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\hypersetup{pdftitle={Matching Technical Options with Farm Clusters to Improve Agricultural Production and Soil Quality in Kakamega, Western Kenya},pdfauthor={Kelvin Mark Mtei, Frank Mussgnug, Mathias Becker},pdfsubject={Tropentag 2010: Abstract},pdfkeywords={Decision support tool, factors of production, logistic regression model, technology requirements, technology suitability, weeds suppression},pdfpagemode=None,colorlinks=true}
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\parbox[b]{13.4cm}{\centering \large{\textbf{Tropentag, September 14-16, 2010, Zurich}}\\[1ex] \Large{``World Food System  ---\\A Contribution from Europe''\\[2ex]}}
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\Large{\textbf{Matching Technical Options with Farm Clusters to Improve Agricultural Production and Soil Quality in Kakamega, Western Kenya\footnote{\textbf{Contact Address:} Kelvin Mark Mtei, University of Bonn, Institute of Crop Science and Resource Conservation - Plant Nutrition, Karlrobertkreiten str. 13, 53115~Bonn, Germany, \mbox{e-mail}: \email{s7kemtei@uni-bonn.de}}\\[0.8ex]}}
\normalsize{\textsc{Kelvin Mark Mtei, Frank Mussgnug, Mathias Becker}}
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\begin{itemize*}
\item[]{\small{\textit{University of Bonn, Institute of Crop Science and Resource Conservation (INRES) - Plant Nutrition, Germany}}}
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\index[author]{Mtei, Kelvin Mark}
\index[author]{Mussgnug, Frank}
\index[author]{Becker, Mathias}
\begin{center}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
Declining resource quality and limited resource availability have been the main contributing factors to poor agricultural production at farm level in Sub-Saharan Africa. Technologies  recommended to improve soil quality and productivity have been unable to mitigate the situation significantly because farm specific conditions are not considered in recommendations. Previous typology"=studies classified farms in Kakamega into six main clusters based on household socio"=ecological characteristics (clusters 2, 3 and 5 as subsistence"=oriented resource poor, and; 1, 4 and 6 as market"=oriented resource rich farmers). This study aimed at evaluating suitability of technologies to these clusters, specifically to i) assess technology requirement and benefits at farm level ii) match technology attributes with cluster characteristics iii) develop a decision support tool for recommending technology to specific clusters. Four sites were set in predominant soil types (Alfisol and Ultisol) and seven technical options (clean weeding, animal manure, seed priming, mineral fertiliser, zero"=tillage with mineral fertiliser, zero"=tillage with cover crop (Arachis pintoi) and mineral fertiliser, green manure (\textit{Mucuna} puriens) and a famers'-practice"=control) were evaluated during the short rains (August---December) 2008 and long rains (February---July) 2009. Data were collected to assess technology requirements based on factors of production (land, labour, capital and knowledge) and benefits (yield and weed suppression). Soil samples were taken to assess soil quality improvement.



Matching of technology attributes with socio"=ecological characteristics of farm"=clusters by suitability approaches (matrix"=rating) and statistical analysis of similarity (ANOSIM), indicated that clean weeding and seed priming were highly"=suitable ($>$\mbox{80\,\%}) to subsistence"=oriented resource poor clusters but unsuitable to cluster 4 (\mbox{33\,\%}, cluster had the lowest available labour); animal manure and green manure were moderately"=suitable (60--\mbox{80\,\%}) to all clusters but unsuitable to cluster 4 (\mbox{34\,\%}); mineral fertiliser and zero tillage with mineral fertiliser were moderately"=suitable (60--\mbox{80\,\%}) to all the clusters but cluster 4 (\mbox{20\,\%}); cover crop with mineral fertiliser moderately"=suited (60--\mbox{80\,\%}) all clusters.



Next step (advanced matching) will involve modelling by binomial logistic regression that relates technology and cluster variables with their effects to yield, soil quality improvement and weed control. A decision support tool for selecting technologies to specific cluster will be developed.



}

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\noindent \textbf{Keywords:} Decision support tool, factors of production, logistic regression model, technology requirements, technology suitability, weeds suppression
\index[key]{Decision support tool}
\index[key]{Factors of production}
\index[key]{Logistic regression model}
\index[key]{Technology requirements}
\index[key]{Technology suitability}
\index[key]{Weeds suppression}
\end{document}