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Estimation of Biophysical Parameters of Forage Cactus Under Different Agricultural Systems Through Vegetation Indices and Machine Learning Using RGB Images Acquired with Unmanned Aerial Vehicles

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da Silva, Gabriel Italo Novaes ; Jardim, Alexandre Manicoba da Rosa Ferraz ; dos Santos, Wagner Martins ; Bezerra, Alan Cezar ; Alba, Elisiane ; da Silva, Marcos Vinicius ; da Silva, Jhon Lennon Bezerra ; de Souza, Luciana Sandra Bastos ; Marinho, Gabriel Thales Barboza ; Montenegro, Abelardo Antonio de Assuncao ; da Silva, Thieres George Freire
Número total de Autores: 11
Tipo de documento: Artigo Científico
Fonte: AGRICULTURE-BASEL; v. 14, n. 12, p. 16-pg., 2024-12-01.
Resumo

The objective of this study was to correlate the biophysical parameters of forage cactus with visible vegetation indices obtained by unmanned aerial vehicles (UAVs) and predict them with machine learning in different agricultural systems. Four experimental units were conducted. Units I and II had different plant spacings (0.10, 0.20, 0.30, 0.40, and 0.50 m) with East-West and North-South planting directions, respectively. Unit III had row spacings (1.00, 1.25, 1.50, and 1.75 m), and IV had cutting frequencies (6, 9, 12 + 6, and 18 months) with the clones "Orelha de Elefante Mexicana", "Mi & uacute;da", and "IPA Sert & acirc;nia". Plant height and width, cladode area index, fresh and dry matter yield (FM and DM), dry matter content, and fifteen vegetation indices of the visible range were analyzed. The RGBVI and ExGR indices stood out for presenting greater correlations with FM and DM. The prediction analysis using the Random Forest algorithm, highlighting DM, which presented a mean absolute error of 1.39, 0.99, and 1.72 Mg ha-1 in experimental units I and II, III, and IV, respectively. The results showed potential in the application of machine learning with RGB images for predictive analysis of the biophysical parameters of forage cactus. (AU)

Processo FAPESP: 23/05323-4 - Fenologia vegetal e informações ambientais para biodiversidade e mudanças climáticas
Beneficiário:Alexandre Maniçoba da Rosa Ferraz Jardim
Modalidade de apoio: Bolsas no Brasil - Programa Capacitação - Treinamento Técnico
Processo FAPESP: 17/22269-2 - Transição para sustentabilidade e o nexo água-agricultura-energia: explorando uma abordagem integradora com casos de estudo nos biomas Cerrado e Caatinga
Beneficiário:Jean Pierre Henry Balbaud Ometto
Modalidade de apoio: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Temático