Coping with variability in agricultural production -implications for soil testing and fertiliser management

• Published in: Communications in soil science and plant analysis 2000-06, Vol.31 (11-14), p.1531-1551
• Main Authors: Cook, S. E., Bramley, R. G. V.
• Format: Article
• Language: English
• Subjects: Agronomy. Soil science and plant productions; Biological and medical sciences; Fundamental and applied biological sciences. Psychology; Methods and techniques; Soil science
• ISSN: 0010-3624; 1532-2416
• DOI: 10.1080/00103620009370524

Decisions about fertiliser applications are fraught with uncertainty. Uncertainty about the outcome of an application of fertiliser is caused by unknown or uncontrolled variation about the condition of the soil to which it is applied, its fate, and the demand from the crop. Uncertainty can be eased by providing information which reduces ignorance about the likely outcomes of applying fertiliser, thereby increasing the decision-maker's chances of success. Such information could include analyses of soil and plant tissue, prior information about crop performance, and predictions of climate and prices. This information could be used to improve the rate, location and timing of applications. Precision agriculture technology greatly enhances our ability to acquire and manage more of this information. However, information costs money, which must be traded-off against the greater likelihood of success. This trade-off is very difficult to evaluate, and in practice depends on a range of factors, including the availability of data, current understanding of its meaning and the preferences of the decision-maker. Research in the Western Australia (WA) wheatbelt, suggests that conventional soil testing is of limited value in explaining variability of crop response in the field. Possible reasons for this include the inadequate representation of major sources of variation - in particular water availability, weeds or disease; inaccurate representation of nutrient uptake mechanisms; and errors of calibration over large agro-ecological regions and wide ranges in soil types or properties. We suggest that this situation may be improved somewhat by more sensitive methods which can reflect small but significant variations in soil chemistry and nutrient availability, and more localised test calibration. However, such improvements may do little to ease the problem of confounding sources of variation. Using field-scale examples, this paper examines the scale of variability with which the decision-maker must cope, and some options that are available to handle it.