Use of correspondence analysis in agroecosystem health and sustainability assessment

Describing agroecosystems and assessing their sustainability and health has become of great interest to researchers, Development agents and communities. Such assessments are frequently carried out using a group of carefully chosen attributes, known as indicators. This was the approach adopted in a p...

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Autores principales: Gitau, T., McDermott, John J., Waltner-Toews, D., McDermott, B.
Formato: Conference Paper
Lenguaje:Inglés
Publicado: International Society for Veterinary Epidemiology and Economics 2000
Materias:
Acceso en línea:https://hdl.handle.net/10568/51289
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author Gitau, T.
McDermott, John J.
Waltner-Toews, D.
McDermott, B.
author_browse Gitau, T.
McDermott, B.
McDermott, John J.
Waltner-Toews, D.
author_facet Gitau, T.
McDermott, John J.
Waltner-Toews, D.
McDermott, B.
author_sort Gitau, T.
collection Repository of Agricultural Research Outputs (CGSpace)
description Describing agroecosystems and assessing their sustainability and health has become of great interest to researchers, Development agents and communities. Such assessments are frequently carried out using a group of carefully chosen attributes, known as indicators. This was the approach adopted in a project whose objective was an integrated assessment of a tropical-highlands agroecosystem. Initially, information on a large numbers of variables was collected. However, it was felt that many of the variables initially measured were unlikely to provide important information and required great effort to collect. Thus, methods and approaches to develop useful subsets of indicators were investigated. In this paper we explore the use of multiple correspondence analysis (MCA) in two contexts: (1) as a basis for system description and analysis and (2) as a tool to choose indicator groupings that are relatively parsimonious and informative.
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spelling CGSpace512892023-02-15T09:34:34Z Use of correspondence analysis in agroecosystem health and sustainability assessment Gitau, T. McDermott, John J. Waltner-Toews, D. McDermott, B. epidemiology methods agriculture ecosystem public health small farms Describing agroecosystems and assessing their sustainability and health has become of great interest to researchers, Development agents and communities. Such assessments are frequently carried out using a group of carefully chosen attributes, known as indicators. This was the approach adopted in a project whose objective was an integrated assessment of a tropical-highlands agroecosystem. Initially, information on a large numbers of variables was collected. However, it was felt that many of the variables initially measured were unlikely to provide important information and required great effort to collect. Thus, methods and approaches to develop useful subsets of indicators were investigated. In this paper we explore the use of multiple correspondence analysis (MCA) in two contexts: (1) as a basis for system description and analysis and (2) as a tool to choose indicator groupings that are relatively parsimonious and informative. 2000 2014-10-31T06:22:22Z 2014-10-31T06:22:22Z Conference Paper https://hdl.handle.net/10568/51289 en Limited Access International Society for Veterinary Epidemiology and Economics
spellingShingle epidemiology
methods
agriculture
ecosystem
public health
small farms
Gitau, T.
McDermott, John J.
Waltner-Toews, D.
McDermott, B.
Use of correspondence analysis in agroecosystem health and sustainability assessment
title Use of correspondence analysis in agroecosystem health and sustainability assessment
title_full Use of correspondence analysis in agroecosystem health and sustainability assessment
title_fullStr Use of correspondence analysis in agroecosystem health and sustainability assessment
title_full_unstemmed Use of correspondence analysis in agroecosystem health and sustainability assessment
title_short Use of correspondence analysis in agroecosystem health and sustainability assessment
title_sort use of correspondence analysis in agroecosystem health and sustainability assessment
topic epidemiology
methods
agriculture
ecosystem
public health
small farms
url https://hdl.handle.net/10568/51289
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