This paper generates an extrapolation suitability index (ESI) to guide scaling-out of improved maize varieties and inorganic fertilizers. The best-bet technology packages were selected based on yield gap data from trial sites in Tanzania. A modified extrapolation detection algorithm was used to generate maps on two types of dissimilarities between environmental conditions at the reference sites and the outlying projection domain. The two dissimilarity maps were intersected to generate ESI. Accounting for correlation structure among covariates improved estimate of risk of extrapolating technologies. The covariate that highly limited the suitability of specific technology package in each pixel was identified. The impact based spatial targeting index (IBSTI) identified zones that should be prioritized to maximize the potential impacts of scaling-out technology packages. The proposed indices will guide extension agencies in targeting technology packages to suitable environments with high potential impact to increase probability of adoption and reduce risk of failure.
This work is licensed under CC-BY 4.0
This work is licensed under CC-BY 4.0
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TI - Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages
AU - Muthoni, F.K.
AU - Baijukya, F.
AU - Bekunda, M.
AU - Sseguya, H.
AU - Kimaro, A.A.
AU - Alabi, T.
AU - Mruma, S.
AU - Hoeschle-Zeledon, I.
AB - This paper generates an extrapolation suitability index (ESI) to guide scaling-out of improved maize varieties and inorganic fertilizers. The best-bet technology packages were selected based on yield gap data from trial sites in Tanzania. A modified extrapolation detection algorithm was used to generate maps on two types of dissimilarities between environmental conditions at the reference sites and the outlying projection domain. The two dissimilarity maps were intersected to generate ESI. Accounting for correlation structure among covariates improved estimate of risk of extrapolating technologies. The covariate that highly limited the suitability of specific technology package in each pixel was identified. The impact based spatial targeting index (IBSTI) identified zones that should be prioritized to maximize the potential impacts of scaling-out technology packages. The proposed indices will guide extension agencies in targeting technology packages to suitable environments with high potential impact to increase probability of adoption and reduce risk of failure.
PY - 2019
UR - https://www.cifor-icraf.org/knowledge/publication/15189/
DO - https://doi.org/10.1080/10106049.2017.1404144
KW - agronomy, food security, population, probability, technology
ER -Endnote (.ciw)
%T Accounting for correlation among environmental covariates improves delineation of extrapolation suitability index for agronomic technological packages
%A Muthoni, F.K.
%A Baijukya, F.
%A Bekunda, M.
%A Sseguya, H.
%A Kimaro, A.A.
%A Alabi, T.
%A Mruma, S.
%A Hoeschle-Zeledon, I.
%D 2019
%U https://www.cifor-icraf.org/knowledge/publication/15189/
%R https://doi.org/10.1080/10106049.2017.1404144
%X This paper generates an extrapolation suitability index (ESI) to guide scaling-out of improved maize varieties and inorganic fertilizers. The best-bet technology packages were selected based on yield gap data from trial sites in Tanzania. A modified extrapolation detection algorithm was used to generate maps on two types of dissimilarities between environmental conditions at the reference sites and the outlying projection domain. The two dissimilarity maps were intersected to generate ESI. Accounting for correlation structure among covariates improved estimate of risk of extrapolating technologies. The covariate that highly limited the suitability of specific technology package in each pixel was identified. The impact based spatial targeting index (IBSTI) identified zones that should be prioritized to maximize the potential impacts of scaling-out technology packages. The proposed indices will guide extension agencies in targeting technology packages to suitable environments with high potential impact to increase probability of adoption and reduce risk of failure.
%K agronomy
%K food security
%K population
%K probability
%K technology
Année de publication
2019
ISSN
1010-6049
Auteurs
Muthoni, F.K.; Baijukya, F.; Bekunda, M.; Sseguya, H.; Kimaro, A.A.; Alabi, T.; Mruma, S.; Hoeschle-Zeledon, I.
Langue
English
Mots clés
agronomy, food security, population, probability, technology
Source
Geocarto International. 34(4): 368-390
Géographique
Tanzania
