Precision farming is the process of adjusting husbandry practices within a
field according to measured spatial variability. In this review, we explore
the prospects for precision farming using the principles that underly conv
entional soil management and agronomy.
The cost-effectiveness of precision farming is determined by the cost of de
fining zones within fields, the stability of zones through time, the differ
ence in treatment between zones in terms of cost, and the responsiveness of
the crop in terms of yield and quality to changes in treatment. Cost-effec
tive precision farming is most likely where prior knowledge indicates large
heterogeneity and where treatment zones can be predicted, for example from
soil type or field history.
Soil related factors are likely to provide the main basis for precision far
ming because they tend to be stable through time and influence crop perform
ance. In particular, soil mapping may usefully indicate the moisture availa
ble for crop growth, organic matter maps may be utilized for precision appl
ication of fertilizers and soil acting herbicides, and variation in soil pH
can be mapped and used as a basis for variable lime application. However,
comprehensive nutrient mapping is less likely to be economic with existing
techniques of chemical analysis. The value of yield mapping lies in identif
ying zones which are sufficiently stable to be of use in determining future
practices. Maps of grain quality and nutrient content would significantly
augment the value of yield maps in guiding marketing decisions and future a
gronomy. Interactions between soil differences and seasonal weather are lar
ge, so yield maps show considerable differences from season to season. Inte
rpretation of such maps needs to follow a careful, informed, analytical pro
cess.
Extensive and thorough field experimentation by crop scientists over many y
ears has shown that yield variation arises as a result of a large and compl
ex range of factors. It is highly improbable that simple explanations will
be appropriate for much in-field field variation. However, the capacity to
sense yield variability within fields as opposed to between fields, where t
here are many confounding differences, provides an opportunity for the indu
stry to improve its understanding of soil-based effects on crop performance
. This should support its decision taking, whether through precision farmin
g or through field-by-field agronomy.
The main obstacle to the adoption of precision farming is the lack of appro
priate sensors. Optimal sensor configurations that will measure the specifi
c needs identified by end-users need to be developed.
The conclusions reached in this paper probably apply to farming throughout
northern Europe.