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United States Department of Agriculture

Agricultural Research Service

Staub: Accomplishments
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1 - Germplasm Enhancement
2 - The Development of Genetic Stocks, Genetic Analyses, and Map Construction
3 - Cucumis Taxonomy, Evolution, and Interspecific Hybridization
4 - Molecular Marker Utility for PVP and Diversity Analysis
5 - Trait Evaluation and Collection of Exotic Germplasm
6 - The Physiological and Anatomical Characterization of a Fruit Anomaly
7 - Feasibility Studies for Cucumber Production
8 - The Development of Molecular Markers
9 - Identification and Characterization of a Postharvest Disorder
10 - Characterization of Responses to Stress Environments
11 - Development of Computer Programs for Research and Teaching
Feasibility Studies for Cucumber Production
Feasibility Studies for Cucumber Production

USDA Vegetable Crops Research Unit
Cucumber and Melon Genetics

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Demonstrated Accomplishments of the Laboratory

7. Accomplishment: Feasibility Studies for Cucumber Production

Single-source production of agricultural products presents economic risk to producers and processors. About 70% of the winter production (November to April) of pickling cucumber for U.S. processors is located in Mexico. The laboratory has conducted a feasibility study for the production of processing cucumber in Hispaniola (#127), and determined the risk to U.S. processors of partitioning production between Mexico and Hispaniola (#128). Role: The senior author was a graduate student under the Dr. Staub's supervision where he conceived the research, attracted funding, participated in the development of strategic alliances, determined with the student the most relevant mode of computer analysis, and assisted in manuscript preparation. Impact: The U.S. cucumber processing industry experiences slow but steady growth (about 2%) where processed product value is about 750 million dollars. Although traditionally processors have used Mexico as a sole source during winter production (about 100 million dollars for unprocessed cucumber), this investment strategy has become increasingly difficult to justify given present fluctuating market conditions and narrow industry profit margins. Research performed in this area supports NP #301 by furnishing production information, databases, and procedures to ensure competitiveness in American agriculture. The laboratory, in cooperation with U.S. processing industry representatives, chose Hispaniola (The Dominican Republic and Haiti) as a test site for off-shore cucumber production because of its economic, political and agricultural infrastructure, and its proximity to the U.S. The production analysis determined the most appropriate variety through small plot trials, and the components of cost of production and export using larger experimental plots (1 to 5 acres). These data were then used in a Monte Carlo-based risk analysis to determine possible investment scenarios for U.S. processors. The underpinnings of this assessment of production and risk involved the dynamic creation of strategic alliances between U.S. processors, Hispanola growers, exporters, and university extension based in the Dominican Republic. This alliance was sustained for 8 years (1990 to 1997) and resulting contracts made for transport of raw product to U.S. processors. This was the first comprehensive study of cucumber production and risk in the Caribbean and Central America. It resulted in production and export figures that were used for comparative analysis of Hispaniola and potential Asian production sites (e.g., India and Sri Lanka). Analysis indicated that India, but not Sri Lanka was a possible candidate for cucumber production for U.S. processors. Dr. Staub, as a consultant with U.S. processors and in cooperation with the then largest cucumber processing company in India (VST, Inc.), used the data from this analysis to determine the risk of investment strategies for U.S. processors in India (1995-1999; see C.3.b.). The Hispaniola project created the first computer-based model for use in risk analysis employing economically valid input cost equation for use in Monte-Carlo analysis for decision-making. This model has been used by processors for the evaluation of risk using other, more company-oriented, investment and diversification scenarios. See publications #127; #128.


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Last Modified: 12/11/2006
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