Maclean et al. - 2002 - Rice almanac source book for the most important e
Maclean et al. - 2002 - Rice almanac source book for the most important e
Maclean et al. - 2002 - Rice almanac source book for the most important e
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eing developed at IRRI. Similar biosaf<strong>et</strong>y<br />
committees have been established in o<strong>the</strong>r ricegrowing<br />
countries in Asia.<br />
One of <strong>the</strong> princip<strong>al</strong> biosaf<strong>et</strong>y issues is <strong>the</strong><br />
assessment of <strong>the</strong> movement of <strong>for</strong>eign genes by<br />
pollen dispers<strong>al</strong> from transgenic rice to o<strong>the</strong>r rice<br />
vari<strong>et</strong>ies and wild rice. In 1995, IRRI began<br />
operating a greenhouse designed to prevent pollen<br />
dispers<strong>al</strong> from transgenic plants in <strong>the</strong> early<br />
stages of ev<strong>al</strong>uation. This 320-m 2 greenhouse<br />
enables researchers to grow and multiply<br />
transgenic plants and to ev<strong>al</strong>uate <strong>the</strong>m <strong>for</strong><br />
resistance to insects, disease, and o<strong>the</strong>r stresses.<br />
A recent study using transgenic IR72 with Xa21<br />
in a screenhouse reve<strong>al</strong>ed that <strong>the</strong>re was no<br />
function<strong>al</strong> transfer of transgenes from transgenic<br />
IR72 to nontransgenic control plants, a finding<br />
that ensures <strong>the</strong> potenti<strong>al</strong> use of this technology<br />
in improving rice germplasm.<br />
Crop modeling to integrate<br />
knowledge<br />
Crop modeling enables researchers to integrate<br />
knowledge from different disciplines in a<br />
quantitative way. That, in turn, helps researchers<br />
to understand <strong>the</strong> underlying processes that<br />
d<strong>et</strong>ermine <strong>the</strong> behavior of complex agricultur<strong>al</strong><br />
systems. Ma<strong>the</strong>matic<strong>al</strong> models are representations<br />
of systems made from ma<strong>the</strong>matic<strong>al</strong> equations.<br />
Integrating and solving <strong>the</strong> equations<br />
enable a numeric<strong>al</strong> description of <strong>the</strong> system to<br />
be produced. During <strong>the</strong> first phase of a<br />
modeling exercise, <strong>the</strong> modeler seeks to give<br />
names, magnitudes, and units to <strong>the</strong> component<br />
parts of <strong>the</strong> problem. In <strong>the</strong> second phase of<br />
modeling a problem, <strong>the</strong> processes are described<br />
as ma<strong>the</strong>matic<strong>al</strong> functions. In <strong>the</strong> fin<strong>al</strong> phase,<br />
“what-if” questions can be asked about <strong>the</strong><br />
functioning of a system and numeric<strong>al</strong> answers<br />
provided. Ma<strong>the</strong>matic<strong>al</strong> models that contain no<br />
clear logic<strong>al</strong> link with <strong>the</strong> basic processes governing<br />
<strong>the</strong> relationship b<strong>et</strong>ween <strong>the</strong> system inputs<br />
and outputs are unlikely to contribute much of<br />
significance to any debate concerning strategic<br />
decisions in relation to research management.<br />
Models at different levels of d<strong>et</strong>ail are<br />
developed to me<strong>et</strong> different objectives, ranging<br />
from a thorough understanding of an existing<br />
system to <strong>the</strong> prediction of crop production in<br />
untested conditions. Four types of crop production<br />
systems can be distinguished:<br />
1. Potenti<strong>al</strong> production, where production is<br />
d<strong>et</strong>ermined by solar radiation,<br />
temperature, and crop and vari<strong>et</strong><strong>al</strong><br />
characteristics.<br />
Transgenic greenhouse at IRRI.<br />
Internation<strong>al</strong> issues 43