Agriculture Reference
In-Depth Information
illustration of the diversity of the constituents of a DSN, McRoberts
et al
. (2000)
found that up to eight different types of person (spouse, business partner, children,
accountant, advisor, commercial representative, lawyer, employee) were consulted
occasionally
by a group of Scottish arable farmers when making crop protection
decisions. No farmer who provided information for the study
never
consulted anyone
when making a crop protection decision. The three most frequently reported types of
person who were
always
consulted were: advisors (36% of respondents), commercial
representatives (24%) and business partners (22%). Whether a new IT-based tool is of
type (1) or type (2) it is likely to have to compliment, rather than replace, the activities
of the DSN. Within the context of the DSN, DSSs might be better thought of as
Discussion Support Systems. On this basis future developments might most
effectively be targeted on type (2) tools which are intuitive to use and which focus on
the key decision to be made, leaving the DSN to supply the additional, background
information often contained in a DSS. These comments notwithstanding, there are, of
course, successful examples of type (1) tools in use. We briefly describe some of these
in the next section, before dealing with some generic issues of the efficacy of tools,
using examples of type (2) tools in the final section.
12.8 SOME EXAMPLES OF DSS
So far in this chapter we have dealt in broad terms with sources and presentation of
information relevant to plant disease epidemiology. In attempting to raise some
issues concerning the availability and quality of information that can be obtained
directly on the desktop of the modern epidemiologist we have largely concentrated
on sources of information of use to epidemiologists and on the use of IT simply in
making information available. In this section we report some proven or historical
examples of IT and DSSs. In the following section we consider recent developments
in epidemiology for situations where IT is used in attempts to put epidemiology into
practice for the purpose of forecasting disease and making crop management
decisions. Disease forecasting is also dealt with in Chapter 9.
In Denmark a DSS for crop protection called 'PC-Plant Protection' was devised
motivated by a decision made in 1986 to reduce pesticide use in Denmark by 50%.
The Danish Institute of Plant and Soil Science and the Danish Agricultural Advisory
Centre chose to implement their research findings with a detailed use of threshold
values to support decisions on treatment need, choice of pesticides and the
appropriate dosage for the actual problem using a PC programme. This is not
available on the internet as it is licensed to users. Even as far back as 1996, 2800
licences were in use at agricultural schools and with advisers and farmers. It was
judged to be user-friendly and the model was considered to be reliable and to meet
the requirements of advisers. In 1996, a farm survey of 488 farmers who had used
the system in 1995 showed that the system has been well accepted by farmers, not
only because of its reliable recommendations but also because of the good
profitability that resulted from its use. It also enabled Denmark to make substantial
progress in pesticide input reductions. Development continued with a weather
module, taking into account detailed weather information and an environmental
