Using Cluster Analysis to Classify Farms for Conventional/Alternative Systems Research

Bernhardt, Kevin; Allen, John C.; Helmers, Glenn A.

doi:10.2307/1349593

Cited by 19 publications

(22 citation statements)

References 17 publications

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“…Cluster analysis was used to identify different production systems (Bernhardt et al, 1996). First, relevant production practices variables (Table 2) were submitted to hierarchical cluster analysis to select the number of different clusters from the distances coefficients in the scree diagram (elbow rule).…”

Section: Methodsmentioning

confidence: 99%

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Analysis of Pineapple Production Systems in Benin

Hotegni¹,

Lommen²,

Vorst

et al. 2012

Acta Hortic.

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In Benin, pineapple is an important fruit crop, mainly grown in the Atlantic department. The overall quality of the two cultivars grown, 'Sugarloaf' and 'Smooth Cayenne', does not meet the requirements for some outlets and the heterogeneity in fruit quality within and between lots is high. This paper (1) describes and analyses the pineapple production systems of 'Sugarloaf' and 'Smooth Cayenne' and (2) identifies the main constraints reducing the quality of pineapple produced. First, semi-structured interviews were carried out with key informants including producers' organisations, input supplier and extension agents. Next, an in-depth questionnaire was carried out with 100 producers in the Atlantic department. Additionally, pedological and meteorological information was collected. Results indicated that pedo-climatic conditions in the Atlantic department were favourable for pineapple cultivation. The production practices were very diverse for both cultivars, especially regarding planting material used (slips, hapas and suckers), planting density, flowering induction time, and fertiliser application. The production systems of the two cultivars differed in type of planting material used, planting density, use of K 2 SO 4 , number of fertiliser applications and ethephon application. In 'Smooth Cayenne' cultivation, only hapas and suckers were used, planting density was lower, the number of fertiliser applications was higher, K 2 SO 4 was generally used and maturity was more often synchronised than in 'Sugarloaf' cultivation. The main constraints were availability of appropriate planting material, heterogeneity in weight, age and leaf number of planting material, and availability and high costs of fertilisers. Tackling all these constraints would help producers improve the quality of produced pineapple in Benin.

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Section: Methodsmentioning

confidence: 99%

“…Ward's method was used to calculate the distances. Next, the K-means algorithm (Hartigan, 1985) was used to partition the producers' production systems into the pre-determined cluster number, with the Euclidean distance being used as similarity measure (Bernhardt et al, 1996). The final cluster centres per variable, i.e.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Pineapple Production Systems in Benin

Hotegni¹,

Lommen²,

Vorst

et al. 2012

Acta Hortic.

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show abstract

“…We used a K-means algorithm, a non-parametric method, that uses a Euclidean distance similarity measure and iterative partitioning to differentiate observational units into sub-groups or clusters. K-means clustering requires that the number of clusters be established a priori (Bernhardt et al 1996). Procedures used to find a local partition optimum, based on the a priori selection of the optimum number of partitions, are heuristic and can be described mathematically as follows: Minimize: (Bernhardt et al 1996).…”

Section: Selection Of the Clustering Algorithmmentioning

confidence: 99%

“…Procedures used to find a local partition optimum, based on the a priori selection of the optimum number of partitions, are heuristic and can be described mathematically as follows: Minimize: (Bernhardt et al 1996). In other words, this index is the percent of total variation in all variables not accounted for by clustering (Bernhardt et al 1996).…”

Section: Selection Of the Clustering Algorithmmentioning

confidence: 99%

Classifying federal public land grazing permittees

Gentner¹,

Tanaka²

2002

REM

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This study identifies the characteristics and attitudes of public land ranchers. Data from a random survey of 2,000 U.S. Forest Service and Bureau of Land Management grazing permittees (53.5% response rate) were cluster analyzed and 8 distinct groups of ranchers were identified. Each cluster differed with respect to why they were in ranching and how they would respond to public land policy changes related to grazing fees, grazing reductions, and changes in grazing season. Profit motivation for being in ranching was found to be a relatively low objective for all 8 types of ranchers. Washington to 77% in Nevada. The BLM and the USFS manage these lands to provide timber, grazing, recreation and mineral production, among other goods and services.Approximately 85% of federal land is grazed by domestic livestock (CAST 1996). The 2 management agencies administer 29,925 grazing permits across the west. These permits cover approximately 21.6 million federal animal unit months (AUMs) of grazing (CAST 1996). Grazing permit holders account for over half of the commercial beef cattle in these 11 western states (CAST 1996). Levels of yearlong dependence on public forage vary across the West: some ranches utilize federal lands for aThe authors would like to thank the USDA Fund for Rural America for funding this research through the grant "Western Regional Evaluation of Social and Economic Impacts of Public Land Policy." We would also like to thank members of Western Regional Research Project 192, "Rural Communities and Public Lands in the West: Impacts and Alternatives" for reviewing survey drafts and providing boundless support. We would especially like to thank the public land ranchers who took the time to fill out and return the survey form.Oregon impacto que tiepen los cambios en las politicas del manejo de terrenos comunales federales relacionados con las cuotas de pastoreo, la reduccon de las areas de apacentamiento y los cambios en las estaciones de pastoreo sobre la rentabilidad financiera global de la explotaciones. Los resultados indicaron que la ganancia monetaria no es el objetivo principal de los productores que explotan terrenos comunales federales. large part of their seasonal grazing capacity and some ranches, in areas where yearlong grazing is possible, depend on federal lands for most, if not all, AUMs of grazing capacity.In recent times, the use of public lands for non-consumptive uses, such as recreation and preservation, has increased dramatically. In the 1980s, visitor days on USFS lands increased by approximately 50% (CAST 1996). Also, some individuals that don't actively use public land have become advocates of preservation of these lands for environmental reasons. These 2 new and growing groups are typically from urban areas and are much more active and vocal than urbanites from the past regarding rural land use matters. Generally, these new activists feel nonconsumptive resource uses, such as recreation and preservation, should be given higher weight than consumptive uses such as grazing, timb...

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“…In these studies, farm management systems were distinguished primarily on the basis of social, economic and land use variables. Most recently, cluster analysis has been used to classify farms in Nebraska into conventional and alternative management systems using binary data (Bernhardt et al 1996).…”

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confidence: 99%

Multivariate classification of farming systems for use in integrated pest management studies

Leeson¹,

Sheard²,

Thomas³

1999

Can. J. Plant Sci.

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. 1999. Multivariate classification of farming systems for use in integrated pest management studies. Can. J. Plant Sci. 79: 647-654. On-farm studies provide a realistic setting to examine the impact of interactions of management practices on weed communities within various farming systems. Clustering farm units into groups that use similar management practices enables the replication of farm management systems within on-farm studies. The goal of this study is to objectively classify farm units into management systems on the basis of quantitative variables describing aspects of cropping history and chemical input levels using multivariate techniques. Twenty-eight Saskatchewan farmers provided details of their management practices from 1990 to 1997 through a series of questionnaires. Twelve variables derived from the questionnaires were used to describe cropping history, pesticide, tillage and fertilizer use on each farm unit. These variables were used to cluster farm units using minimum variance classification and NMS ordination. Both techniques identified seven farm management systems. The greatest differences were observed between organic and non-organic systems. Farm management systems that used annual fallow and continuous annual cropping histories were most similar. The consistent results obtained by use of the two unrelated methodologies indicate the utility of this approach for the classification of farm management systems.

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Using Cluster Analysis to Classify Farms for Conventional/Alternative Systems Research

Cited by 19 publications

References 17 publications

Analysis of Pineapple Production Systems in Benin

Analysis of Pineapple Production Systems in Benin

Classifying federal public land grazing permittees

Multivariate classification of farming systems for use in integrated pest management studies

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