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Agronomía Colombiana

versión impresa ISSN 0120-9965

Resumen

MUNOZ B., Johanna; RODRIGUEZ C., Luis Felipe  y  CRIOLLO, Hernando. Technical-economic characterization of the lulo production system (Solanum quitoense Lam.) in the department of Nariño. Agron. colomb. [online]. 2014, vol.32, n.2, pp.276-282. ISSN 0120-9965.  https://doi.org/10.15446/agron.colomb.v32n2.40961.

Nariño is a significant producer of lulo in Colombia, with the producers of the region found in the northern part of the department. The principal problems for the producers are the low levels of productivity and profit, which have led to increasing abandonment of this crop, losses of manual labor, and a reduction in the standard of living. The general objective of the present study focused on the application of multivariate analysis in order to reveal the characteristics of the production system, such as the elements of decisions. The results of surveys, interviews, and direct observations of the production units were analyzed through principal component and grouping analyses, using the Ward distance criterion. The studied lots were between 1,788 m a.s.l. in the La Florida District of the municipality of Colón and 2,480 m a.s.l. in the Botanilla District of the municipality of Cartago. Yields were low, although the majority of the producers in Colón obtained yields over 7.0 kg/ plant with a shared production system. The plantlets used for the establishment of the crops are produced by the farmers, few in number, and rarely bought. Chemical fertilization and phytosanitation predominate, although, in San Lorenzo, only organic fertilizers are applied during sowing; microelements are not applied in any of the municipalities. The harvest is commercialized by agrobusinesses with prices fixed by the venders. The analysis of the economic variables showed that those producers with a high number of plants were more efficient and obtained a profit of 488.4%, higher than the general average which was 202.5%.

Palabras clave : fruits; descriptive analysis; principal component analysis; cluster analysis.

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