What Will Increasing Corn Acreage Do To Nematode Populations In The Mid South Implications For Future Nematode Management Strategies
Wes Kirkpatrick
Arkansas Cooperative Extension Service
Historically, mid-South cropping systems
generally fell into one of three broad categories:
monoculture of cotton, rice, or soybean,
a soybean-rice rotational system, or a
soybean-wheat double-cropping system. In the
last few years, however, the economic outlook for
corn as a viable crop in the region has
changedthe cropping patterns for many growers.
As a “new” crop is added to our system, crop
pest dynamics may be altered and pest management
strategies may need to be adjusted. Plantparasitic
nematodes are resident in the soil in
essentially every field. Although some nematode
species have not been considered to be of major
economic significance, three species are of concern
across the mid-South region: the southern
root-knot nematode (RKN), the reniform nematode
(RN), and the soybean cyst nematode (SCN).
These three nematodes account for about 90%
of the nematode-induced yield suppression in
cotton and soybean in the four-state region. A
significant increase in corn acreage is likely to
change the status quo of our current concepts
of nematode management as our cropping patterns
change. Two major questions that must
be addressed are: 1) How will the introduction of
corn into our cropping systems affect the population
densities of these nematodes in relation to
cotton and soybean, and 2) Will these (or other)
nematodes be of economic concern in corn?
While very little research has been conducted in
the region to answer either of these questions,
there is considerable useful basic information regarding
the ecology and biology of nematodes in
relation to corn production in other areas of the
country. This information provides a platform
for some general concepts and recommendations
until research to address specific problems and
questions can be conducted. Each nematode
and host plant relationship is unique. For example,
SCN has a narrow host range that includes
soybean and a few leguminous weeds.
Rotation of soybean with corn can dramatically
lower SCN populations. Interestingly enough,
our traditional soybean-rice cropping sequence
has been much less effective in lowering SCN
populations. Consequently, addition of corn as
a regular component of a rotational sequence
with soybean can be expected to aid in the management
of SCN. Similarly, corn is not a host
for RN. Inclusion of corn in rotation with either
soybean or cotton can lower RN populations although
rapid resurgence in the nematode population
is likely once a susceptible crop is grown
in the field (Figure 1). Once again, corn as a regular
component of a cropping sequence that includes
cotton and (or) soybean will likely be of
benefit to the overall productivity of the cropping
system. Unfortunately, growing corn in a field
where RKN is present may exacerbate an existing
problem or create a problem where one did
not exist. Most currently popular corn hybrids
that have been evaluated are susceptible to RKN.
Production of corn in fields where RKN is present
is likely to increase RKN population densities
and may be particularly problematic for crops
grown subsequently in the rotation sequence.
Although it is relatively easy to predict the impact
of corn on nematode population dynamics,
there is little recent experimental data in the
mid-South to indicate the actual importance of
nematodes in corn yield performance. Several
nematode species including RKN, the lesion
nematode and the stubby-root nematode have
been reported to suppress corn yields in other
regions of the country. Records from the
Arkansas Nematode Diagnostic Laboratory during
the past five years indicate that all three of
these nematode species are frequently encountered
in samples from corn fields in the state
that were submitted to the laboratory for nematode
assay. It is likely that nematodes will be a
factor in corn production for some growers, but
research and grower experience will be required
before their significance can be accurately quantified.
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