Implementation of image processing for the evaluation of tar spot (Phyllachora maydis) in corn (Zea mays)

Authors

DOI:

https://doi.org/10.28940/terra.v40i0.1066

Keywords:

doses, leaf, resistant, silicion, susceptible

Abstract

The disease known as tar spot (Phyllachora maydis) af fects corn (Zea mays). It causes lesions on the leaves that, when progressing, can cause the death of the plant. There are dif ferent methods to assess the progress of a disease in plants. Visual assessment scales are generally used; however, their use is quite subjective. Image processing has been used in recent times as an alternative for the evaluation of plant diseases. This alternative avoids bias and error during evaluations. The objective of this experiment was to use the Leaf Doctor cell phone application as an alternative to the evaluation of the disease caused by P. maydis. For the experiment, a completely randomized block design was used. Three varieties of corn were planted and the level of tolerance to tar spot was evaluated when treated with dif ferent doses of silicon. The most resistant variety to the disease was INIAP-551. The dif ferent doses of silicon do not reduce the disease; however, it was possible to determine an increase in the production of corn in doses of silicon of 252 kg ha-1. The results indicate that the program can be considered as an ef f icient alternative to evaluate the development of the disease known as tar spot due to the high correlation with the visual assessment scale (R2: 0.77-0.94).

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Author Biographies

Rómulo Enrique Vinces-Tachong, Universidad Tecnica Estatal de Quevedo

I am a student of the Agronomy career. This project contributed to the preparation of this scientific publication.

Mayra Carolina Vélez-Ruiz, Universidad Tecnica Estatal de Quevedo

During my experience as a graduate student, I have acquired knowledge about the evaluation of damage caused by insects in different types of plants. Emphasizing my doctoral studies during which I worked with corn evaluating damage caused by Sitophilus zeamais. Additionally, I can collaborate in this research with my statistical knowledge, which is very necessary to be able to work with entomopathogens.

Ramiro Remigio Gaibor-Fernández, Universidad Tecnica Estatal de Quevedo

During my experience acquired in my years of teaching at the State Technical University of Quevedo, I have had the opportunity to be part of some research projects and undergraduate students, among which for the purposes of this project my thesis of Agricultural Engineer stands out through the management of fertilizers in corn. My thesis allowed me to learn about the problems of the region in cultivation and its importance. I think my profile fits satisfactorily for this project which could be of great help.

Published

2022-11-19

How to Cite

Vinces-Tachong, R. E., Vélez-Ruiz, M. C., Gaibor-Fernández, R. R., & Herrera-Eguez, F. E. (2022). Implementation of image processing for the evaluation of tar spot (Phyllachora maydis) in corn (Zea mays). REVISTA TERRA LATINOAMERICANA, 40. https://doi.org/10.28940/terra.v40i0.1066

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Section

Agricultura Sustentable: Investigación en América Latina

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