Open Access

ARTICLE

Identification of axillary buds of potato seedlings based on a vision system with fuzzy logic

by Martínez Corral L¹, E Martínez-Rubin², F F lores-García³, M Vázquez-Rueda³, J Frías-Ramírez², MA Segura-Castruita²

1 Departamento de Investigación, Instituto Tecnológico Superior de Lerdo. Av. Tecnológico No. 1555 sur, Periférico Gómez-Lerdo km. 14.5, Cd. Lerdo, Durango, México.
2 Departamento de Estudios de Posgrado e Investigación del Instituto Tecnológico de Torreón. Carretera Torreón-San Pedro km. 7.5, Ejido Anna. Torreón, Coahuila, México.
3 Instituto Tecnológico de la Laguna. Blvd. Revolución y Clzda. Cuauhtémoc s/n Torreón, Coahuila, México.

* Corresponding Author:Address Correspondence to: Dra. Luime Martínez-Corral. Tel. 52(871)7250949. e-mail:

Phyton-International Journal of Experimental Botany 2011, 80(all), 79-84. https://doi.org/10.32604/phyton.2011.80.079

Abstract

Potato (Solanum tuberosum L.) is a crop whose production yield at national level is very low compared with that in the most productive countries. This is because it is a partially automated crop with deficient and inadequate agronomic practices, low technification levels and great quantity of work wages required per hectare of cultivation. The necessity to generate technical and modern procedures that increase crop production, quality and yield has fostered development of projects leading to obtain seedlings free of pathogens with material of high genetic, physiological and sanitary quality. Utilization of a vision system for the computerized visual recognition of the cut region in the plant that favors its propagation implies the analysis and processing of certain statistical describers of an object obtained from a digital image. The objective of this work was to develop a vision system focused on the extraction and treatment of image information for the identification of plant axillary buds in potato seedlings which presents reasoning through a group of rules based on equally designed diffuse logic and implemented in the proposed program. The results proved 96% effectiveness in the cases of identification of plant axillary buds; this was possible with a minimum human intervention through a visual interface of the program, which combines the digital image processing with specialized diffuse control algorithms to this end.

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Keywords

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