Systems Informatics and Analysis - Engineering and Science of Biomass Feedstock Production and Provision - page 203

in grams of CO 2 equivalent. It can perform calculations for switchgrass, Miscanthus,
hybrid poplar, and willow in addition to conventional crops.
The Integrated Farm System Model (IFSM), a whole-farm simulation model, has
been developed to assist sustainable management of livestock farming for the dairy
and beef industries [ 67 ]. Although the focus of this model is on livestock farming,
it includes perennial grasses and forage crops. It is a long-term strategic planning
tool. The model consists of nine major submodels including a forage cropping sub-
model, storage and animal submodels, tillage and manure handling submodels, and
a corn growth model based on the CEREZ-maize model. Since it is a very generic
model incorporating a large number of possibilities, scenario setup becomes an
important task in which the user has to select many parameters. Rotz et al. [ 67 ] have
emphasized the value of crosschecking and validating model parameters. The model
has also been proposed as a teaching and extension aid.
The Farmdoc website ( http://farmdoc.illinois.edu/index.html ) maintained by the
University of Illinois at Urbana-Champaign is an excellent source of information
for on-farm decision making. In addition to documentation and extension presenta-
tions, the website provides web-based access to FAST (Farm Analysis Solution
Tools). These are spreadsheet-based tools for various farming-related activities such
as farm management, fi nancial analysis, loan analysis, livestock management, and
risk management. This is an excellent example of how simple to use decision-
making tools can be made accessible via Internet. Easy to understand demos are
also provided. Although the modeling component in FAST is relatively simple, the
informatics aspects, including database management and web accessibility, are par-
ticularly impressive.

8.3.2.2 Equipment Selection and Management Tools

Optimization of farm machinery selection for energy crops is extremely critical.
Although this topic has been extensively studied for conventional crops, unique
challenges associated with energy crops require further investigation. These chal-
lenges include managing grain as well as residue collection simultaneously, sharing
machinery with regular crop harvest, managing harvesting during severe weather
conditions, and accounting for the perennial nature of these crops.
Wold [ 68 ] developed a simulation model to improve the effi ciency of single pass
crop harvest and residue collection. A variety of biomass collection options after
grain harvest, such as direct unloading by the harvester and baling, are considered.
For the baling option, bale collection was also simulated and three different
heuristics-based algorithms were compared to solve the vehicle routing problem.
For each of these options, varying cart capacity and number of carts were consid-
ered to model different scenarios. The delivered cost to the plant gate, after adding
costs for fertilization and transportation, was between about $30 to $60 Mg −1 . The
model has been developed in MATLAB and also provides a user interface in
Microsoft Excel ® . The user interface could be used for data entry and running simu-
lations from a stand-alone executable fi le. This allows the program to be easily
accessible for extension work without the necessity of a MATLAB license.