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Database development for alfalfa (Medicago sativa L.) characterization in an artificial vision system

Martínez-Corral1 L, E Martínez-Rubín2, F Flores-García1, GC Castellanos2, AR Juárez2, MJD López3
Instituto Tecnológico de la Laguna, Dirección: Blvd. Revolución y Clzda. Cuauhtémoc s/n Torreón, Coahuila, México.
Instituto Tecnológico de Torreón. Carretera Torreón – San Pedro Km. 7.5, Ejido Anna. Torreón, Coah. México.
FAZ-UJED, Facultad de Agricultura y Zootecnia de la Universidad Juárez del Estado de Durango. Carretera Gómez Palacio-Tlahualilo, Km. 35 Ej. Venecia, México.
* Corresponding Author:Address Correspondence to: L. Martínez-Corral, e-mail: ; Teléfono: 52(871)7250949.

Phyton-International Journal of Experimental Botany 2009, 78(all), 43-47. https://doi.org/10.32604/phyton.2009.78.043

Abstract

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.

Keywords

artificial intelligence, vision systems, plant nutrition.

Cite This Article

, M., Flores-García, F., Castellanos, G., Juárez, A., López, M. (2009). Database development for alfalfa (Medicago sativa L.) characterization in an artificial vision system. Phyton-International Journal of Experimental Botany, 78(all), 43–47.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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