Haitian agricultural potential is largely unexploited. The country needs a new approach to its agricultural development and development cooperation needs new practices to drive more appropriate interventions. Our research integrates advanced statistical methodologies and SWOT analysis at a pilot scale to identify the most relevant features for farm economic sustainability in the Torbeck Plain. Multidimensional data were collected in 49 farms and Principal Component Analysis (PCA) was used to discover the main components affecting the system’s variability. The most meaningful variables are then used for Hierarchical Cluster Analysis (HCA) to provide farms’ classification. Results were used to inform a statistically driven SWOT analysis. PCA reveals the presence of three main components. First, it seems that crop choice makes the difference because of the sale price’s great importance. The irrigation system’s availability affects neither yield nor income, whilst mechanization is mostly important for farms whose farmer’s first crop choice is maize. Moreover, mechanization is a generally worthwhile investment for farms whose fields’ area is at least about 1.2-1.5 ha. Overall, the statistical analysis provides reasonable farms’ classification and interesting insights about the Torbeck agricultural system. These were valuable for informing a SWOT analysis suggesting data-driven strategies for improving the agricultural system in Torbeck, which match the existing international guidelines and provide local priorities for intervention. In the short term they include i) informing crop choice ii) providing opportunities and infrastructure for local marketing. Long-term goals include developing extension services based on subsistence farmers' needs, advocating for data-driven national and international strategies for intervention, deepening the knowledge about relevant threats such as the diffused use of dangerous pesticides, or the unadvised water management.
An investigation about the agricultural system in Torbeck plain, Haiti : A statistically driven SWOT analysis / G. Russo, J.W. Bernadin, A. Spada, J. Aristil, G. Assante, P. De Marinis. - In: JOURNAL OF AGRICULTURE AND ENVIRONMENT FOR INTERNATIONAL DEVELOPMENT. - ISSN 2240-2802. - 115:1(2021), pp. 97-124. [10.12895/jaeid.20211.1465]
An investigation about the agricultural system in Torbeck plain, Haiti : A statistically driven SWOT analysis
G. RussoPrimo
Software
;A. SpadaConceptualization
;J. Aristil;G. Assante;P. De Marinis
2021
Abstract
Haitian agricultural potential is largely unexploited. The country needs a new approach to its agricultural development and development cooperation needs new practices to drive more appropriate interventions. Our research integrates advanced statistical methodologies and SWOT analysis at a pilot scale to identify the most relevant features for farm economic sustainability in the Torbeck Plain. Multidimensional data were collected in 49 farms and Principal Component Analysis (PCA) was used to discover the main components affecting the system’s variability. The most meaningful variables are then used for Hierarchical Cluster Analysis (HCA) to provide farms’ classification. Results were used to inform a statistically driven SWOT analysis. PCA reveals the presence of three main components. First, it seems that crop choice makes the difference because of the sale price’s great importance. The irrigation system’s availability affects neither yield nor income, whilst mechanization is mostly important for farms whose farmer’s first crop choice is maize. Moreover, mechanization is a generally worthwhile investment for farms whose fields’ area is at least about 1.2-1.5 ha. Overall, the statistical analysis provides reasonable farms’ classification and interesting insights about the Torbeck agricultural system. These were valuable for informing a SWOT analysis suggesting data-driven strategies for improving the agricultural system in Torbeck, which match the existing international guidelines and provide local priorities for intervention. In the short term they include i) informing crop choice ii) providing opportunities and infrastructure for local marketing. Long-term goals include developing extension services based on subsistence farmers' needs, advocating for data-driven national and international strategies for intervention, deepening the knowledge about relevant threats such as the diffused use of dangerous pesticides, or the unadvised water management.File | Dimensione | Formato | |
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