Agriculture Reference
In-Depth Information
sunflower and weeds, the aim being to establish a universal scale using a consistent
set of numeric codes that can readily be adapted to all crops (Table 2.2). Individual
scales for maize, pea, faba bean, sunflower and oilseed rape growth stages were
published respectively by Hanway (1963), Knott (1987, 1990), Schneiter and Miller
(1981), and Sylvester-Bradley
et al.
(1984); Chiarappa (1971) published keys for
numerous crops. The use of remote sensing with hand-held radiometers (section
2.5.4) offers possibilities for indirectly measuring crop growth stages based on
spectral reflectance changes from a healthy crop during plant growth. However,
accurate calibration of radiometer readings with existing decimalised codes for crop
growth stages in order to aid and standardize disease assessment would be desirable.
2.5 METHODS OF DISEASE ASSESSMENT
In any disease assessment or phytopathometric method, two criteria must be
satisfied; these were described by James (1983) as consistency between observers
and simplicity for speed of operation. These criteria, therefore, dictate that all
assessment methods should be well defined and standardized at the earliest possible
stage of their development. Campbell and Madden (1990a) pointed out that a
successful system for the assessment of disease gives results that are accurate,
precise and reproducible and presented the analogy of the target used by an archer
where the objective was to shoot all arrows into the centre circle of the target (Fig.
2.4): obviously, option A would be the most desirable for any assessment method.
Strange (2003) pointed out that although there is generally little disagreement
between observers at either end of a descriptive disease severity scoring scale (such
as 1-9), wide variation can occur in the central (often critical) part of the scale
especially if there are no visual prompts.
Disease can be measured using direct methods (i.e. assessing disease in or on
plant material) or indirect methods (e.g. monitoring the spore population using spore
traps). Obviously direct methods are likely to be more strongly correlated with yield
losses in the crop and are therefore to be preferred. However, recent methods
involving remote sensing and detection of crop stress due to disease are likely to
increase the accuracy of indirect disease measurements. Direct methods are
concerned with both the quantitative and qualitative estimations of disease.
2.5.1 Direct quantitative methods
Direct quantitative methods are largely concerned with measurements of incidence
or severity, defined as follows.
Disease incidence (
I
) = (number of infected plant units /
total number of plant units assessed) x 100
Disease severity (
S
) = (area of diseased tissue /
total tissue area) x 100
