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Systems projects take place over many years, pass through many stages of development and progress, and draw together team members whose level of investment can vary significantly. Given all of this, issues with accountability are not unusual. To maintain momentum and follow-through, hold regular meetings to assess progress and set target dates for achieving objectives. […]

From an institutional perspective, the financial management of multidisciplinary systems projects is essentially the same as for other externally funded projects. Normal accounting and budgeting procedures can easily accommodate systems projects, even those with a large number of subcontracts. However, the complexity of systems projects and the need for group decision-making create distinct issues for […]

The transition from a potential project to one that is successfully implemented requires diligent application of participatory principles. During this start-up phase, the team will revisit the proposal plan and revise it as needed to move into execution. Once funding has been obtained, the team is committed to a collaborative endeavor that will be part […]

An indicator is an observed or measured variable that reflects the state of a system (Mayer, 2008). In agricultural systems, crop health is monitored using indicators such as plant architecture and leaf color and shape. Farmers use quantitative soil tests, soil color and surface texture, amount of runoff, and the “feel” of tillage (e.g., how […]

Life Cycle Assessment Life cycle assessment (LCA) was developed in the 1960s within the field of industrial ecology, as a “cradle-to-grave” approach for assessing the impacts of industrial systems and manufacturing processes on environmental and human health (Horne et al., 2009). An LCA begins with an inventory of the raw materials required to produce a […]

Structural equation modeling (SEM) is an extension of the general linear model (GLM) and can be a more powerful alternative to multiple regression, path analysis, factor analysis, time-series analysis and analysis of covariance (Garson, 2010). An SEM model is essentially a composite hypothesis made up of a series of cause-and-effect relationships between variables using statistical […]

Systems experiments, by the nature of their design and goals, have multiple confounding factors that cannot be easily separated (Teasdale and Cavigelli, 2010). This means that a mixture of statistical approaches is often required. Univariate and multivariate statistics are the most typical mathematical methods of systems analysis. Which approach to use will depend upon the […]

Start planning for the financial support of systems projects early. Most simulated agricultural systems projects that have been in place for 10 or more years are still in operation because the researchers planned ahead to receive institutional support (Table 3.1). Even where institutional support is provided, extramural funding is often required to carry out more […]

In general, systems-based studies and factorial experiments confront similar issues when determining the number of replications and plot configurations needed for adequate statistical analyses. A few issues, however, are specific to agricultural systems research and can be addressed by the experimental design and sampling strategies. To start, what constitutes a “control” for a systems experiment? […]