Quantifying the benefits of accounting for yield potential in spatially and seasonally responsive nutrient management in a Mediterranean climate
Y. M. Oliver A B and M. J. Robertson AA CSIRO Sustainable Ecosystems, Private Bag 5, PO Wembley, WA 6913, Australia.
B Corresponding author. Email: Yvette.Oliver@csiro.au
Australian Journal of Soil Research 47(1) 114-126 https://doi.org/10.1071/SR08099
Submitted: 28 April 2008 Accepted: 13 October 2008 Published: 18 February 2009
Abstract
Crop yield potential is a chief determinant of nutrient requirements, but there is little objective information available on the gains in profitability that can be made by accounting for the influences of soil type and season on yield potential when making fertiliser decisions. We conducted such an assessment using crop growth simulation coupled to nutrient response curves for wheat-growing at 4 locations in the low-medium rainfall zone of Western Australia. At each location, the yield potential was simulated on 10 soil types with plant-available water capacity (PAWC) ranging from 34 to 134 mm, which represent the major soils types in Western Australia. Soil survey maps were available to quantify soil type variability and the historical climate record (1974–2005) for seasonal variability.
The benefits possible for fertiliser (NPK) management that takes account of variation in crop yield potential due to season and soil type by having ‘perfect knowledge’ ranged from $2 to 40/ha. Seasonal variation was more important than soil type for the better soils (high PAWC), providing two-thirds of the benefit of perfect knowledge. On low PAWC soils, knowledge of soils and seasonal influences on yield potential were similar contributors to profit gains. An assessment of one yield forecasting system showed that about 50% of the maximum gains could be captured if seasons could be categorised as below, at, or above average at the time the fertiliser decision is made. In each catchment, 30–40% of fields showed scope for benefits in accounting for within-field variation in soil type due to large variation in PAWC, and therefore yield. Maximum profit gains and reductions in nutrient excess were greater in the low rainfall locations and also on the low PAWC soil types.
Acknowledgments
This study was funded by CSIRO and the Grains Research and Development Corporation. The cooperation of growers in the Wallatin–O’Brien and Mingenew–Irwin catchments is acknowledged. Martin Wells of Land Assessment Pty Ltd provided the soil map for Wallatin–O’Brien and the Department of Agriculture and Food Western Australia provided the soil map for Mingenew–Irwin. Fulco Ludwig assisted with the analysis.
Adams ML,
Cook S, Bowden JW
(2000) Using yield maps and intensive soil sampling to improve nitrogen fertilizer recommendations from a deterministic model in the Western Australian wheatbelt. Australian Journal of Experimental Agriculture 40, 959–968.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
(accessed 20 April 2006).
French RJ, Schultz JE
(1984) Water use efficiency of wheat in a Mediterranean-type environment. I. The relation between yield, water use and climate. Australian Journal of Agricultural Research 35, 743–764.
| Crossref | GoogleScholarGoogle Scholar |
(accessed 19/12/07)
Irmak A,
Batchelor WD,
Jones JW,
Paz JO,
Beck HW, Egeh M
(2002) Relationship between plant available soil water and yield for explaining soybean yield variability. Applied Engineering in Agriculture 18(4), 472–482.
Keating BA,
Carberry PS,
Hammer GL,
Probert ME,
Robertson MJ,
Holzworth D,
Huth NI,
Hargreaves JNG,
Meinke H,
Hochman Z,
McLean G,
Verburg K,
Snow V,
Dimes JP,
Silburn DM,
Wang ME,
Brown S,
Bristow KL,
Asseng S,
Chapman S,
McCown RL,
Freebairn DM, Smith CJ
(2003) An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18, 267–288.
| Crossref | GoogleScholarGoogle Scholar |
Kingwell R, Pannell D
(2005) Economic trends and drivers affecting the wheatbelt of Western Australia to 2030. Australian Journal of Agricultural Research 56, 553–561.
| Crossref | GoogleScholarGoogle Scholar |
Lobell DB,
Ortiz-Monasterio JI, Asner GP
(2004) Relative importance of soil and climate variability for nitrogen management in irrigated wheat. Field Crops Research 87, 155–165.
| Crossref | GoogleScholarGoogle Scholar |
Marshall GR,
Parton KA, Hammer GL
(1996) Risk attitude, planting conditions and the value of seasonal forecasts to a dryland wheat grower. Australian Journal of Agricultural Economics 40, 211–234.
McBratney A,
Whelan B,
Ancev T, Bouma J
(2005) Future directions of precision agriculture. Precision Agriculture 6, 7–23.
| Crossref | GoogleScholarGoogle Scholar |
Meinke H, Stone RC
(2005) Seasonal and inter-annual climate forecasting: the new tool for increasing preparedness to climate variability and change in agricultural planning and operations. Climatic Change 70, 221–253.
| Crossref | GoogleScholarGoogle Scholar |
Morgan CLS,
Norman JM, Lowery B
(2003) Estimating plant-available water across a field using an inverse model. Soil Science Society of America 67, 620–629.
|
CAS |
Pringle MJ,
McBratney AB,
Whelan BM, Taylor JA
(2003) A preliminary approach to assessing the opportunity for site-specific crop management in a field, using yield monitor data. Agricultural Systems 76, 273–292.
| Crossref | GoogleScholarGoogle Scholar |
Probert ME,
Dimes JP,
Keating BA,
Dalal RC, Strong WM
(1998) APSIM’s water and nitrogen modules and simulation of the dynamics of water and nitrogen in fallow systems. Agricultural Systems 56, 1–28.
| Crossref | GoogleScholarGoogle Scholar |
Robertson MJ, Kirkegaard JA
(2005) Water-use efficiency of dryland canola in an equi-seasonal rainfall environment. Australian Journal of Agricultural Research 56, 1373–1386.
| Crossref | GoogleScholarGoogle Scholar |
Robertson MJ,
Lyle G, Bowden JW
(2008) Within-field variability of wheat yield and economic implications for spatially-variable nutrient management. Field Crops Research 105, 211–220.
| Crossref | GoogleScholarGoogle Scholar |
Smith IN,
McIntosh P,
Ansell TJ,
Reason CJC, McInnes K
(2000) Southwest Western Australian winter rainfall and its association with Indian Ocean climate variability. International Journal of Climatology 20, 1913–1930.
| Crossref | GoogleScholarGoogle Scholar |
Turner NC
(1992) Crop production on duplex soils: an introduction. Australian Journal of Experimental Agriculture 32, 797–800.
| Crossref | GoogleScholarGoogle Scholar |
Whelan BM, McBratney AB
(2000) The ‘null hypothesis’ of precision agriculture management. Precision Agriculture 2, 265–279.
| Crossref | GoogleScholarGoogle Scholar |
Wong MTF, Asseng S
(2006) Determining the causes of spatial and temporal variation of wheat yields at sub-field scale using a new method of upscaling a crop model. Plant and Soil 283, 203–215.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Wong MTF,
Corner RJ, Cook SE
(2001) A decision support system for mapping the site-specific potassium requirement of wheat in the field. Australian Journal of Experimental Agriculture 41, 644–661.
| Crossref | GoogleScholarGoogle Scholar |
Wong MTF,
Oliver Y, Robertson MJ
(2009) Gamma-radiometric assessment of soil depth across a landscape not measurable using electromagnetic surveys. Soil Science Society of America Journal (in press) ,
Zhang N,
Wang M, Wang N
(2002) Precision agriculture: a worldwide overview. Computers and Electronics in Agriculture 36, 113–132.
| Crossref | GoogleScholarGoogle Scholar |
