Impacts on Plant Pathogens - Climate Resilient Agriculture for Ensuring Food Security - page 170

Table 8.4 Commercially available genetically modifi ed crops for disease resistance (Castle et al. 2006 )

Year of fi rst
commercial
sale

Trait
phenotype

Target trait
gene(s)

Trait
designation Originating company

Crop Trade name

Squash Resistance a to

CMV, WMV2,
and ZYMV

Coat protein genes
of CMV, WMV2,
and ZYMV

CZW3 Asgrow; Seminis

Vegetable Seeds
(now Monsanto)

1998 Destiny III,

Conqueror III,
Liberator III

Resistance a to
WMV2 and
ZYMV

Coat protein genes
of WMV2 and
ZYMV

ZW-20 Asgrow; Seminis

Vegetable Seeds
(now Monsanto)

1995 Preclude II, Patriot

II, Declaration II,
Independence II

Papaya Resistance a to

PRSV

Coat protein gene
of PRSV

55-1 Cornell university;

University of
Hawaii, USDA

1998 SunUp, Rainbow

63-1

a CMV cucumber mosaic virus, PRSV papaya ring spot virus, WMV2 watermelon mosaic virus, ZYMV zucchini yellow
mosaic virus

hypotheses and to determine critical relation-
ships to help develop process-based approaches.
Field-based research examining the infl uence of
a combination of interacting factors (Norby et al.
1997 ) would be needed to provide a more realis-
tic appraisal of impacts. Methodology to model
climate change impact has not been fully devel-
oped. Some of the impact assessments (Brasier
and Scott 1994 ) are “fi rst pass analysis” using
climate-matching software such as BIOCLIM
(Busby 1991 ), HABITAT (Walker and Cocks
1991 ), or CLIMEX (Sutherst and Maywald
1985 ). Some have used and advocated the use of
simulation models (Luo et al. 1995 ; Teng et al.
1996 ). However, their use is currently limited due
to a lack of hard data on impacts. Empirical pro-
cedures for assessing long-term climate and dis-
ease interactions are only just beginning to
emerge (Scherm and Yang 1995 ; Coakley and
Scherm 1996 ). There is a need to look beyond the
science of plant pathology to seek and invite con-
cepts and ideas from other relevant disciplines
for a reappraisal of priorities. Developments in
information technology can help in the quest for
knowledge and its dissemination (Bridge et al.
1998 ).
Knowledge needs to be acquired, synthesized,
and generalized at a scale relevant to an environ-
mental unit. Impact on an agricultural system
must include on- and off-farm effects determined
at a landscape scale of spatial resolution.
Historically plant pathology research using site-
specifi c knowledge of individual pathosystems

has served well in understanding, predicting, and
managing diseases. Environmental variables at
the microclimate level have been utilized at this
spatial scale. In contrast, climate systems operate
at a global scale, and general circulation models
(GCMs) are better at explaining climate at this
coarse level of resolution. This difference in the
level of understanding between plant pathology
and biometeorology/climatology at the various
spatial and temporal scales has hampered inter-
disciplinary interaction. The need to bridge this
gap in knowledge has been recognized (Kennedy
1997 ). In recent years, a number of attempts have
been made to downscale GCM outputs to a bio-
logically relevant mesoscale (Bardossy 1997 ).
Lack of epidemiologically relevant weather vari-
ables has been an impediment to the application
of GCMs and other climate models to plant dis-
ease modeling. Duration of surface wetness and
relative humidity, which critically infl uence
infection and disease development by many plant
pathogens, have not been easily obtained from
GCM output until recently. Usefulness of
remotely gathered site-specifi c wetness and other
data for plant pathology research has been vari-
able (Gleason et al. 1997 ), and Seem et al. ( 2000 )
provide a more detailed discussion on this topic.

8.12 Research Needs

Research needs to be undertaken on the follow-
ing lines: