Systems Informatics and Analysis - Engineering and Science of Biomass Feedstock Production and Provision - page 195

WIMOVAC (Windows Intuitive Model of Vegetation response to Atmosphere and
Climate Change) [ 21 ]. The importance of on-farm decision-making tools for biomass
feedstock production has been recently highlighted by the United States Department
of Energy [ 22 ].

8.3 Systems Informatics and Analysis in Biomass Feedstock

Production and Provision

There are multiple approaches to classify literature on the application of SIA for
BFPP systems. One approach is based on the methodologies used, such as data-
bases, simulation models, optimization models, decision support tools, and web-
based applications. The second approach is based on the temporal scope of the
applications, such as strategic (years), management (weeks to months), and opera-
tional (hours to days). Lowrance et al. [ 23 ] instead proposed a spatially hierarchical
approach including agronomic, microeconomic, ecologic, and macroeconomic lev-
els. One can also discuss SIA literature specifi c to each task of the BFPP value chain
represented in Fig. 1.2 . However, it is often diffi cult to clearly delineate many such
applications since they cut across multiple tasks.
In this chapter, we have used a classifi cation approach that is based on the one
proposed by Lowrance et al. [ 23 ] with modifi cations to account for the literature
related to BFPP. These classes are:

• Crop growth and management system : This includes crop growth modeling,

interaction of crops with soil and water, and the impact of management practices
on crop yield.

• On - farm production system : This includes machinery selection, fertilization and

irrigation management, and whole-farm management.

• Local production and provision system : This includes farm production as well as

transportation and logistics management and local biorefi nery system design,
management, and operation.

• Regional / national / global system : This includes macroeconomic models for pol-

icy analysis as well as resource management.

The proposed classifi cation involves spatial hierarchy where crop growth and
management are of relevance to a specifi c fi eld, while the regional, national, and
global issues are relevant at a much larger scale (Fig. 8.3 ). For each of these classes,
the important informatics, modeling, and analysis applications are discussed below.

8.3.1 Crop Growth and Management Systems

The research at the crop growth and management system level is often aimed at opti-
mizing the interactions between the crop genotype, environment, and crop manage-
ment [ 24 ]. Specifi c focus areas include estimating and maximizing the potential/