Identifying Growth Patterns in Arid-Zone Onion Crops (Allium Cepa) Using Digital Image Processing
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Published:2023-05-10
Issue:3
Volume:11
Page:67
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ISSN:2227-7080
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Container-title:Technologies
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language:en
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Short-container-title:Technologies
Author:
Duarte-Correa David1ORCID, Rodríguez-Reséndiz Juvenal1ORCID, Díaz-Flórez Germán2ORCID, Olvera-Olvera Carlos Alberto2ORCID, Álvarez-Alvarado José M.1ORCID
Affiliation:
1. Facultad de Ingeniería, Universidad Autónoma de Querétaro, Querétaro 76010, Mexico 2. Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas “Francisco García Salinas”, Jardín Juárez 147, Zacatecas 98000, Mexico
Abstract
The agricultural sector is undergoing a revolution that requires sustainable solutions to the challenges that arise from traditional farming methods. To address these challenges, technical and sustainable support is needed to develop projects that improve crop performance. This study focuses on onion crops and the challenges presented throughout its phenological cycle. Unmanned aerial vehicles (UAVs) and digital image processing were used to monitor the crop and identify patterns such as humid areas, weed growth, vegetation deficits, and decreased harvest performance. An algorithm was developed to identify the patterns that most affected crop growth, as the average local production reported was 40.166 tons/ha. However, only 25.00 tons/ha were reached due to blight caused by constant humidity and limited sunlight. This resulted in the death of leaves and poor development of bulbs, with 50% of the production being medium-sized. Approximately 20% of the production was lost due to blight and unfavorable weather conditions.
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