Agriculture Reference
In-Depth Information
agriculture is considered as ecosystem manipulation rather than production, and this
approach could influence such activities as the assessment of disease in crop plants.
There exists little doubt that the need for disease assessment and yield loss appraisal
in the world's food crops is of paramount importance. Oerke and Dehne (1997)
concluded that although worldwide production of most crops has increased
considerably since 1965
,
losses in wheat, potatoes, barley and rice from pathogens,
pests and weeds simultaneously increased by 4% to 10% whereas in maize, soybean,
cotton and coffee losses remained unchanged or slightly decreased. These authors
also concluded that the efficacy of crop protection varied for different crops, being
highest (55%) in cotton but reaching only 34% to 38% in rice, wheat and maize.
However variability between world cropping areas was high in terms of actual
prevention of crop losses with a worldwide crop protection efficiency of only 40%.
Johnson
et al
. (2003) quantified the economic impact of
Fusarium
ear blight in
wheat in the USA. During 1991-1997 production losses and price effects resulted in
direct losses totalling more than $1.3 billion whereas the total economic impact of
the disease on affected rural communities and agribusinesses related to grain
production and marketing was three to four times this amount. Not since potato late
blight has a plant disease caused as much social havoc as
Fusarium
ear blight
(McMullen, 2003).
Although traditional methods of disease assessment will continue to find a place
in modern agriculture, technological advances in the application of computer
programmes for estimating disease severity with variegated disease patterns have
improved the accuracy of observers in the field and have removed, at least in part,
the subjective element of phytopathometry and the effect of several confounding
factors. Detailed data analyses such as those undertaken by Hughes
et al.
(1997)
have revealed the complexities and consequences of aggregated data in spacial
hierarchies when estimating disease incidence. Furthermore, the now widespread
use of immunological and molecular nucleic acid-based techniques for the
identification of disease organisms has increased our capability to accurately
measure disease incidence in infected plant tissue; in the last few years the
development of robust diagnostic kits for use by the farmer or grower (as dip-sticks
or dot-blots) has simplified such technology in the field for the detection and
quantification of fungal and bacterial plant pathogens (Strange, 2003).
The increasing use of remote-sensing technology for estimating disease damage
to crops is having a continuing impact on the science of phytopathometry, from the
use of sophisticated hand-held radiometers to satellite imagery. The development of
high resolution technology, such as synthetic aperture radar (SAR) has greatly
improved the effectiveness of satellite imagery in countries where cloud cover has
been a serious impediment to the progress of this methodology. Monitoring
agriculture with remote sensing (MARS) has become an increasingly common form
of GIS technology. However, it is likely that remote sensing at this magnitude will
remain an indirect method of assessing plant disease through the detection of crop
stress due to biotic or abiotic factors, rather than directly measuring reductions in
leaf area due to disease. In the laboratory, the availability of relatively inexpensive
true-colour image analysis systems for analyzing diseased leaf area percentages has
increased the accuracy of disease assessments at this level.
