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\hypersetup{pdftitle={Management Optimisation in Cumin Fields by Determining the Cause and Effects of Yield Reduction: A Case Study in Iran with C\&R Tree Method as One of Data Mining Classification Procedures},pdfauthor={Mina Farajzadeh},pdfsubject={Tropentag 2010: Abstract},pdfkeywords={C&R method, cumin yield, data mining, system optimisation},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{Management Optimisation in Cumin Fields by Determining the Cause and Effects of Yield Reduction: A Case Study in Iran with C\&R Tree Method as One of Data Mining Classification Procedures\footnote{\textbf{Contact Address:} Mina Farajzadeh, Gorgan University of Agricultural Science and Natural Resources, Shahid Beheshti St., Gorgan, Iran, \mbox{e-mail}: \email{mina2002f@yahoo.com}}\\[0.8ex]}}
\normalsize{\textsc{Mina Farajzadeh}}
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\begin{itemize*}
\item[]{\small{\textit{Gorgan University of Agricultural Science and Natural Resources, Iran}}}
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\index[author]{Farajzadeh, Mina}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
Data mining is one of these tools that can use in agricultural  researches to clarify the cause and effects of variations in results and observations. C\&R Tree method uses recursive partitioning to split the records into segments with similar output field values. The C\&R method as a classification and regression(C\&R) tree, is a tree"=based classification and prediction method. In this method collected data base split to two subgroups, each of which is subsequently split in two more subgroups, and so on, until one of the stopping criteria is triggered. In this regard a case study was done on cumin fields of Khorasan provinces of Iran, to determine the importance of involved causes which affect actual yield of this crop. Data were collected in around 60 fields. The results showed that inappropriate sowing date and infection to fungi diseases were the most important factors, which affected negatively the cumin yield. Sowing the crop in the middle of common sowing dates and avoiding excess moisture in the soil also were determined as the best"=proposed management options to alleviate the negative effects of these factors on cumin yield. Therefore, to sustain of this valuable under"=utilised crop which is favourable in strict rotations of this stressful regions, designing the low"=irrigation but on time systems to alleviate the Fusarium spp injuries and encouraging the farmers to select December as the best time to sowing the cumin were introduced as optimised managements. These results indicated that classification methods can use as a powerful tool to detect causes of an effects of yield reductions in agroecosystems. This procedure can be considered as a valuable method to detect the causes and present approaches to resolve the problems in fields. Undoubtedly, Finding the causes of yield reduction in agroecosystems is the first step to optimise them and moving to reduce risks and provide food security in general.}

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\noindent \textbf{Keywords:} C\&R method, cumin yield, data mining, system optimisation
\index[key]{C\&R method}
\index[key]{Cumin yield}
\index[key]{Data mining}
\index[key]{System optimisation}
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