Agriculture Reference
In-Depth Information
Yields were expressed as relative to the maximum in each trial (weed-free plot
yield), duration of competition (DC) was expressed in units of thermal time
(TTUs) from sowing (see Chapter 4), thereby including effects of temperature
as well as time, and weed competition was quantified as the 'weed load' (WL =
the sum over all the species present of their plant densities multiplied by 'their
competitiveness indexes'). Different weed species were given a 'competitiveness
index' based on the degree to which their presence had been found to lower
maize yields. Up to 75% of the variation in relative yields between fields and
seasons caused by weed competition was explained by regressions on DC and
WL. For a weed flora of average competitiveness it took 220 TTUs (base
temperature 7.2°C) before commencing weeding to cause a 5% decrease in
relative yield with 20 weeds/m
2
, and 315 TTUs with five weeds/m
2
. Relative
yields decreased at about these respective rates for each weed density as the
thermal time before weeding was prolonged. Equation 5.1, which describes the
response surface shown in Fig. 5.2 (Dunan
et al.
, 1996, Fig. 2) was the most
meaningful summary of the results:
Onion Relative Yield = 0.83 - {1.5.10
5
DC
1.198
(Eqn 5.1)
[WL/(1 + 0.2
WL)]}
Several dynamic simulation models of weed competition in allium crops
have been developed (Dunan
et al.
, 1999; Baumann
et al.
, 2002; Grundy
et al.
,
2005). These all model competition for light and therefore apply to the
situation in crops without significant competition for water or nutrients, a
reasonable assumption for irrigated crops. In these models, onions and weeds
are assumed to grow as they would in the absence of competition until the leaf
canopy approaches closure (i.e. when Leaf Area Index (LAI) exceeds unity).
Then, the fraction of the incident light that is apportioned to crop or weed
species, and which therefore drives the subsequent growth of each species, is
specified by rules considered adequate to describe the real situation. For
example, in Dunan
et al.
(1999), growth rate in a competitive situation is the
growth rate of an isolated plant at the prevailing temperature multiplied by a
competition factor, cf
i
, appropriate to the species. The competition factor
models the fraction of the total incident light that the species captures. This is
determined by the leaf area index of the species (LAI
i
) weighted by its light
extinction coefficient, k
i
, derived from its equivalent of Eqn 4.1, relative to the
sum of such weighted LAIs for all the species in the competitive situation. Thus,
for the ith species competing among a total of n species:
i=n
cf
i
= k
i
LAI
i
/(
k
i
LAI
i
)
(Eqn 5.2)
i=1
With these models it is possible to incorporate parameters that describe the
growth rate of individual plants of a species (e.g. k
i
and the parameters that
