Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

Abstract If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm ‘unique’ solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for ‘truly’ typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted.

[1]  C. R. W. Spedding,et al.  An Introduction to Agricultural Systems , 1988, Springer Netherlands.

[2]  Second Edition,et al.  Statistical Package for the Social Sciences , 1970 .

[3]  Derek Byerlee,et al.  Planning technologies appropriate to farmers: Concepts and procedures , 1988 .

[4]  J. Berdegué,et al.  Tipificación de sistemas de producción agrícola , 1990 .

[5]  Jerzy Kostrowicki,et al.  Agricultural typology concept and method , 1977 .

[6]  John Van Ryzin,et al.  Classification and clustering : proceedings of an advanced seminar conducted by the Mathematics Research Center, the University of Wisconsin at Madison, May 3-5, 1976 , 1977 .

[7]  Rolf H. Gebauer,et al.  Socio-economic classification of farm households —conceptual, methodical and empirical considerations , 1987 .

[8]  Howard B. Lee,et al.  A first course in factor analysis , 1973 .

[9]  Robert F. Ling,et al.  Classification and Clustering. , 1979 .

[10]  R. T. Hardiman,et al.  Use of cluster analysis for identification and classification of farming systems in Qingyang County, Central North China , 1990 .

[11]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[12]  R. Sokal.  Clustering and Classification: Background and Current Directions , 1977 .

[13]  Avi Perevolotsky.  Goat production systems in Piura, Peru: A multidisciplinary analysis☆ , 1990 .

[14]  G. W. Milligan,et al.  An examination of procedures for determining the number of clusters in a data set , 1985 .

[15]  R. Mojena,et al.  Hierarchical Grouping Methods and Stopping Rules: An Evaluation , 1977, Comput. J..

[16]  M. Aldenderfer.  Cluster Analysis , 1984 .