Geoscience Reference
In-Depth Information
many tropical environments characterised by limited inputs
and semi-arid climate.
The CERES-Rice model is a process-oriented, management-
level model of rice crop growth and development that predicts the
duration of growth, the average growth rates and the amount of
assimilate partitioned to the economic yield components of the
plant (Hundal and Kaur, 1999). The simulation processes of the
model are dynamic and are affected by environmental and culti-
var-specific factors. The duration of growth for a particular culti-
var, however, is highly dependent on its thermal environment and
to some extent the photoperiod during floral induction. Therefore,
the model requires input data such as daily weather data, initial
soil conditions, crop management and crop cultivar informa-
tion. The daily weather data includes solar radiation, precipita-
tion, maximum and minimum temperature. Initial soil conditions
involve drainage and runoff coefficients, initial soil water, rooting
preference factors, organic nitrogen and carbon contents. The out-
put data for each model simulation run encompasses the results
of simulated daily growth and development, carbon balance, soil
water balance, nitrogen balance and mineral nutrient aspects.
3.6
Conclusion
Crop modelling can play a significant role in system approaches
by providing a powerful capability for scenario analysis. Crop
modelling has developed extensively over the past 30 years and
a diverse range of crops models are now available. It is argued,
however, that the tendency to distinguish between and sepa-
rate the so-called 'scientific' and 'engineering' challenges and
approaches in crop modelling has constrained the maturation of
modelling. It is considered that effective crop modelling must
combine a scientific approach to enhance understanding with
an applications orientation to retain a focus on prediction and
problem-solving. Greater use of crop simulation models has
also been suggested to increase the efficiency of different tri-
als. While simulation models successfully capture the temporal
variation, they use a lumped parameter approach that assumes
the spatial variability of the soils, crops or climate.
References
Aggarwal, P.K., Banerjee, B., Daryaei, M.G., Bhatia,
A., Bala, A., Rani, S., Chander, S, Pathak, H.
and Kalra, N. 2006. InfoCrop: A dynamic simulation model
