Agriculture Reference
In-Depth Information
Figure 2.1. (A) Path (broken line) generated by the computer system (Field Runner) used to
direct the operator to the sampling sites (solid lines) of a stratified random design. (B) One
sector composed of two-row beds of individual plants (points) and a randomly located
transect selected within the sector (bracketed area). (C) Two-row transect with 30 plants per
row. (From Delp
et al
.
,
1986a).
whatever the sampling regime and Hughes (1999) described operating characteristic
(OC) curves as instrumental in establishing and evaluating the performance of
sampling schemes; these were affected by the sampling distribution of pathogen
intensity and by sampling size (Madden and Hughes, 1999b). In a separate paper,
Madden and Hughes (1999a) explored the relationship between disease incidences at
two levels (field and individual plants) in a spatial hierarchy in order to find a simple
approximation (effective sample size) to interrelate incidence at the two levels; they
concluded that it was possible to predict incidence at the lower level from incidence
at the higher level in the presence of aggregation without using the complicated
beta-binomial function, making it easier to use group sampling.
2.4 TIMING AND FREQUENCY OF DISEASE ASSESSMENT
Disease assessment data must be qualified by the growth stage of the crop or plant at
the time of the assessment. This is because the effects of a given level of disease on
plant growth and yield and the importance of that disease level in relation to the
progress of an epidemic will vary at different plant growth stages. Consequently, it
is important to be familiar with the keys currently available and other methods, for
