WUR-LICT - WUR-Living Income Calculation Tool

Submitted by georgios on Thu, 10/15/2020 - 11:52
Program type
Living Income Calculation Tool
Available since

WUR-LICT application is a tool for living income benchmarking of rural households in less-developed countries. It is delivered in the form of a stand-alone Windows application.

The interface will lead the user step by step on how to collect the necessary data, run the WUR-LICT model, and receive the final results.

The user can navigate through the interface by using the different Tabs at the top of the screen.

The first tabs (from GENERAL INFORMATION up to EDUCATION) will help the user to collect all the necessary data.

In the COLLECT NUTRIENTS tab, the user can use the United States Department of Agriculture (USDA) food database via the provided USDA ID finder tool in order to collect all the food nutrient contents.

Finally, the user can run the Linear Programming algorithm to find the lowest cost nutritious diet. If a solution is found, the final RESULTS tab will contain the results in tables.

Scale of application
Regional; expressed per Adult Equivalent, averaged over the area of data collection.
Spatial resolution
Local/regional; determined by the area of data collection
Key outputs
  • Food costs information including a nutritious diet with the minimum cost.
  • Housing costs information.
  • Education (primary and lower secondary) costs information.
  • Healthcare costs information.
  • Total living income costs information.
Time horizon
Calculations for 1 specific year.
Time step of modeling
Static model for 1 year.
Required to run

A machine with Windows 10.

Double click for installing the executable file (WUR-LICT Setup 0.1.0.exe).

Required to develop

React (Javascript), Electron.

Database I/O
Text files

Living income benchmarking of rural households in low-income countries Food Security; https://doi.org/10.1007/s12571-020-01099-8

Ven, Gerrie W. J. van de, Anne de Valença, Wytze Marinus, Ilse de Jager, Katrien K. Descheemaeker, Willem Hekman, Beyene Teklu Mellisse, Frederick Baijukya, Mwantumu Omari, Ken E. Giller,
WUR, Plant Production Systems, Wageningen, The Netherlands