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Spatial Targeting for Scaling-Out Maize Technologies

Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages
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Procedure for delineating extrapolation suitability index (ESI) and impact based spatial targeting index (IBSTI) for estimating risk of extrapolating maize technologies.

Our spatial colleagues at IITA, led by Francis Kamau Muthoni, recently published a study on the spatial targeting of maize technologies in Tanzania, applying a novel spatial correlation method.

Muthoni, Francis Kamau, Frederick Baijukya, Mateete Bekunda, Haroon Sseguya, Anthony Kimaro, Tunrayo Alabi, Silvanus Mruma, and Irmgard Hoeschle-Zeledon. “Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages.” Geocarto International (2017): 1-23. https://doi.org/10.1080/10106049.2017.1404144 (Open Access)

The team generated a new spatial data layer of Impact-Based Spatial Targeting Index (IBSTI) based on multiple biophysical and socioeconomic indicators and their covariates with a rich set of variety and fertilizer trial data collected from multiple sites across Tanzania.

This method helped the team to identify factors limiting the performance of maize technologies in each pixel, revealing complex spatial heterogeneity of agroecological and socioeconomic conditions even within the broadly generalized zone of Southern Highlands. The overall approach is expected to guide extension agencies in targeting technology packages best suitable for local environments with high potential impact to increase the probability of adoption and reduce risk of failure at a granular level.

The full text of the paper is available from the website of journal, Geocarto International.

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