Agriculture Reference
In-Depth Information
Fig. 8.4
Factors impacting
the crop growth and
management system that are
often incorporated in
system-level studies. Factors
in
blue circles
are related to
the environment, factors in
green circles
are related to
the genotype, and factors in
gray circles
are related to the
management
• Biomass production: Most models use the crop-specifi c radiation use effi ciency
(RUE) approach where the total intercepted radiation gives the total biomass
production. However, the photosynthesis and respiration (PR) approach and the
biochemical approach have also been used.
• Biomass partitioning: The total biomass produced is partitioned into different
compartments. Many models use only two compartments, namely, aboveground
and belowground. However, additional compartments have also been considered
in some models.
Based on this background, some important models that have been used for bio-
energy crop growth are discussed below and a summary is presented in Table
8.1
.
The informatics-related issues are presented towards the end of this section.
8.3.1.1
Review of Model
EPIC (Erosion Productivity Impact Calculator) model, also known as the
Environmental Policy Integrated Climate model, was developed in the 1980s to
study the relationship between soil erosion and soil productivity over many years
[
29
]. One of the nine modules relates to crop growth and determines the total bio-
mass yield per unit area for a crop using the RUE approach. The drainage area con-
sidered is generally small and about 1 ha [
29
]. Although the simulations are
performed for a specifi c location, results can be extended to larger watersheds by
assuming consistency in soil properties and climate. The model also has an interac-
tive data entry system as well as data analysis options, which enable it to be used as
a DSS. Brown et al. [
30
] used the EPIC model to simulate switchgrass yield for dif-
ferent nitrogen application rates as well as for different climate change scenarios
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