Resumen

MARTINEZ-CORRAL, L et al. Database development for alfalfa (Medicago sativa L.) characterization in an artificial vision system. Phyton (B. Aires) [online]. 2009, vol.78, n.1, pp.43-47. ISSN 1851-5657.

The increasing demand of alfalfa crop production in the Lagunera Region has caused the search of new alternatives to the conventional methods of nutritional and hydric evaluation of alfalfa, where costs and time are optimized. The use of a machine vision system for computerized visual recognition of the crop hydric and/or nutritional stress implies the analysis and processing of certain characteristics, such as color, shape and object dimensions from a digital image. Due to the fact that identification parameters are closely related, it is necessary to compile information from specialists, foliar analysis, mathematical morphology and alfalfa crop deficiency photographs. The goal of this work was to develop an information system that works as a database tool for nutritional (nitrogen, phosphorous, potassium) deficiency and water stress characterizations of alfalfa crops, integrating all parameters mentioned before. The database utilizes images captured by a CCD camera, and results of extraction techniques and recognition of configured patterns in a machine vision system previously developed. Integration of the artificial vision module and human expert knowledge module are presented in a single information base, programmed in Visual Basic language.

Palabras clave : Artificial intelligence; Vision systems; Plant nutrition.

        · resumen en Español     · texto en Español     · Español ( pdf )