Determining the height of cotton plants (Gossypium hirsutum L.) Malvaceae f. with the assistance of a drone
DOI:
https://doi.org/10.14295/bjs.v3i4.516Keywords:
drone, geoprocessing, Gossypium hirsutum, genus Gossypium, vegetative morphological parametersAbstract
The use of drones in crop assessment has become increasingly common. The use of drones presents benefits for evaluating the height of plants in various crops, including cotton, checking nutritional, phytosanitary, genetic parameters, abiotic and biotic effects. The objective of this study was to evaluate the use of drones to aid in the evaluation of trials in cotton cultivation. The study was carried out at the Goiano Institute of Agriculture, located in the municipality of Montividiu, State of Goiás, Brazil. A Phantom 4 Pro drone was used to carry out the mapping and WebODM was used to carry out photogrammetry and obtain a digital model of the surface area in the cotton field. In the experimental design, 4 randomized blocks with 10 treatments were used. The results demonstrated that there was no difference between the four blocks for vegetative index. The digital surface model proved to be efficient in detecting possible differences between the analyzed blocks. This analysis is essential to understand variations in response to cotton cultivation in different blocks and identify possible factors that contribute to these differences.
References
Albetis, J. O., Torres-Sánchez, J., Peña, J. M., & López-Granados, F. (2016). Assessment of different methodologies for height estimation in crops using UAVs. Computers and Electronics in Agriculture, 128, 109-123.
Anderson, V., Leung, A. C., Mehdipoor, H., Jänicke, B., Milošević, D., Oliveira, A., & Zurita-Milla, R. (2021). Tehcnological opportunities for sensing of the health effects of weather and climate change: a state-of-the-art-review. International Journal of Biometeorology, 65, 779-803. https://doi.org/10.1007/s00484-020-02063-z DOI: https://doi.org/10.1007/s00484-020-02063-z
Bronson, K. F., Booker, J. D., Keeling, J. W., Boman, R. K., Wheeler, T. A., Lascano, R. J., & Nichols, R. L. (2005). Cotton canopy reflectance at landscape scale as affected by nitrogen fertilization. Agronomy Journal, 97(3), 654-660. https://doi.org/10.2134/agronj2004.0093 DOI: https://doi.org/10.2134/agronj2004.0093
Brito, P. S. (2020). Comunicando a sustentabilidade: "Sou de Algodão". Uma campanha voltada para a sustentabilidade do setor algodoeiro brasileiro. Tese de Doutorado.
Constable, G. A., & Roth, G. W. (2019). Cotton Production Manual. University of California Agriculture and Natural Resources.
Da Silva, I. S., & Lima, R. A. (2023). Dificuldades e benefícios para a produção do algodoeiro (Gossypium Hirsutum L.) no norte do Brasil. Educamazônia-Educação, Sociedade e Meio Ambiente, 16 (2), 279-288.
Fang, D. D. (2015). Cotton Fiber Development: Insights from Genomics and Proteomics. Springer.
Galbieri, R., & Asmus, G. L. (2016). Principais espécies de nematoides do algodoeiro no Brasil. In: Nematoides fitoparasitas do algodoeiro nos cerrados brasileiros: Biologia e medidas de controle. IMAmt, p. 11-36.
Hassanalian, M., & Abdelkefi, A. (2017). Classifications, applications, and design challenger of drones: A review. Progress in Aerospace Sciences, 91, 99-131. https://doi.org/10.1016/j.paerosci.2017.04.003 DOI: https://doi.org/10.1016/j.paerosci.2017.04.003
Khan, Z., Shafique, M., & Sun, Z. (2019). Estimating cotton plant height using multi-view UAV imagery. Remote Sensing, 11(13), 1502.
Lamas, F. M. (2017). Manejo do perfil dos solos cultivados com o algodoeiro no Brasil. In: Congresso Brasileiro De Algodão, 11, Maceió. Inovação e rentabilidade da cotonicultura: livro de resumos. Brasília, DF: Associação Brasileira dos Produtores de Algodão.
Li, H., Lascano, R. J., Barnes, E. M., Booker, J., Wilson, L. T., Bronson, K. F., & Segarra, E. (2001). Multispectral reflectance of cotton related to plant growth, soil water, texture, and site elevation. Agronomy Journal, 93(6), 1327-1337. https://doi.org/10.2134/agronj2001.1327 DOI: https://doi.org/10.2134/agronj2001.1327
Li, Z., Yang, G., Liu, C., & Zhang, Y. (2017). Estimating cotton plant height using a low-cost unmanned aerial vehicle. Remote Sensing, 9(6), 588.
Lillesand, T. M., Zang, S., Zhang, B., Li, S., & Wu, C. (2014). Remote Sensing and Image Interpretation.
Percy, R. G., & Ulloa, M. (2020). Cotton. CABI Publishing.
Oliveira, J. T., Maradini, P. S., Borges, A. C., & Gava, R. (2023). Viabilidade da fertirrigação por pivô central com uso de efluentes tratados em diferentes níveis. Nativa, 9(1), 23-29. https://doi.org/10.31413/nativa.v9i1.10884 DOI: https://doi.org/10.31413/nativa.v9i1.10884
Puia, J. D., Martins, B. R., Borsato, L. C., & Vigo, S. C. (2021). Comportamento diferencial de linhagens de algodão a Cercospora gossypina. Nativa, 9(2), 163-166. https://doi.org/10.31413/nativa.v9i2.10834 DOI: https://doi.org/10.31413/nativa.v9i2.10834
Raphael, J. P. A. (2019). Tecnologias transgênicas na cultura do algodoeiro no Brasil: revisão. In: Colloquium Agrariae, 15(1), 115-129.
Sankaran, S., Khot, L. R., Espinoza, C. Z., Jarolmasjed, S., Sathuvalli, V. R., & Vandemark, G. J. (2015). Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review. European Journal of Agronomy, 70, 112-123. DOI: https://doi.org/10.1016/j.eja.2015.07.004
Sankaran, S., Khot, L. R., Espinoza, C. Z., Jarolmasjed, S., Sathuvalli, V. R., Vandemark, G. J., & Pavek, M. J (2015). Precision Agriculture and Drones: A Review of the Current, State of the Art. Computadores e Eletrônicos na Agricultura , 182 , 106019.
Shakir, A., Karim, S., Qadir, A., Farooq, U., Shakir, M., & Laghari, A. A. (2018). Aerial Imagery in Agriculture: A Review. Current Medical Imaging, 19(5), 417-427.
Shil, S. (2018). Weather parameters and it’s impact on agricultural production – A review. Innovative Farming – An International Peer Reviewed Journal of Agriculture and Allied Sciences, 3(4), 141-149. https://www.innovativefarming.in/index.php/IF/article/view/55
Silva, J. V. B., Gomes, R. S. S., Carvalho, T. K. N., Lacerda, A. V., Rodrigues, R. M., & Medeiros, J. G. F. (2022). Controle de patógenos em sementes de algodão com o uso de Trichoderma harzianum. Nativa, 10(2), 204-210. https://doi.org/10.31413/nativa.v10i2.13563 DOI: https://doi.org/10.31413/nativa.v10i2.13563
Smith, C. W., & Cothren, J. T. (2019). Cotton: Origin, History, Technology, and Production. Wiley-Blackwell.
Stewart, J. M., Oosterhuis, D. M., Heitholt, J. J., & Mauney, J. R. (2018). Physiology of Cotton. Springer Science & Business Media.
Thenkabail, P. S., Smith, B. B., & Pauw, E. (2000). Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sensing of Environment, 71(2), 158-182. https://doi.org/10.1016/S0034-4257(99)00067-X DOI: https://doi.org/10.1016/S0034-4257(99)00067-X
Torres-Sánchez, J. (2018). Applications of unmanned aerial vehicles in agriculture and environment: A review. Precision Agriculture. Agronomia , 11 (2), 203.
Yang, G., Liu, H., Xu, B., & Zhang, X. (2018). Estimating crop height using an unmanned aerial vehicle in the field growth period. Computers and Electronics in Agriculture, 144, 202-209.
Zhang, J., & Yang, G. (2018). Estimating cotton plant height with an unmanned aerial vehicle using a structure-from-motion approach. Precision Agriculture, 19(3), 542-556.
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Copyright (c) 2024 Jeremias Silva de Sousa, Adriano Guimarães Pereira, Hugo Manoel de Souza, Igor Vinicius dos Santos Araújo, Daniel Noe Coaguila Nuñez
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