Netherlands)
43. Nouvellon Y, Seen DL, Rambal S, Bégué A, Moran MS, Kerr Y, Qi J (2000) Time course of radiation use efficiency in a shortgrass ecosystem: Consequences for remotely sensed estimation of primary production. Remote Sensing of Environment 71, 43-55. doi:10.1016/S0034-4257(99) 00063-2
44. Oesterheld M, Sala OE, McNaughton SJ (1992) Effect of animal husbandry on herbivore-carrying capacity at a regional scale. Nature 356, 234-236. doi:10.1038/356234a0
45. Oesterheld M, DiBella CM, Kerdiles H (1998) Relation between NOAAAVHRR satellite data and stocking rate of rengelands. Ecological Applications 8, 207-212. doi:10.1890/1051-0761(1998)008[0207:
46. RBNASD]2.0.CO;2 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. doi:10.1016/j.jaridenv.2006.03.008
47. Paruelo JM, Epstein HE, Lauenroth WK, Burke IC (1997) ANPP estimates from NDVI for the Central Grassland Region of the United States. Ecology 78, 953-958. doi:10.1890/0012-9658(1997)078[0953:
48. Paruelo JM, Oesterheld M, Di Bella CM, Arzadum M, Lafontaine J, Cahuepé M, Rebella CM,[AEFNFT]2.0.CO;2 (2000) Estimation of primary production of subhumid rangelands from remote sensing data. Applied Vegetation Science 3, 189-195. doi:10.2307/1478997
49. Potter CS, Randerson JT, Field CB, Matson PA, Vitousek PM, Mooney HA, Klooster SA (1993) Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles 7, 811-841. doi:10.1029/93GB02725
50. Prince SD (1991) A model of regional primary production for use with coarse resolution satellite data. International Journal of Remote Sensing 12, 1313-1330. doi:10.1080/01431169108929728
51. Prince SD, Goward SN (1995) Global primary production: A remote sensing approach. Journal of Biogeography 22, 815-835. doi:10.2307/2845983
52. Rahman MM, Stanley JN, Lamb DW, Trotter MG (2014) Methodology for measuring fAPAR in crops using a combination of active optical and linear irradiance sensors: a case study in Triticale (X Triticosecale Wittmack). Precision Agriculture, in press. doi:10.1007/s11119-014-9349-6
53. Reeves MC, Winslow JC, Running SW (2001) Mapping weekly rangeland vegetation productivity using MODIS algorithms. Journal of Range Management 54, A90-A105.
54. Running SW, Nemani RR, Peterson DL, Band LE, Potts DF, Pierce LL, Spanner MA (1989) Mapping regional forest evapotranspiration and photosynthesis by coupling satellite data with ecosystem simulation. Ecology 70, 1090-1101. doi:10.2307/1941378
55. Running S, Thornton P, Nemani R, Glassy J (2000) Global terrestrial gross and net primary productivity from the earth observing system. In 'Methods in ecosystem science'. (Eds O Sala, R Jackson, H Mooney) pp. 44-57. (Springer-Verlag: New York)
56. Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H (2004) A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54, 547-560. doi:10.1641/0006-3568 (2004)054[0547:ACSMOG]2.0.CO;2
57. Runyon J, Waring RH, Goward SN, Welles JM (1994) Environmental limits on net primary production and light-use efficiency across the Oregon transect. Ecological Applications 4, 226-237. doi:10.2307/1941929
58. Sala OE, Biondini ME, Lauenroth WK (1988) Bias in estimates of primary production: An analytical solution. Ecological Modelling 44, 43-55. doi:10.1016/0304-3800(88)90081-6
59. Scurlock JMO, Johnson K, Olson RJ (2002) Estimating net primary productivity from grassland biomass dynamics measurements. Global Change Biology 8, 736-753. doi:10.1046/j.1365-2486.2002.00512.x
60. Sellers PJ (1985) Canopy reflectance, photosynthesis and transpiration. International Journal of Remote Sensing 6, 1335-1372. doi:10.1080/ 01431168508948283
61. Sellers PJ, Berry JA, Collatz GJ, Field CB, Hall FG (1992) Canopy reflectance, photosynthesis, and transpiration. III. A reanalysis using improved leaf models and a new canopy integration scheme. Remote Sensing of Environment 42, 187-216. doi:10.1016/0034-4257(92) 90102-P
62. Sellers PJ, Tucker CJ, Collatz GJ, Los SO, Justice CO, Dazlich DA, Randall DA (1994) A global 18 by 18 NDVI data set for climate studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing 15, 3519-3545. doi:10.1080/01431169408954343
63. Sheeby JE, Johnson IR (1988) Physiological models of grass growth. In 'The grass crop'. (EdsMJones,ALazenby) pp. 243-275. (Springer: Dordrecht, the Netherlands),.
64. Sinclair TR, Muchow RC (1999) Radiation use efficiency. In 'Advances in agronomy'. Vol. 65. (Ed. LS Donald) pp. 215-265. (Academic Press: Waltham, MA, USA)
65. Steinmetz S, Guerif M, Delecolle R, Baret F (1990) Spectral estimates of the absorbed photosynthetically active radiation and light-use efficiency of a winter wheat crop subjected to nitrogen and water deficiencies. International Journal of Remote Sensing 11, 1797-1808. doi:10.1080/01431169008955130
66. Taylor K, Griffith C, Lefort L, Gaire R, Compton M, Wark T, Lamb D, Falzon G, TrotterM(2013) Farming the web of things. Intelligent Systems, IEEE 28, 12-19. doi:10.1109/MIS.2013.102
67. Topp GC, Davis JL, Bailey WG, Zebchuk WD (1984) The measurement of soil water content using a portable TDR hand probe. Canadian Journal of Soil Science 64, 313-321. doi:10.4141/cjss84-033
68. Verhoef W (1984) Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remote Sensing of Environment 16, 125-141. doi:10.1016/0034-4257(84)90057-9
69. Vinayak SV, Apte SD (2013) Real time monitoring of agri-parameters using WSN for precision agriculture. International Journal of Advanced Research in Computer Science and Software Engineering 3, 1045-1048.
70. Yao AYM (1974) Agricultural potential estimated from the ratio of actual to potential evapotranspiration. Agricultural Meteorology 13, 405-417. doi:10.1016/0002-1571(74)90081-8
71. Zegelin SJ, White I, Jenkins DR (1989) Improved field probes for soil water content and electrical conductivity measurement using time domain reflectometry. Water Resources Research 25, 2367-2376. doi:10.1029/ WR025i011p02367